From f34ec92ce5ef5fae1e420c1e19a4631d080030c8 Mon Sep 17 00:00:00 2001 From: bastonero Date: Fri, 8 Sep 2023 12:57:49 +0000 Subject: [PATCH 01/22] On-the-fly training via AiiDA and FLARE :rocket: I implement in the `AiiDAEnsemble` a first version of on-the-fly training using the FLARE code, which exploits (sparse) Gaussian processes and the ACE/MB descriptors to train and make estimations of the errors. --- .gitignore | 3 + .pre-commit-config.yaml | 54 +++ Modules/Ensemble.py | 94 ++++- Modules/aiida_ensemble.py | 378 +++++++++++++++----- tests/aiida_ensemble/get_sgp.py | 171 +++++++++ tests/aiida_ensemble/test_aiida_ensemble.py | 1 + tests/aiida_ensemble/test_otf_flare.py | 152 ++++++++ 7 files changed, 767 insertions(+), 86 deletions(-) create mode 100644 .pre-commit-config.yaml create mode 100644 tests/aiida_ensemble/get_sgp.py create mode 100644 tests/aiida_ensemble/test_otf_flare.py diff --git a/.gitignore b/.gitignore index 29130e0c..511c17ae 100644 --- a/.gitignore +++ b/.gitignore @@ -64,6 +64,9 @@ scf_population*.dat frequencies*.* timer.json minim.dat +otf_run* +disp_* +_data_tmp_ # Translations *.mo diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..09a819de --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,54 @@ +repos: +- repo: https://github.com/pre-commit/pre-commit-hooks + rev: 'v4.1.0' + hooks: + - id: double-quote-string-fixer + - id: end-of-file-fixer + - id: fix-encoding-pragma + - id: mixed-line-ending + - id: trailing-whitespace + exclude: >- + (?x)^( + tests/.*.*out| + tests/.*.in$ + )$ + +- repo: https://github.com/ikamensh/flynt/ + rev: '0.76' + hooks: + - id: flynt + +- repo: https://github.com/pycqa/isort + rev: '5.12.0' + hooks: + - id: isort + +- repo: https://github.com/pre-commit/mirrors-yapf + rev: 'v0.32.0' + hooks: + - id: yapf + name: yapf + types: [python] + args: ['-i'] + exclude: &exclude_files > + (?x)^( + docs/.*| + tests/.*(? Ry/Bohr^3 + + gpa_to_rybohr3 = 1.0 / (CONSTANTS.ry_si / CONSTANTS.bohr_si**3 / 1.0e9) # GPa -> Ry/Bohr^3 + ase_stress_units = -1.0 * gpa_to_rybohr3 * units.Ry / units.Bohr**3 # convention as in ASE (sign and eV/Ang^3) except ImportError: import warnings warnings.warn('aiida or aiida-quantumespresso are not installed') +try: + from flare.atoms import FLARE_Atoms + from flare.learners.utils import get_env_indices, is_std_in_bound +except ImportError: + pass + class AiiDAEnsemble(Ensemble): """Ensemble subclass to interface SSCHA with aiida-quantumespresso.""" - def compute_ensemble( - self, + def compute_ensemble( # pylint: disable=arguments-renamed + self, pw_code: str, protocol: str = 'moderate', options: dict = None, overrides: dict = None, group_label: str = None, **kwargs - ): + ) -> None: """Get ensemble properties. - All the parameters refer to the + All the parameters refer to the :func:`aiida_quantumespresso.workflows.pw.base.PwBaseWorkChain.get_builder_from_protocol` method. - Parameters - --------- - pw_code: - The string associated with the AiiDA code for `pw.x` - protocol: - The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' - options: - The options for the calculations, such as the resources, wall-time, etc. - overrides: - The overrides for the get_builder_from_protocol - group_label: - The group label where to add the submitted nodes for eventual future inspection - kwargs: - The kwargs for the get_builder_from_protocol + Args: + ---- + pw_code: The string associated with the AiiDA code for `pw.x` + protocol: The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' + options: The options for the calculations, such as the resources, wall-time, etc. + overrides: The overrides for the get_builder_from_protocol + group_label: The group label where to add the submitted nodes for eventual future inspection + kwargs: The kwargs for the get_builder_from_protocol + """ from aiida.orm import load_group - - group = None if group_label is None else load_group(group_label) - + + group = None if group_label is None else load_group(group_label) + # Check if not all the calculation needs to be done if self.force_computed is None: self.force_computed = np.array([False] * self.N, dtype=bool) - n_calcs = np.sum(self.force_computed.astype(int)) + n_calcs = np.sum(self.force_computed.astype(int)) computing_ensemble = self - self.has_stress = True # by default we calculate stresses with the `get_builder_from_protocol` + self.has_stress = True # by default we calculate stresses with the `get_builder_from_protocol` if overrides: try: tstress = overrides['pw']['parameters']['CONTROL']['tstress'] @@ -76,51 +82,272 @@ def compute_ensemble( should_i_merge = True computing_ensemble = self.get_noncomputed() self.remove_noncomputed() - - # ============= AIIDA SECTION ============= # + + structures = copy(computing_ensemble.structures) + dft_indices = np.arange(0, len(structures), 1).tolist() # store here the indices to run with DFT/AiiDA + + # ============= FLARE SECTION ============= # + # If a model is specified and it's not empty, try to predict. + # Predict only the ones that are within uncertainty, the rest do via DFT/AiiDA. + if self.gp_model is not None: + if self.max_atoms_added < 0: + self.max_atoms_added = structures[0].get_ase_atoms().get_global_number_of_atoms() + if len(self.gp_model.training_data) > 0: + self._predict_with_model(structures, computing_ensemble, dft_indices) + + # ============= AIIDA SECTION START ============= # workchains = submit_and_get_workchains( - structures=computing_ensemble.structures, + structures=[structures[i] for i in dft_indices], pw_code=pw_code, temperature=self.current_T, + dft_indices=dft_indices, protocol=protocol, options=options, overrides=overrides, **kwargs ) - + if group: group.add_nodes(workchains) workchains_copy = copy(workchains) - while(workchains_copy): + while workchains_copy: workchains_copy = get_running_workchains(workchains_copy, computing_ensemble.force_computed) if workchains_copy: - time.sleep(60) # wait before checking again - + time.sleep(60) # wait before checking again + for i, is_computed in enumerate(computing_ensemble.force_computed): if is_computed: - out = workchains[i].outputs - computing_ensemble.energies[i] = out.output_parameters.dict.energy / CONSTANTS.ry_to_ev - computing_ensemble.forces[i] = out.output_trajectory.get_array('forces')[-1] / CONSTANTS.ry_to_ev + dft_stress = None + wc = workchains[dft_indices.index(i)] + dft_energy = wc.outputs.output_parameters.dict.energy + dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] + computing_ensemble.energies[i] = dft_energy / CONSTANTS.ry_to_ev + computing_ensemble.forces[i] = dft_forces / CONSTANTS.ry_to_ev if self.has_stress: - computing_ensemble.stresses[i] = out.output_trajectory.get_array('stress')[-1] * gpa_to_rybohr3 - # ============= AIIDA SECTION ============= # + stress = wc.outputs.output_trajectory.get_array('stress')[-1] + computing_ensemble.stresses[i] = stress * gpa_to_rybohr3 + dft_stress = ase_stress_units * np.array([ + stress[0, 0], stress[1, 1], stress[2, 2], stress[1, 2], stress[0, 2], stress[0, 1] + ]) + + if self.gp_model is not None: + self._update_gp( + FLARE_Atoms.from_ase_atoms(wc.inputs.pw.structure.get_ase()), + dft_frcs=dft_forces, + dft_energy=dft_energy, + dft_stress=dft_stress, + ) + # ============= AIIDA SECTION END ============= # + if self.gp_model is not None: + self._train_gp() + self._write_model() + + # ============= FINALIZE ============= # if self.has_stress: computing_ensemble.stress_computed = copy(computing_ensemble.force_computed) - print("CE BEFORE MERGE:", len(self.force_computed)) + print('CE BEFORE MERGE:', len(self.force_computed)) if should_i_merge: - # Remove the noncomputed ensemble from here, and merge - self.merge(computing_ensemble) - print("CE AFTER MERGE:", len(self.force_computed)) + self.merge(computing_ensemble) # Remove the noncomputed ensemble from here, and merge + print('CE AFTER MERGE:', len(self.force_computed)) + + def _predict_with_model( + self, + structures: list[Structure], + computing_ensemble: Ensemble, + dft_indices: list[int], + ) -> None: + """Predict on all the structures and estimate errors. + + This is used to remove the structures indecis to not compute via AiiDA/DFT. + + Args: + ---- + structures: list of :class:`~cellconstructor.Structure.Structure` to simulate + computing_ensemble: the :class:`~sscha.Ensemble` with the forces to compute + dft_indices: list of integers related to the structures + + """ + for index, structure in enumerate(structures): + atoms = FLARE_Atoms.from_ase_atoms(structure.get_ase_atoms()) + self._compute_properties(atoms) + + # get max uncertainty atoms + if self.build_mode == 'bayesian': + env_selection = is_std_in_bound + elif self.build_mode == 'direct': + env_selection = get_env_indices + + tic = time.time() + + std_in_bound, _ = env_selection( + self.std_tolerance, + self.gp_model.force_noise, + atoms, + max_atoms_added=self.max_atoms_added, + update_style=self.update_style, + update_threshold=self.update_threshold, + ) + + self.output.write_wall_time(tic, task='Env Selection') + + if std_in_bound: + dft_indices.remove(index) # remove index computed via ML-FF + + computing_ensemble.energies[index] = atoms.potential_energy / units.Ry + computing_ensemble.forces[index] = deepcopy(atoms.forces) / units.Ry + if self.has_stress: + computing_ensemble.stresses[index] = -1 * deepcopy( + atoms.get_stress(voigt=False) + ) * units.Bohr**3 / units.Ry + + computing_ensemble.force_computed[index] = True + + def _compute_properties(self, atoms: FLARE_Atoms) -> None: + """Compute energies, forces, stresses, and their uncertainties. + + The FLARE ASE calculator is used, and write the results. + + Args: + ---- + atoms: a :class:`flare.atoms.FLARE_Atoms` instance for which to compute properties + + """ + tic = time.time() + + atoms.calc = self.flare_calc + atoms.calc.calculate(atoms) + + self.output.write_wall_time(tic, task='Compute Properties') + + def _write_model(self) -> None: + """Write the current model in a JSON file.""" + self.flare_calc.write_model(self.flare_name) + def _update_gp( + self, + atoms: FLARE_Atoms, + dft_frcs: ndarray, + dft_energy: float | None = None, + dft_stress: ndarray | None = None, + ) -> None: + """Update the current GP model. -def get_running_workchains(workchains: list, success: list[bool]) -> list: + Args: + ---- + atoms (FLARE_Atoms): :class:`flare.atoms.FLARE_Atoms`` instance whose + local environments will be added to the training set. + dft_frcs (np.ndarray): DFT forces on all atoms in the structure, in eV/Angstrom. + dft_energy (float): total energy of the entire structure, in eV. + dft_stress (np.ndarray): DFT forces on all atoms in the structure. + Sign as in ASE (-1 in respect with QE), units in eV/Angstrom^3, + and in Voigt notation, i.e. (xx, yy, zz, yz, xz, xy). + + """ + from ase.calculators.singlepoint import SinglePointCalculator + + tic = time.time() + + self._compute_properties(atoms) + + # get max uncertainty atoms + if self.build_mode == 'bayesian': + env_selection = is_std_in_bound + elif self.build_mode == 'direct': + env_selection = get_env_indices + + tic = time.time() + + std_in_bound, train_atoms = env_selection( + self.std_tolerance, + self.gp_model.force_noise, + atoms, + max_atoms_added=self.max_atoms_added, + update_style=self.update_style, + update_threshold=self.update_threshold, + ) + + self.output.write_wall_time(tic, task='Env Selection') + + # Here we make the decision to skip adding environments even if the + # DFT calculation was performed. This avoids slowing down the model, + # while the SSCHA is feeded with the DFT results. + if not std_in_bound: + stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) + self.output.add_atom_info(train_atoms, stds) + + # Convert ASE stress (xx, yy, zz, yz, xz, xy) to FLARE stress + # (xx, xy, xz, yy, yz, zz). + flare_stress = None + if dft_stress is not None: + flare_stress = -np.array([ + dft_stress[0], + dft_stress[5], + dft_stress[4], + dft_stress[1], + dft_stress[3], + dft_stress[2], + ]) + + results = { + 'forces': atoms.forces, + 'energy': atoms.potential_energy, + 'free_energy': atoms.potential_energy, + 'stress': atoms.stress, + } + + atoms.calc = SinglePointCalculator(atoms, **results) + + # update gp model + self.gp_model.update_db( + atoms, + dft_frcs, + custom_range=train_atoms, + energy=dft_energy, + stress=flare_stress, + ) + + self.gp_model.set_L_alpha() + self.output.write_wall_time(tic, task='Update GP') + + # write model + self._write_model() + + def _train_gp(self) -> None: + """Optimize the hyperparameters of the current GP model.""" + tic = time.time() + + self.gp_model.train(logger_name=self.output.basename + 'hyps') + + self.output.write_wall_time(tic, task='Train Hyps') + + hyps, labels = self.gp_model.hyps_and_labels + if labels is None: + labels = self.gp_model.hyp_labels + + self.output.write_hyps( + labels, + hyps, + tic, # actually here there should be the actual start time of the entire simulation + self.gp_model.likelihood, + self.gp_model.likelihood_gradient, + hyps_mask=self.gp_model.hyps_mask, + ) + + +def get_running_workchains(workchains: list[WorkChainNode], success: list[bool]) -> list: """Get the running workchains popping the finished ones. - + Two extra array should be given to populate the successfully finished runs. + + Args: + ---- + workchains: list of :class:`~aiida.orm.WorkChainNode` + success: list where to store whether the workchains finished successfully or not. + """ wcs_left = copy(workchains) @@ -132,60 +359,51 @@ def get_running_workchains(workchains: list, success: list[bool]) -> list: index = int(workchain.label.split('_')[-1]) success[index] = True print(f'[SUCCESS] for with PK={workchain.pk}') - - wcs_left.remove(workchain) # here it may be critical - + + wcs_left.remove(workchain) # here it may be critical + return wcs_left def submit_and_get_workchains( - structures: list[cellconstructor.Structure.Structure], + structures: list[Structure], pw_code: str, temperature: float | int, + dft_indices: list[int], protocol: str = 'moderate', options: dict = None, overrides: dict = None, **kwargs -): +) -> list[WorkChainNode]: """Submit and return the workchains for a list of :class:`~cellconstructor.Structure.Structure`. - Parameters - --------- - structures: - a list of :class:`~cellconstructor.Structure.Structure` to run via PwBaseWorkChain. - pw_code: - The string associated with the AiiDA code for `pw.x` - temperature: - The temperature corresponding to the structures ensemble - protocol: - The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' - options: - The options for the calculations, such as the resources, wall-time, etc. - overrides: - The overrides for the get_builder_from_protocol - kwargs: - The kwargs for the get_builder_from_protocol + Args: + ---- + structures: a list of :class:`~cellconstructor.Structure.Structure` to run via PwBaseWorkChain. + pw_code: The string associated with the AiiDA code for `pw.x` + temperature: The temperature corresponding to the structures ensemble + dft_indices: The indices of the compute ensemble related to the structures. + protocol: The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' + options: The options for the calculations, such as the resources, wall-time, etc. + overrides: The overrides for the get_builder_from_protocol + kwargs: The kwargs for the get_builder_from_protocol + """ from aiida.engine import submit - from aiida.plugins import WorkflowFactory from aiida.orm import StructureData + from aiida.plugins import WorkflowFactory PwBaseWorkChain = WorkflowFactory('quantumespresso.pw.base') structures_data = [StructureData(ase=cc.get_ase_atoms()) for cc in structures] workchains = [] - for i, structure in enumerate(structures_data): + for i, structure in zip(dft_indices, structures_data): builder = PwBaseWorkChain.get_builder_from_protocol( - code=pw_code, - structure=structure, - protocol=protocol, - options=options, - overrides=overrides, - **kwargs + code=pw_code, structure=structure, protocol=protocol, options=options, overrides=overrides, **kwargs ) - builder.metadata.label = 'T_{}_id_{}'.format(temperature, i) + builder.metadata.label = f'T_{temperature}_id_{i}' workchains.append(submit(builder)) print(f'Launched with PK={workchains[-1].pk}') - - return workchains \ No newline at end of file + + return workchains diff --git a/tests/aiida_ensemble/get_sgp.py b/tests/aiida_ensemble/get_sgp.py new file mode 100644 index 00000000..ed71c8cc --- /dev/null +++ b/tests/aiida_ensemble/get_sgp.py @@ -0,0 +1,171 @@ +import numpy as np +from flare.bffs.sgp._C_flare import NormalizedDotProduct, DotProduct, B2 +from flare.bffs.sgp import SGP_Wrapper +from flare.bffs.sgp.calculator import SGP_Calculator +from flare.atoms import FLARE_Atoms +from ase import Atoms +from ase.calculators.lj import LennardJones +from ase.build import make_supercell + +# Define kernel. +sigma = 2.0 +power = 1.0 +dotprod_kernel = DotProduct(sigma, power) +normdotprod_kernel = NormalizedDotProduct(sigma, power) + +# Define remaining parameters for the SGP wrapper. +sigma_e = 0.3 +sigma_f = 0.2 +sigma_s = 0.1 +species_map = {6: 0, 8: 1} +single_atom_energies = {0: -5, 1: -6} +variance_type = "local" +max_iterations = 20 +opt_method = "L-BFGS-B" +bounds = [(None, None), (sigma_e, None), (None, None), (None, None)] + + +def get_atoms(a=2.0, sc_size=2, numbers=[6, 8]) -> Atoms: + """Return an ase.Atoms instance.""" + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) + unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) + multiplier = np.identity(3) * sc_size + atoms = make_supercell(unit_cell, multiplier) + + return atoms + + +def get_random_atoms(a=2.0, sc_size=2, numbers=[6, 8], set_seed: int = 0) -> FLARE_Atoms: + """Create a random structure.""" + if set_seed: + np.random.seed(set_seed) + + atoms = get_atoms(a, sc_size, numbers) + atoms.positions += (2 * np.random.rand(len(atoms), 3) - 1) * 0.05 + flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) + + return flare_atoms + + +def get_isolated_atoms(numbers=[6, 8]) -> FLARE_Atoms: + """Create a random structure.""" + a = 30.0 + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [1, 1, 1], [a / 2, a / 2, a / 2]]) + if 8 in numbers: + numbers = [6, 8, 8] + else: + numbers = [6, 6, 6] + unit_cell = Atoms(cell=cell, positions=positions, numbers=numbers, pbc=True) + atoms = unit_cell + flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) + + return flare_atoms + + +def get_empty_sgp(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: + """Return an empty SGP model.""" + if kernel_type == "NormalizedDotProduct": + kernel = normdotprod_kernel + elif kernel_type == "DotProduct": + kernel = dotprod_kernel + + kernel.power = power + + # Define B2 calculator. + cutoff = 5.0 + cutoff_function = "quadratic" + radial_basis = "chebyshev" + radial_hyps = [0.0, cutoff] + cutoff_hyps = [] + cutoff_matrix = cutoff * np.ones((n_types, n_types)) + if multiple_cutoff: + cutoff_matrix += np.eye(n_types) - 1 + + descriptor_settings = [n_types, 3, 2] + b2_calc = B2( + radial_basis, + cutoff_function, + radial_hyps, + cutoff_hyps, + descriptor_settings, + cutoff_matrix, + ) + + empty_sgp = SGP_Wrapper( + [kernel], + [b2_calc], + cutoff, + sigma_e, + sigma_f, + sigma_s, + species_map, + single_atom_energies=single_atom_energies, + variance_type=variance_type, + opt_method=opt_method, + bounds=bounds, + max_iterations=max_iterations, + ) + + return empty_sgp + + +def get_updated_sgp(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: + """Return the SGP updated with the new structure properties.""" + if n_types == 1: + numbers = [6, 6] + elif n_types == 2: + numbers = [6, 8] + + sgp = get_empty_sgp(n_types, power, multiple_cutoff, kernel_type) + + # add a random structure to the training set + training_structure = get_random_atoms(numbers=numbers) + training_structure.calc = LennardJones() + + forces = training_structure.get_forces() + energy = training_structure.get_potential_energy() + stress = training_structure.get_stress() + + sgp.update_db( + training_structure, + forces, + custom_range=(1, 2, 3, 4, 5), + energy=energy, + stress=stress, + mode="specific", + rel_e_noise=0.1, + rel_f_noise=0.2, + rel_s_noise=0.1, + ) + + # add an isolated atom to the training data + training_structure = get_isolated_atoms(numbers=numbers) + training_structure.calc = LennardJones() + + forces = training_structure.get_forces() + energy = training_structure.get_potential_energy() + stress = training_structure.get_stress() + + custom_range = [0] + sgp.update_db( + training_structure, + forces, + custom_range=custom_range, + energy=energy, + stress=stress, + mode="specific", + ) + + print("sparse_indices", sgp.sparse_gp.sparse_indices) + + return sgp + + +def get_sgp_calc(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Calculator: + """Return an SGP calculator, ASE type.""" + sgp = get_updated_sgp(n_types, power, multiple_cutoff, kernel_type) + sgp_calc = SGP_Calculator(sgp) + + return sgp_calc diff --git a/tests/aiida_ensemble/test_aiida_ensemble.py b/tests/aiida_ensemble/test_aiida_ensemble.py index 53d2f8c1..6773e152 100644 --- a/tests/aiida_ensemble/test_aiida_ensemble.py +++ b/tests/aiida_ensemble/test_aiida_ensemble.py @@ -48,6 +48,7 @@ def test_submit_and_get_workchains(fixture_code): structures=structures, pw_code=pw_code, temperature=300, + dft_indices=[0,1,2,3,4], ) assert len(workchains) == 5 diff --git a/tests/aiida_ensemble/test_otf_flare.py b/tests/aiida_ensemble/test_otf_flare.py new file mode 100644 index 00000000..3345b069 --- /dev/null +++ b/tests/aiida_ensemble/test_otf_flare.py @@ -0,0 +1,152 @@ +"""Tests for :mod:`sscha.aiida_ensemble`.""" +import pytest +import numpy as np + +from ase import Atoms +from ase.calculators.lj import LennardJones + +from flare.atoms import FLARE_Atoms +from .get_sgp import get_sgp_calc, get_random_atoms + + +@pytest.fixture +def generate_structure(): + """Return an :class:`cellconstructor.Structure.Structure` instance.""" + + def _generate_structure(a=2.0, sc_size=2, numbers=[6, 8]): + """Return an :class:`cellconstructor.Structure.Structure` instance.""" + import numpy as np + from ase.build import make_supercell + from cellconstructor.Structure import Structure + + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) + unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) + multiplier = np.identity(3) * sc_size + atoms = make_supercell(unit_cell, multiplier) + + structure = Structure() + structure.generate_from_ase_atoms(atoms) + + return structure + + return _generate_structure + + +@pytest.fixture +def generate_ensemble(generate_structure): + """Return an AiiDAEnsemble instance.""" + + def _generate_ensemble(temperature: float = 0.0): + """Return an AiiDAEnsemble instance.""" + from cellconstructor.Phonons import compute_phonons_finite_displacements + from sscha.aiida_ensemble import AiiDAEnsemble + + dyn = compute_phonons_finite_displacements(generate_structure(), LennardJones(), supercell=[1,1,1]) + dyn.Symmetrize() + dyn.ForcePositiveDefinite() + + return AiiDAEnsemble(dyn, temperature) + + return _generate_ensemble + + +def test_no_otf(generate_ensemble): + """Test the :class:`sscha.aiida_ensemble.AiiDAEnsemble` initialization parameters w/o OTF. + + .. note:: this test shouldn't be here, but in the tests for generic Ensemble. + """ + ensemble = generate_ensemble() + + assert ensemble.gp_model is None + assert ensemble.flare_calc is None + assert ensemble.std_tolerance is None + assert ensemble.max_atoms_added is None + assert ensemble.update_style is None + assert ensemble.update_threshold is None + assert ensemble.build_mode is None + assert ensemble.output is None + assert ensemble.output_name is None + assert ensemble.checkpt_name is None + assert ensemble.flare_name is None + assert ensemble.atoms_name is None + assert ensemble.checkpt_files is None + assert ensemble.write_model is None + + +def test_set_otf(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble.set_otf` method.""" + ensemble = generate_ensemble() + flare_calc = get_sgp_calc() + ensemble.set_otf(flare_calc, max_atoms_added=-1) + + assert ensemble.gp_model is not None + + +def test_compute_properties(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._compute_properties` method.""" + ensemble = generate_ensemble() + ensemble.generate(20) + atoms = ensemble.structures[0].get_ase_atoms() + ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + + ensemble._compute_properties(atoms) + + +def test_predict_with_model(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._predict_with_model` method.""" + num_configs = 20 + ensemble = generate_ensemble() + ensemble.generate(num_configs) + ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + + dft_indices = np.arange(0,num_configs,1).tolist() + + ensemble._predict_with_model( + ensemble.structures, + ensemble, + dft_indices + ) + + assert dft_indices == [] + assert len(ensemble.force_computed) == num_configs + assert all(ensemble.force_computed) + + +def test_write_model(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._write_model` method. + + .. note:: in principle here we should double check with a regression test that + the json file is formatted as expected. + """ + ensemble = generate_ensemble() + ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + + ensemble._write_model() + + +def test_update_gp(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._update_gp` method.""" + ensemble = generate_ensemble() + ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + + atoms = get_random_atoms() + atoms.calc = LennardJones() + forces = atoms.get_forces() + energy = atoms.get_potential_energy() + stress = atoms.get_stress() + + ensemble._update_gp( + FLARE_Atoms.from_ase_atoms(atoms), + forces, + energy, + stress + ) + + +def test_train_gp(generate_ensemble): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._train_gp` method.""" + ensemble = generate_ensemble() + ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + + ensemble._train_gp() \ No newline at end of file From 4a93dda1735791a019c42a8448b6e1f51d5710d7 Mon Sep 17 00:00:00 2001 From: bastonero Date: Sat, 9 Sep 2023 00:11:17 +0000 Subject: [PATCH 02/22] Fix logic for on-the-fly training --- .gitignore | 1 + Modules/Ensemble.py | 14 +- Modules/aiida_ensemble.py | 145 +- tests/aiida_ensemble/dyn1 | 4148 ++++++++++++ tests/aiida_ensemble/dyn2 | 6457 +++++++++++++++++++ tests/aiida_ensemble/dyn3 | 4148 ++++++++++++ tests/aiida_ensemble/test_aiida_ensemble.py | 33 + tests/aiida_ensemble/test_otf_flare.py | 15 +- 8 files changed, 14893 insertions(+), 68 deletions(-) create mode 100644 tests/aiida_ensemble/dyn1 create mode 100644 tests/aiida_ensemble/dyn2 create mode 100644 tests/aiida_ensemble/dyn3 diff --git a/.gitignore b/.gitignore index 511c17ae..571ec6b8 100644 --- a/.gitignore +++ b/.gitignore @@ -65,6 +65,7 @@ frequencies*.* timer.json minim.dat otf_run* +nohup.out disp_* _data_tmp_ diff --git a/Modules/Ensemble.py b/Modules/Ensemble.py index 728d5ae5..9ae20918 100644 --- a/Modules/Ensemble.py +++ b/Modules/Ensemble.py @@ -163,6 +163,7 @@ def __init__(self, dyn0, T0, supercell = None, **kwargs): self.atoms_name = None self.checkpt_files = None self.write_model = None + self.init_atoms = None self.sscha_energies = [] self.sscha_forces = [] @@ -3505,6 +3506,7 @@ def set_otf( flare_calc, # flare args write_model: int = 0, + init_atoms: list[int] | None = None, # otf args std_tolerance_factor: float = 1, output_name: str = "otf_run", @@ -3514,7 +3516,16 @@ def set_otf( # other args build_mode="bayesian", ): - """Set on-the-fly training.""" + """Set on-the-fly training. + + Args: + ---- + init_atoms (List[int], optional): List of atoms from the input + structure whose local environments and force components are + used to train the initial GP model. If None is specified, all + atoms are used to train the initial GP. Defaults to None. + + """ from flare.io.output import Output from flare.bffs.gp.calculator import FLARE_Calculator from flare.bffs.sgp.calculator import SGP_Calculator @@ -3524,6 +3535,7 @@ def set_otf( self.flare_calc = flare_calc self.gp_model = flare_calc.gp_model + self.init_atoms = init_atoms # set otf self.std_tolerance = std_tolerance_factor diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index d8cb6103..f9065dbd 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -65,9 +65,6 @@ def compute_ensemble( # pylint: disable=arguments-renamed if self.force_computed is None: self.force_computed = np.array([False] * self.N, dtype=bool) - n_calcs = np.sum(self.force_computed.astype(int)) - computing_ensemble = self - self.has_stress = True # by default we calculate stresses with the `get_builder_from_protocol` if overrides: try: @@ -76,24 +73,23 @@ def compute_ensemble( # pylint: disable=arguments-renamed except KeyError: pass - # Check wheter compute the whole ensemble, or just a small part - should_i_merge = False - if n_calcs != self.N: - should_i_merge = True - computing_ensemble = self.get_noncomputed() - self.remove_noncomputed() - - structures = copy(computing_ensemble.structures) + structures = copy(self.structures) dft_indices = np.arange(0, len(structures), 1).tolist() # store here the indices to run with DFT/AiiDA # ============= FLARE SECTION ============= # # If a model is specified and it's not empty, try to predict. # Predict only the ones that are within uncertainty, the rest do via DFT/AiiDA. if self.gp_model is not None: + number_of_atoms = structures[0].get_ase_atoms().get_global_number_of_atoms() + if self.max_atoms_added < 0: - self.max_atoms_added = structures[0].get_ase_atoms().get_global_number_of_atoms() + self.max_atoms_added = number_of_atoms + + if self.init_atoms is None: + self.init_atoms = list(range(number_of_atoms)) + if len(self.gp_model.training_data) > 0: - self._predict_with_model(structures, computing_ensemble, dft_indices) + self._predict_with_model(structures, dft_indices) # ============= AIIDA SECTION START ============= # workchains = submit_and_get_workchains( @@ -112,23 +108,29 @@ def compute_ensemble( # pylint: disable=arguments-renamed workchains_copy = copy(workchains) while workchains_copy: - workchains_copy = get_running_workchains(workchains_copy, computing_ensemble.force_computed) + workchains_copy = get_running_workchains(workchains_copy, self.force_computed) if workchains_copy: time.sleep(60) # wait before checking again - for i, is_computed in enumerate(computing_ensemble.force_computed): - if is_computed: + for i, is_computed in enumerate(self.force_computed): + if is_computed and i in dft_indices: dft_stress = None wc = workchains[dft_indices.index(i)] + dft_energy = wc.outputs.output_parameters.dict.energy dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] - computing_ensemble.energies[i] = dft_energy / CONSTANTS.ry_to_ev - computing_ensemble.forces[i] = dft_forces / CONSTANTS.ry_to_ev + + self.energies[i] = dft_energy / CONSTANTS.ry_to_ev + self.forces[i] = dft_forces / CONSTANTS.ry_to_ev + if self.has_stress: stress = wc.outputs.output_trajectory.get_array('stress')[-1] - computing_ensemble.stresses[i] = stress * gpa_to_rybohr3 + + self.stresses[i] = stress * gpa_to_rybohr3 + dft_stress = ase_stress_units * np.array([ - stress[0, 0], stress[1, 1], stress[2, 2], stress[1, 2], stress[0, 2], stress[0, 1] + stress[0, 0], stress[1, 1], stress[2, 2], + stress[1, 2], stress[0, 2], stress[0, 1], ]) if self.gp_model is not None: @@ -146,18 +148,13 @@ def compute_ensemble( # pylint: disable=arguments-renamed # ============= FINALIZE ============= # if self.has_stress: - computing_ensemble.stress_computed = copy(computing_ensemble.force_computed) + self.stress_computed = copy(self.force_computed) - print('CE BEFORE MERGE:', len(self.force_computed)) - - if should_i_merge: - self.merge(computing_ensemble) # Remove the noncomputed ensemble from here, and merge - print('CE AFTER MERGE:', len(self.force_computed)) + self._clean_runs(dft_indices) def _predict_with_model( self, structures: list[Structure], - computing_ensemble: Ensemble, dft_indices: list[int], ) -> None: """Predict on all the structures and estimate errors. @@ -167,7 +164,6 @@ def _predict_with_model( Args: ---- structures: list of :class:`~cellconstructor.Structure.Structure` to simulate - computing_ensemble: the :class:`~sscha.Ensemble` with the forces to compute dft_indices: list of integers related to the structures """ @@ -194,17 +190,21 @@ def _predict_with_model( self.output.write_wall_time(tic, task='Env Selection') - if std_in_bound: + if not std_in_bound: + print(f"[DFT CALLED] For structure index {index}") + else: + print(f"[BFFS USED] For structure index {index}") dft_indices.remove(index) # remove index computed via ML-FF - - computing_ensemble.energies[index] = atoms.potential_energy / units.Ry - computing_ensemble.forces[index] = deepcopy(atoms.forces) / units.Ry + + self.energies[index] = atoms.potential_energy / units.Ry + self.forces[index] = deepcopy(atoms.forces) / units.Ry if self.has_stress: - computing_ensemble.stresses[index] = -1 * deepcopy( + self.stresses[index] = -1 * deepcopy( atoms.get_stress(voigt=False) ) * units.Bohr**3 / units.Ry - computing_ensemble.force_computed[index] = True + self.force_computed[index] = True + def _compute_properties(self, atoms: FLARE_Atoms) -> None: """Compute energies, forces, stresses, and their uncertainties. @@ -250,34 +250,40 @@ def _update_gp( from ase.calculators.singlepoint import SinglePointCalculator tic = time.time() + is_not_empty_model = len(self.gp_model.training_data) > 0 + + if is_not_empty_model: + self._compute_properties(atoms) - self._compute_properties(atoms) - - # get max uncertainty atoms - if self.build_mode == 'bayesian': - env_selection = is_std_in_bound - elif self.build_mode == 'direct': - env_selection = get_env_indices + # get max uncertainty atoms + if self.build_mode == 'bayesian': + env_selection = is_std_in_bound + elif self.build_mode == 'direct': + env_selection = get_env_indices - tic = time.time() + tic = time.time() - std_in_bound, train_atoms = env_selection( - self.std_tolerance, - self.gp_model.force_noise, - atoms, - max_atoms_added=self.max_atoms_added, - update_style=self.update_style, - update_threshold=self.update_threshold, - ) + std_in_bound, train_atoms = env_selection( + self.std_tolerance, + self.gp_model.force_noise, + atoms, + max_atoms_added=self.max_atoms_added, + update_style=self.update_style, + update_threshold=self.update_threshold, + ) - self.output.write_wall_time(tic, task='Env Selection') + self.output.write_wall_time(tic, task='Env Selection') + else: + std_in_bound = False + train_atoms = self.init_atoms # Here we make the decision to skip adding environments even if the # DFT calculation was performed. This avoids slowing down the model, # while the SSCHA is feeded with the DFT results. if not std_in_bound: - stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) - self.output.add_atom_info(train_atoms, stds) + if is_not_empty_model: + stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) + self.output.add_atom_info(train_atoms, stds) # Convert ASE stress (xx, yy, zz, yz, xz, xy) to FLARE stress # (xx, xy, xz, yy, yz, zz). @@ -293,10 +299,10 @@ def _update_gp( ]) results = { - 'forces': atoms.forces, - 'energy': atoms.potential_energy, - 'free_energy': atoms.potential_energy, - 'stress': atoms.stress, + 'forces': dft_frcs, + 'energy': dft_energy, + 'free_energy': dft_energy, + 'stress': flare_stress, } atoms.calc = SinglePointCalculator(atoms, **results) @@ -312,15 +318,13 @@ def _update_gp( self.gp_model.set_L_alpha() self.output.write_wall_time(tic, task='Update GP') - - # write model - self._write_model() + def _train_gp(self) -> None: """Optimize the hyperparameters of the current GP model.""" tic = time.time() - self.gp_model.train(logger_name=self.output.basename + 'hyps') + self.gp_model.train(logger_name=self.output_name + 'hyps.dat') self.output.write_wall_time(tic, task='Train Hyps') @@ -336,6 +340,25 @@ def _train_gp(self) -> None: self.gp_model.likelihood_gradient, hyps_mask=self.gp_model.hyps_mask, ) + + def _clean_runs(self, dft_indices: list[int]) -> None: + """Clean the failed runs and print summary. + + Args: + ---- + dft_indices (list[int]): list of performed dft indices calculations. + + """ + n_calcs = np.sum(self.force_computed.astype(int)) + print('=============== SUMMARY AIIDA CALCULATIONS =============== \n') + print('Total structures included: ', n_calcs) + print('Structures not included : ', self.N-n_calcs) + if self.gp_model is not None: + print('Steps using OTF-ML model : ', self.N-len(dft_indices)) + print() + print('===================== END OF SUMMARY ===================== \n') + if n_calcs != self.N: + self.remove_noncomputed() def get_running_workchains(workchains: list[WorkChainNode], success: list[bool]) -> list: diff --git a/tests/aiida_ensemble/dyn1 b/tests/aiida_ensemble/dyn1 new file mode 100644 index 00000000..4332e258 --- /dev/null +++ b/tests/aiida_ensemble/dyn1 @@ -0,0 +1,4148 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 24 0 5.36307068 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 +Basis vectors + 0.49334568 0.01129550 -0.85311514 + -0.03458521 1.75181777 0.00000000 + 0.49334568 0.01129550 0.85311514 + 1 'H ' 918.73579607 + 1 1 0.5519365595 0.2313707631 -0.1692669144 + 2 1 0.4174621950 0.6671291184 -0.1692669144 + 3 1 0.4001695915 1.5430380039 0.1692669144 + 4 1 0.5346439560 1.1072796486 0.1692669144 + 5 1 0.6981106437 0.2360660957 0.0464225528 + 6 1 0.2712881108 0.6624337858 0.0464225528 + 7 1 0.2539955073 1.5383426713 -0.0464225528 + 8 1 0.6808180402 1.1119749812 -0.0464225528 + 9 1 0.6732076478 0.2102400630 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-0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 0.000000 0.000000 0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 0.000000 -0.000000 ) +( -0.027073 0.000000 0.202321 -0.000000 -0.000000 -0.000000 ) + freq ( 2) = 0.01221175 [THz] = 0.40734011 [cm-1] +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( -0.000000 0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( 0.000000 -0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( -0.000000 0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) +( 0.000000 -0.000000 0.000000 -0.000000 0.204124 -0.000000 ) +( -0.000000 0.000000 -0.000000 0.000000 0.204124 0.000000 ) + freq ( 3) = 0.01682493 [THz] = 0.56121930 [cm-1] +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 0.000000 0.000000 ) +( 0.202321 0.000000 0.027073 0.000000 -0.000000 0.000000 ) + freq ( 4) = 12.38868468 [THz] = 413.24203915 [cm-1] +( -0.087790 0.000000 -0.002593 0.000000 -0.217110 0.000000 ) +( -0.087790 0.000000 -0.002593 0.000000 0.217110 0.000000 ) +( -0.087790 0.000000 -0.002593 0.000000 -0.217110 0.000000 ) +( -0.087790 0.000000 -0.002593 0.000000 0.217110 0.000000 ) +( -0.094700 0.000000 -0.001337 0.000000 -0.127957 0.000000 ) +( -0.094700 0.000000 -0.001337 0.000000 0.127957 0.000000 ) +( -0.094700 0.000000 -0.001337 0.000000 -0.127957 0.000000 ) +( -0.094700 0.000000 -0.001337 0.000000 0.127957 0.000000 ) +( -0.075240 0.000000 0.077339 0.000000 0.136450 0.000000 ) +( -0.075240 0.000000 0.077339 0.000000 -0.136450 0.000000 ) +( -0.075240 0.000000 0.077339 0.000000 0.136450 0.000000 ) +( -0.075240 0.000000 0.077339 0.000000 -0.136450 0.000000 ) +( -0.123629 0.000000 0.058284 0.000000 0.189584 0.000000 ) +( -0.123629 0.000000 0.058284 0.000000 -0.189584 0.000000 ) +( -0.123629 0.000000 0.058284 0.000000 0.189584 0.000000 ) +( -0.123629 0.000000 0.058284 0.000000 -0.189584 0.000000 ) +( 0.153083 0.000000 -0.080425 0.000000 -0.013713 0.000000 ) +( 0.153083 0.000000 -0.080425 0.000000 0.013713 0.000000 ) +( 0.153083 0.000000 -0.080425 0.000000 -0.013713 0.000000 ) +( 0.153083 0.000000 -0.080425 0.000000 0.013713 0.000000 ) +( 0.228276 0.000000 -0.051269 0.000000 0.009675 0.000000 ) +( 0.228276 0.000000 -0.051269 0.000000 -0.009675 0.000000 ) +( 0.228276 0.000000 -0.051269 0.000000 0.009675 0.000000 ) +( 0.228276 0.000000 -0.051269 0.000000 -0.009675 0.000000 ) + freq ( 5) = 20.08708572 [THz] = 670.03305674 [cm-1] +( 0.069549 0.000000 0.006533 0.000000 0.157329 0.000000 ) +( -0.069549 0.000000 -0.006533 0.000000 0.157329 0.000000 ) +( 0.069549 0.000000 0.006533 0.000000 0.157329 0.000000 ) +( -0.069549 0.000000 -0.006533 0.000000 0.157329 0.000000 ) +( 0.238094 0.000000 0.149159 0.000000 0.006728 0.000000 ) +( -0.238094 0.000000 -0.149159 0.000000 0.006728 0.000000 ) +( 0.238094 0.000000 0.149159 0.000000 0.006728 0.000000 ) +( -0.238094 0.000000 -0.149159 0.000000 0.006728 0.000000 ) +( -0.046778 0.000000 -0.095302 0.000000 -0.192199 0.000000 ) +( 0.046778 0.000000 0.095302 0.000000 -0.192199 0.000000 ) +( -0.046778 0.000000 -0.095302 0.000000 -0.192199 0.000000 ) +( 0.046778 0.000000 0.095302 0.000000 -0.192199 0.000000 ) +( 0.148593 0.000000 0.006363 0.000000 -0.128839 0.000000 ) +( -0.148593 0.000000 -0.006363 0.000000 -0.128839 0.000000 ) +( 0.148593 0.000000 0.006363 0.000000 -0.128839 0.000000 ) +( -0.148593 0.000000 -0.006363 0.000000 -0.128839 0.000000 ) +( -0.068552 0.000000 -0.066169 0.000000 0.183594 0.000000 ) +( 0.068552 0.000000 0.066169 0.000000 0.183594 0.000000 ) +( -0.068552 0.000000 -0.066169 0.000000 0.183594 0.000000 ) +( 0.068552 0.000000 0.066169 0.000000 0.183594 0.000000 ) +( -0.104532 0.000000 0.005927 0.000000 -0.026613 0.000000 ) +( 0.104532 0.000000 -0.005927 0.000000 -0.026613 0.000000 ) +( -0.104532 0.000000 0.005927 0.000000 -0.026613 0.000000 ) +( 0.104532 0.000000 -0.005927 0.000000 -0.026613 0.000000 ) + freq ( 6) = 20.23261971 [THz] = 674.88754818 [cm-1] +( -0.085203 0.000000 0.011755 -0.000000 -0.159325 -0.000000 ) +( -0.085203 0.000000 0.011755 -0.000000 0.159325 -0.000000 ) +( 0.085203 -0.000000 -0.011755 0.000000 0.159325 0.000000 ) +( 0.085203 -0.000000 -0.011755 0.000000 -0.159325 0.000000 ) +( -0.195639 0.000000 0.152828 -0.000000 -0.052258 -0.000000 ) +( -0.195639 0.000000 0.152828 -0.000000 0.052258 -0.000000 ) +( 0.195639 0.000000 -0.152828 0.000000 0.052258 0.000000 ) +( 0.195639 -0.000000 -0.152828 0.000000 -0.052258 0.000000 ) +( 0.049260 -0.000000 -0.053714 0.000000 0.169558 0.000000 ) +( 0.049260 -0.000000 -0.053714 0.000000 -0.169558 0.000000 ) +( -0.049260 0.000000 0.053714 -0.000000 -0.169558 -0.000000 ) +( -0.049260 0.000000 0.053714 -0.000000 0.169558 -0.000000 ) +( -0.075028 0.000000 -0.031516 0.000000 0.142058 0.000000 ) +( -0.075028 0.000000 -0.031516 0.000000 -0.142058 0.000000 ) +( 0.075028 -0.000000 0.031516 -0.000000 -0.142058 -0.000000 ) +( 0.075028 -0.000000 0.031516 -0.000000 0.142058 -0.000000 ) +( 0.128670 -0.000000 -0.118029 0.000000 -0.164450 0.000000 ) +( 0.128670 -0.000000 -0.118029 0.000000 0.164450 0.000000 ) +( -0.128670 0.000000 0.118029 -0.000000 0.164450 -0.000000 ) +( -0.128670 0.000000 0.118029 -0.000000 -0.164450 -0.000000 ) +( 0.181580 -0.000000 0.025818 -0.000000 0.028690 -0.000000 ) +( 0.181580 -0.000000 0.025818 -0.000000 -0.028690 -0.000000 ) +( -0.181580 0.000000 -0.025818 0.000000 -0.028690 0.000000 ) +( -0.181580 0.000000 -0.025818 0.000000 0.028690 0.000000 ) + freq ( 7) = 23.91196151 [THz] = 797.61717985 [cm-1] +( 0.048801 -0.000000 0.083882 -0.000000 -0.066740 -0.000000 ) +( -0.048801 0.000000 -0.083882 0.000000 -0.066740 0.000000 ) +( -0.048801 0.000000 -0.083882 0.000000 0.066740 0.000000 ) +( 0.048801 -0.000000 0.083882 -0.000000 0.066740 -0.000000 ) +( -0.177079 0.000000 -0.042016 0.000000 0.115594 0.000000 ) +( 0.177079 -0.000000 0.042016 -0.000000 0.115594 -0.000000 ) +( 0.177079 -0.000000 0.042016 -0.000000 -0.115594 -0.000000 ) +( -0.177079 0.000000 -0.042016 0.000000 -0.115594 0.000000 ) +( 0.053894 -0.000000 -0.096000 0.000000 0.239574 0.000000 ) +( -0.053894 0.000000 0.096000 -0.000000 0.239574 -0.000000 ) +( -0.053894 0.000000 0.096000 -0.000000 -0.239574 -0.000000 ) +( 0.053894 -0.000000 -0.096000 0.000000 -0.239574 0.000000 ) +( -0.124711 0.000000 0.028709 -0.000000 0.178765 -0.000000 ) +( 0.124711 -0.000000 -0.028709 0.000000 0.178765 0.000000 ) +( 0.124711 -0.000000 -0.028709 0.000000 -0.178765 0.000000 ) +( -0.124711 0.000000 0.028709 -0.000000 -0.178765 -0.000000 ) +( 0.105308 -0.000000 0.079553 -0.000000 -0.065812 -0.000000 ) +( -0.105308 0.000000 -0.079553 0.000000 -0.065812 0.000000 ) +( -0.105308 0.000000 -0.079553 0.000000 0.065812 0.000000 ) +( 0.105308 -0.000000 0.079553 -0.000000 0.065812 -0.000000 ) +( 0.149296 -0.000000 -0.055861 0.000000 0.156953 0.000000 ) +( -0.149296 0.000000 0.055861 -0.000000 0.156953 -0.000000 ) +( -0.149296 0.000000 0.055861 -0.000000 -0.156953 -0.000000 ) +( 0.149296 -0.000000 -0.055861 0.000000 -0.156953 0.000000 ) + freq ( 8) = 24.02635703 [THz] = 801.43300359 [cm-1] +( 0.077007 0.000000 -0.177382 0.000000 0.163783 0.000000 ) +( 0.077007 0.000000 -0.177382 0.000000 -0.163783 0.000000 ) +( 0.077007 0.000000 -0.177382 0.000000 0.163783 0.000000 ) +( 0.077007 0.000000 -0.177382 0.000000 -0.163783 0.000000 ) +( -0.035531 0.000000 0.062250 0.000000 0.242475 0.000000 ) +( -0.035531 0.000000 0.062250 0.000000 -0.242475 0.000000 ) +( -0.035531 0.000000 0.062250 0.000000 0.242475 0.000000 ) +( -0.035531 0.000000 0.062250 0.000000 -0.242475 0.000000 ) +( -0.007095 0.000000 0.017022 0.000000 0.204900 0.000000 ) +( -0.007095 0.000000 0.017022 0.000000 -0.204900 0.000000 ) +( -0.007095 0.000000 0.017022 0.000000 0.204900 0.000000 ) +( -0.007095 0.000000 0.017022 0.000000 -0.204900 0.000000 ) +( -0.052214 0.000000 0.023781 0.000000 0.188882 0.000000 ) +( -0.052214 0.000000 0.023781 0.000000 -0.188882 0.000000 ) +( -0.052214 0.000000 0.023781 0.000000 0.188882 0.000000 ) +( -0.052214 0.000000 0.023781 0.000000 -0.188882 0.000000 ) +( 0.015605 0.000000 0.055647 0.000000 0.165202 0.000000 ) +( 0.015605 0.000000 0.055647 0.000000 -0.165202 0.000000 ) +( 0.015605 0.000000 0.055647 0.000000 0.165202 0.000000 ) +( 0.015605 0.000000 0.055647 0.000000 -0.165202 0.000000 ) +( 0.002228 0.000000 0.018683 0.000000 0.097831 0.000000 ) +( 0.002228 0.000000 0.018683 0.000000 -0.097831 0.000000 ) +( 0.002228 0.000000 0.018683 0.000000 0.097831 0.000000 ) +( 0.002228 0.000000 0.018683 0.000000 -0.097831 0.000000 ) + freq ( 9) = 24.65452359 [THz] = 822.38638449 [cm-1] +( 0.256288 0.000000 0.040124 0.000000 -0.013082 0.000000 ) +( -0.256288 0.000000 -0.040124 0.000000 -0.013082 0.000000 ) +( 0.256288 0.000000 0.040124 0.000000 -0.013082 0.000000 ) +( -0.256288 0.000000 -0.040124 0.000000 -0.013082 0.000000 ) +( 0.116866 0.000000 0.058288 0.000000 0.065171 0.000000 ) +( -0.116866 0.000000 -0.058288 0.000000 0.065171 0.000000 ) +( 0.116866 0.000000 0.058288 0.000000 0.065171 0.000000 ) +( -0.116866 0.000000 -0.058288 0.000000 0.065171 0.000000 ) +( 0.256842 0.000000 0.092279 0.000000 0.045340 0.000000 ) +( -0.256842 0.000000 -0.092279 0.000000 0.045340 0.000000 ) +( 0.256842 0.000000 0.092279 0.000000 0.045340 0.000000 ) +( -0.256842 0.000000 -0.092279 0.000000 0.045340 0.000000 ) +( 0.110841 0.000000 -0.109045 0.000000 -0.038327 0.000000 ) +( -0.110841 0.000000 0.109045 0.000000 -0.038327 0.000000 ) +( 0.110841 0.000000 -0.109045 0.000000 -0.038327 0.000000 ) +( -0.110841 0.000000 0.109045 0.000000 -0.038327 0.000000 ) +( 0.148806 0.000000 0.012985 0.000000 -0.084222 0.000000 ) +( -0.148806 0.000000 -0.012985 0.000000 -0.084222 0.000000 ) +( 0.148806 0.000000 0.012985 0.000000 -0.084222 0.000000 ) +( -0.148806 0.000000 -0.012985 0.000000 -0.084222 0.000000 ) +( 0.159039 0.000000 -0.060978 0.000000 0.025121 0.000000 ) +( -0.159039 0.000000 0.060978 0.000000 0.025121 0.000000 ) +( 0.159039 0.000000 -0.060978 0.000000 0.025121 0.000000 ) +( -0.159039 0.000000 0.060978 0.000000 0.025121 0.000000 ) + freq ( 10) = 24.70079622 [THz] = 823.92987351 [cm-1] +( -0.092056 0.000000 0.000662 0.000000 -0.263305 0.000000 ) +( 0.092056 0.000000 -0.000662 0.000000 -0.263305 0.000000 ) +( 0.092056 0.000000 -0.000662 0.000000 0.263305 0.000000 ) +( -0.092056 0.000000 0.000662 0.000000 0.263305 0.000000 ) +( -0.070411 0.000000 -0.011013 0.000000 -0.241093 0.000000 ) +( 0.070411 0.000000 0.011013 0.000000 -0.241093 0.000000 ) +( 0.070411 0.000000 0.011013 0.000000 0.241093 0.000000 ) +( -0.070411 0.000000 -0.011013 0.000000 0.241093 0.000000 ) +( -0.044830 0.000000 -0.099313 0.000000 -0.068054 0.000000 ) +( 0.044830 0.000000 0.099313 0.000000 -0.068054 0.000000 ) +( 0.044830 0.000000 0.099313 0.000000 0.068054 0.000000 ) +( -0.044830 0.000000 -0.099313 0.000000 0.068054 0.000000 ) +( -0.101593 0.000000 -0.023869 0.000000 -0.085831 0.000000 ) +( 0.101593 0.000000 0.023869 0.000000 -0.085831 0.000000 ) +( 0.101593 0.000000 0.023869 0.000000 0.085831 0.000000 ) +( -0.101593 0.000000 -0.023869 0.000000 0.085831 0.000000 ) +( 0.070690 0.000000 0.089916 0.000000 -0.185497 0.000000 ) +( -0.070690 0.000000 -0.089916 0.000000 -0.185497 0.000000 ) +( -0.070690 0.000000 -0.089916 0.000000 0.185497 0.000000 ) +( 0.070690 0.000000 0.089916 0.000000 0.185497 0.000000 ) +( 0.077263 0.000000 0.043506 0.000000 -0.137387 0.000000 ) +( -0.077263 0.000000 -0.043506 0.000000 -0.137387 0.000000 ) +( -0.077263 0.000000 -0.043506 0.000000 0.137387 0.000000 ) +( 0.077263 0.000000 0.043506 0.000000 0.137387 0.000000 ) + freq ( 11) = 24.97298901 [THz] = 833.00924777 [cm-1] +( -0.148063 0.000000 0.025103 -0.000000 0.067863 -0.000000 ) +( -0.148063 0.000000 0.025103 -0.000000 -0.067863 -0.000000 ) +( 0.148063 -0.000000 -0.025103 0.000000 -0.067863 0.000000 ) +( 0.148063 -0.000000 -0.025103 0.000000 0.067863 0.000000 ) +( -0.214383 0.000000 -0.015780 0.000000 0.092578 0.000000 ) +( -0.214383 0.000000 -0.015780 0.000000 -0.092578 0.000000 ) +( 0.214383 -0.000000 0.015780 -0.000000 -0.092578 -0.000000 ) +( 0.214383 -0.000000 0.015780 -0.000000 0.092578 -0.000000 ) +( -0.123633 0.000000 -0.016398 0.000000 0.063770 0.000000 ) +( -0.123633 0.000000 -0.016398 0.000000 -0.063770 0.000000 ) +( 0.123633 -0.000000 0.016398 -0.000000 -0.063770 -0.000000 ) +( 0.123633 -0.000000 0.016398 -0.000000 0.063770 -0.000000 ) +( -0.200549 0.000000 -0.012241 0.000000 0.015220 0.000000 ) +( -0.200549 0.000000 -0.012241 0.000000 -0.015220 0.000000 ) +( 0.200549 -0.000000 0.012241 -0.000000 -0.015220 -0.000000 ) +( 0.200549 -0.000000 0.012241 -0.000000 0.015220 -0.000000 ) +( -0.208596 0.000000 -0.090309 0.000000 0.034988 0.000000 ) +( -0.208596 0.000000 -0.090309 0.000000 -0.034988 0.000000 ) +( 0.208596 -0.000000 0.090309 -0.000000 -0.034988 -0.000000 ) +( 0.208596 -0.000000 0.090309 -0.000000 0.034988 -0.000000 ) +( -0.223621 0.000000 0.061991 -0.000000 0.033146 -0.000000 ) +( -0.223621 0.000000 0.061991 -0.000000 -0.033146 -0.000000 ) +( 0.223621 -0.000000 -0.061991 0.000000 -0.033146 0.000000 ) +( 0.223621 0.000000 -0.061991 0.000000 0.033146 0.000000 ) + freq ( 12) = 25.87570451 [THz] = 863.12059541 [cm-1] +( -0.082011 0.000000 0.116489 0.000000 0.104405 0.000000 ) +( -0.082011 0.000000 0.116489 0.000000 -0.104405 0.000000 ) +( -0.082011 0.000000 0.116489 0.000000 0.104405 0.000000 ) +( -0.082011 0.000000 0.116489 0.000000 -0.104405 0.000000 ) +( 0.174588 0.000000 -0.059939 0.000000 -0.078839 0.000000 ) +( 0.174588 0.000000 -0.059939 0.000000 0.078839 0.000000 ) +( 0.174588 0.000000 -0.059939 0.000000 -0.078839 0.000000 ) +( 0.174588 0.000000 -0.059939 0.000000 0.078839 0.000000 ) +( -0.164480 0.000000 0.145595 0.000000 -0.045405 0.000000 ) +( -0.164480 0.000000 0.145595 0.000000 0.045405 0.000000 ) +( -0.164480 0.000000 0.145595 0.000000 -0.045405 0.000000 ) +( -0.164480 0.000000 0.145595 0.000000 0.045405 0.000000 ) +( 0.066822 0.000000 -0.123979 0.000000 0.095121 0.000000 ) +( 0.066822 0.000000 -0.123979 0.000000 -0.095121 0.000000 ) +( 0.066822 0.000000 -0.123979 0.000000 0.095121 0.000000 ) +( 0.066822 0.000000 -0.123979 0.000000 -0.095121 0.000000 ) +( 0.011421 0.000000 -0.091838 0.000000 0.285224 0.000000 ) +( 0.011421 0.000000 -0.091838 0.000000 -0.285224 0.000000 ) +( 0.011421 0.000000 -0.091838 0.000000 0.285224 0.000000 ) +( 0.011421 0.000000 -0.091838 0.000000 -0.285224 0.000000 ) +( -0.006339 0.000000 0.013672 0.000000 -0.095778 0.000000 ) +( -0.006339 0.000000 0.013672 0.000000 0.095778 0.000000 ) +( -0.006339 0.000000 0.013672 0.000000 -0.095778 0.000000 ) +( -0.006339 0.000000 0.013672 0.000000 0.095778 0.000000 ) + freq ( 13) = 26.61073244 [THz] = 887.63848804 [cm-1] +( 0.137458 0.000000 -0.260490 0.000000 0.076959 0.000000 ) +( 0.137458 0.000000 -0.260490 0.000000 -0.076959 0.000000 ) +( -0.137458 0.000000 0.260490 0.000000 -0.076959 0.000000 ) +( -0.137458 0.000000 0.260490 0.000000 0.076959 0.000000 ) +( 0.057295 0.000000 0.045581 0.000000 0.120417 0.000000 ) +( 0.057295 0.000000 0.045581 0.000000 -0.120417 0.000000 ) +( -0.057295 0.000000 -0.045581 0.000000 -0.120417 0.000000 ) +( -0.057295 0.000000 -0.045581 0.000000 0.120417 0.000000 ) +( 0.069987 0.000000 0.029590 0.000000 0.078727 0.000000 ) +( 0.069987 0.000000 0.029590 0.000000 -0.078727 0.000000 ) +( -0.069987 0.000000 -0.029590 0.000000 -0.078727 0.000000 ) +( -0.069987 0.000000 -0.029590 0.000000 0.078727 0.000000 ) +( -0.021983 0.000000 0.073813 0.000000 0.020549 0.000000 ) +( -0.021983 0.000000 0.073813 0.000000 -0.020549 0.000000 ) +( 0.021983 0.000000 -0.073813 0.000000 -0.020549 0.000000 ) +( 0.021983 0.000000 -0.073813 0.000000 0.020549 0.000000 ) +( 0.022302 0.000000 -0.171912 0.000000 0.107253 0.000000 ) +( 0.022302 0.000000 -0.171912 0.000000 -0.107253 0.000000 ) +( -0.022302 0.000000 0.171912 0.000000 -0.107253 0.000000 ) +( -0.022302 0.000000 0.171912 0.000000 0.107253 0.000000 ) +( 0.038121 0.000000 0.275200 0.000000 0.019967 0.000000 ) +( 0.038121 0.000000 0.275200 0.000000 -0.019967 0.000000 ) +( -0.038121 0.000000 -0.275200 0.000000 -0.019967 0.000000 ) +( -0.038121 0.000000 -0.275200 0.000000 0.019967 0.000000 ) + freq ( 14) = 26.90050133 [THz] = 897.30413773 [cm-1] +( 0.186370 0.000000 -0.003971 0.000000 -0.028970 0.000000 ) +( -0.186370 0.000000 0.003971 0.000000 -0.028970 0.000000 ) +( -0.186370 0.000000 0.003971 0.000000 0.028970 0.000000 ) +( 0.186370 0.000000 -0.003971 0.000000 0.028970 0.000000 ) +( 0.126508 0.000000 0.111056 0.000000 0.007590 0.000000 ) +( -0.126508 0.000000 -0.111056 0.000000 0.007590 0.000000 ) +( -0.126508 0.000000 -0.111056 0.000000 -0.007590 0.000000 ) +( 0.126508 0.000000 0.111056 0.000000 -0.007590 0.000000 ) +( 0.155892 0.000000 0.093962 0.000000 -0.039800 0.000000 ) +( -0.155892 0.000000 -0.093962 0.000000 -0.039800 0.000000 ) +( -0.155892 0.000000 -0.093962 0.000000 0.039800 0.000000 ) +( 0.155892 0.000000 0.093962 0.000000 0.039800 0.000000 ) +( 0.176071 0.000000 -0.112712 0.000000 -0.055777 0.000000 ) +( -0.176071 0.000000 0.112712 0.000000 -0.055777 0.000000 ) +( -0.176071 0.000000 0.112712 0.000000 0.055777 0.000000 ) +( 0.176071 0.000000 -0.112712 0.000000 0.055777 0.000000 ) +( 0.171451 0.000000 0.088301 0.000000 -0.067345 0.000000 ) +( -0.171451 0.000000 -0.088301 0.000000 -0.067345 0.000000 ) +( -0.171451 0.000000 -0.088301 0.000000 0.067345 0.000000 ) +( 0.171451 0.000000 0.088301 0.000000 0.067345 0.000000 ) +( 0.189974 0.000000 -0.158862 0.000000 -0.037811 0.000000 ) +( -0.189974 0.000000 0.158862 0.000000 -0.037811 0.000000 ) +( -0.189974 0.000000 0.158862 0.000000 0.037811 0.000000 ) +( 0.189974 0.000000 -0.158862 0.000000 0.037811 0.000000 ) + freq ( 15) = 27.65868626 [THz] = 922.59446473 [cm-1] +( 0.090969 -0.000000 0.008058 -0.000000 0.011951 -0.000000 ) +( -0.090969 0.000000 -0.008058 0.000000 0.011951 0.000000 ) +( 0.090969 -0.000000 0.008058 -0.000000 0.011951 -0.000000 ) +( -0.090969 0.000000 -0.008058 0.000000 0.011951 0.000000 ) +( -0.127073 0.000000 0.182721 -0.000000 0.147944 -0.000000 ) +( 0.127073 -0.000000 -0.182721 0.000000 0.147944 0.000000 ) +( -0.127073 0.000000 0.182721 -0.000000 0.147944 -0.000000 ) +( 0.127073 -0.000000 -0.182721 0.000000 0.147944 0.000000 ) +( 0.067160 -0.000000 0.033199 -0.000000 0.022554 -0.000000 ) +( -0.067160 0.000000 -0.033199 0.000000 0.022554 0.000000 ) +( 0.067160 -0.000000 0.033199 -0.000000 0.022554 -0.000000 ) +( -0.067160 0.000000 -0.033199 0.000000 0.022554 0.000000 ) +( -0.232089 0.000000 -0.099408 0.000000 -0.150889 0.000000 ) +( 0.232089 -0.000000 0.099408 -0.000000 -0.150889 -0.000000 ) +( -0.232089 0.000000 -0.099408 0.000000 -0.150889 0.000000 ) +( 0.232089 0.000000 0.099408 -0.000000 -0.150889 -0.000000 ) +( -0.155651 0.000000 -0.123702 0.000000 -0.080228 0.000000 ) +( 0.155651 -0.000000 0.123702 -0.000000 -0.080228 -0.000000 ) +( -0.155651 0.000000 -0.123702 0.000000 -0.080228 0.000000 ) +( 0.155651 -0.000000 0.123702 -0.000000 -0.080228 -0.000000 ) +( -0.166893 0.000000 -0.035659 0.000000 0.048668 0.000000 ) +( 0.166893 -0.000000 0.035659 -0.000000 0.048668 -0.000000 ) +( -0.166893 0.000000 -0.035659 0.000000 0.048668 0.000000 ) +( 0.166893 -0.000000 0.035659 -0.000000 0.048668 -0.000000 ) + freq ( 16) = 27.78874293 [THz] = 926.93268834 [cm-1] +( 0.072494 -0.000000 0.002190 -0.000000 -0.160344 -0.000000 ) +( 0.072494 -0.000000 0.002190 -0.000000 0.160344 -0.000000 ) +( -0.072494 0.000000 -0.002190 0.000000 0.160344 0.000000 ) +( -0.072494 0.000000 -0.002190 0.000000 -0.160344 0.000000 ) +( -0.067870 0.000000 -0.037763 0.000000 -0.032910 0.000000 ) +( -0.067870 0.000000 -0.037763 0.000000 0.032910 0.000000 ) +( 0.067870 -0.000000 0.037763 -0.000000 0.032910 -0.000000 ) +( 0.067870 -0.000000 0.037763 -0.000000 -0.032910 -0.000000 ) +( 0.120674 -0.000000 0.067088 -0.000000 -0.092799 -0.000000 ) +( 0.120674 -0.000000 0.067088 -0.000000 0.092799 -0.000000 ) +( -0.120674 0.000000 -0.067088 0.000000 0.092799 0.000000 ) +( -0.120674 0.000000 -0.067088 0.000000 -0.092799 0.000000 ) +( -0.131512 0.000000 -0.064572 0.000000 -0.269782 0.000000 ) +( -0.131512 0.000000 -0.064572 0.000000 0.269782 0.000000 ) +( 0.131512 -0.000000 0.064572 -0.000000 0.269782 -0.000000 ) +( 0.131512 -0.000000 0.064572 -0.000000 -0.269782 -0.000000 ) +( -0.011014 0.000000 -0.054346 0.000000 -0.105564 0.000000 ) +( -0.011014 0.000000 -0.054346 0.000000 0.105564 0.000000 ) +( 0.011014 -0.000000 0.054346 -0.000000 0.105564 -0.000000 ) +( 0.011014 -0.000000 0.054346 -0.000000 -0.105564 -0.000000 ) +( -0.034028 0.000000 0.092537 -0.000000 -0.257007 -0.000000 ) +( -0.034028 0.000000 0.092537 -0.000000 0.257007 -0.000000 ) +( 0.034028 -0.000000 -0.092537 0.000000 0.257007 0.000000 ) +( 0.034028 -0.000000 -0.092537 0.000000 -0.257007 0.000000 ) + freq ( 17) = 28.33881819 [THz] = 945.28122391 [cm-1] +( -0.125703 0.000000 0.142060 0.000000 0.085983 0.000000 ) +( 0.125703 0.000000 -0.142060 0.000000 0.085983 0.000000 ) +( 0.125703 0.000000 -0.142060 0.000000 -0.085983 0.000000 ) +( -0.125703 0.000000 0.142060 0.000000 -0.085983 0.000000 ) +( 0.192634 0.000000 -0.114489 0.000000 -0.108192 0.000000 ) +( -0.192634 0.000000 0.114489 0.000000 -0.108192 0.000000 ) +( -0.192634 0.000000 0.114489 0.000000 0.108192 0.000000 ) +( 0.192634 0.000000 -0.114489 0.000000 0.108192 0.000000 ) +( -0.132883 0.000000 -0.150839 0.000000 -0.020251 0.000000 ) +( 0.132883 0.000000 0.150839 0.000000 -0.020251 0.000000 ) +( 0.132883 0.000000 0.150839 0.000000 0.020251 0.000000 ) +( -0.132883 0.000000 -0.150839 0.000000 0.020251 0.000000 ) +( 0.092304 0.000000 0.069151 0.000000 0.119827 0.000000 ) +( -0.092304 0.000000 -0.069151 0.000000 0.119827 0.000000 ) +( -0.092304 0.000000 -0.069151 0.000000 -0.119827 0.000000 ) +( 0.092304 0.000000 0.069151 0.000000 -0.119827 0.000000 ) +( 0.145784 0.000000 0.090758 0.000000 0.177564 0.000000 ) +( -0.145784 0.000000 -0.090758 0.000000 0.177564 0.000000 ) +( -0.145784 0.000000 -0.090758 0.000000 -0.177564 0.000000 ) +( 0.145784 0.000000 0.090758 0.000000 -0.177564 0.000000 ) +( 0.120228 0.000000 -0.021590 0.000000 -0.016822 0.000000 ) +( -0.120228 0.000000 0.021590 0.000000 -0.016822 0.000000 ) +( -0.120228 0.000000 0.021590 0.000000 0.016822 0.000000 ) +( 0.120228 0.000000 -0.021590 0.000000 0.016822 0.000000 ) + freq ( 18) = 28.37984082 [THz] = 946.64959170 [cm-1] +( 0.032543 -0.000000 0.242878 0.000000 -0.028485 0.000000 ) +( 0.032543 -0.000000 0.242878 -0.000000 0.028485 -0.000000 ) +( 0.032543 -0.000000 0.242878 -0.000000 -0.028485 -0.000000 ) +( 0.032543 -0.000000 0.242878 -0.000000 0.028485 -0.000000 ) +( -0.059210 0.000000 -0.164048 0.000000 0.033577 0.000000 ) +( -0.059210 0.000000 -0.164048 0.000000 -0.033577 0.000000 ) +( -0.059210 0.000000 -0.164048 0.000000 0.033577 0.000000 ) +( -0.059210 0.000000 -0.164048 0.000000 -0.033577 0.000000 ) +( 0.131609 -0.000000 0.103862 -0.000000 0.112944 -0.000000 ) +( 0.131609 -0.000000 0.103862 -0.000000 -0.112944 -0.000000 ) +( 0.131609 -0.000000 0.103862 -0.000000 0.112944 -0.000000 ) +( 0.131609 -0.000000 0.103862 -0.000000 -0.112944 -0.000000 ) +( -0.000971 0.000000 -0.139618 0.000000 0.064007 0.000000 ) +( -0.000971 0.000000 -0.139618 0.000000 -0.064007 0.000000 ) +( -0.000971 0.000000 -0.139618 0.000000 0.064007 0.000000 ) +( -0.000971 0.000000 -0.139618 0.000000 -0.064007 0.000000 ) +( -0.049394 0.000000 0.175679 -0.000000 -0.009799 -0.000000 ) +( -0.049394 0.000000 0.175679 -0.000000 0.009799 -0.000000 ) +( -0.049394 0.000000 0.175679 -0.000000 -0.009799 -0.000000 ) +( -0.049394 0.000000 0.175679 -0.000000 0.009799 -0.000000 ) +( -0.054578 0.000000 -0.218754 0.000000 0.094385 0.000000 ) +( -0.054578 0.000000 -0.218754 0.000000 -0.094385 0.000000 ) +( -0.054578 0.000000 -0.218754 0.000000 0.094385 0.000000 ) +( -0.054578 0.000000 -0.218754 0.000000 -0.094385 0.000000 ) + freq ( 19) = 29.27752538 [THz] = 976.59312547 [cm-1] +( 0.174717 -0.000000 0.086294 -0.000000 -0.114646 -0.000000 ) +( 0.174717 -0.000000 0.086294 -0.000000 0.114646 -0.000000 ) +( -0.174717 0.000000 -0.086294 0.000000 0.114646 0.000000 ) +( -0.174717 0.000000 -0.086294 0.000000 -0.114646 0.000000 ) +( -0.055962 0.000000 -0.288358 0.000000 0.110805 0.000000 ) +( -0.055962 0.000000 -0.288358 0.000000 -0.110805 0.000000 ) +( 0.055962 -0.000000 0.288358 0.000000 -0.110805 0.000000 ) +( 0.055962 -0.000000 0.288358 -0.000000 0.110805 -0.000000 ) +( -0.008244 0.000000 0.035435 -0.000000 0.144499 -0.000000 ) +( -0.008244 0.000000 0.035435 -0.000000 -0.144499 -0.000000 ) +( 0.008244 -0.000000 -0.035435 0.000000 -0.144499 0.000000 ) +( 0.008244 -0.000000 -0.035435 0.000000 0.144499 0.000000 ) +( -0.151207 0.000000 0.155316 -0.000000 0.078754 -0.000000 ) +( -0.151207 0.000000 0.155316 -0.000000 -0.078754 -0.000000 ) +( 0.151207 -0.000000 -0.155316 0.000000 -0.078754 0.000000 ) +( 0.151207 -0.000000 -0.155316 0.000000 0.078754 0.000000 ) +( 0.034091 -0.000000 0.086953 -0.000000 0.078313 -0.000000 ) +( 0.034091 -0.000000 0.086953 -0.000000 -0.078313 -0.000000 ) +( -0.034091 0.000000 -0.086953 0.000000 -0.078313 0.000000 ) +( -0.034091 0.000000 -0.086953 0.000000 0.078313 0.000000 ) +( 0.083370 -0.000000 -0.055092 0.000000 -0.009499 0.000000 ) +( 0.083370 -0.000000 -0.055092 0.000000 0.009499 0.000000 ) +( -0.083370 0.000000 0.055092 -0.000000 0.009499 -0.000000 ) +( -0.083370 0.000000 0.055092 -0.000000 -0.009499 -0.000000 ) + freq ( 20) = 29.87419039 [THz] = 996.49572786 [cm-1] +( -0.046078 0.000000 -0.249944 0.000000 -0.014193 0.000000 ) +( 0.046078 -0.000000 0.249944 -0.000000 -0.014193 -0.000000 ) +( -0.046078 0.000000 -0.249944 0.000000 -0.014193 0.000000 ) +( 0.046078 -0.000000 0.249944 0.000000 -0.014193 0.000000 ) +( 0.004708 -0.000000 0.185998 -0.000000 -0.029234 -0.000000 ) +( -0.004708 0.000000 -0.185998 0.000000 -0.029234 0.000000 ) +( 0.004708 -0.000000 0.185998 -0.000000 -0.029234 -0.000000 ) +( -0.004708 0.000000 -0.185998 0.000000 -0.029234 0.000000 ) +( -0.017702 0.000000 0.141441 -0.000000 0.018428 -0.000000 ) +( 0.017702 -0.000000 -0.141441 0.000000 0.018428 0.000000 ) +( -0.017702 0.000000 0.141441 -0.000000 0.018428 -0.000000 ) +( 0.017702 -0.000000 -0.141441 0.000000 0.018428 0.000000 ) +( -0.126316 0.000000 0.080320 -0.000000 0.003852 -0.000000 ) +( 0.126316 -0.000000 -0.080320 0.000000 0.003852 0.000000 ) +( -0.126316 0.000000 0.080320 -0.000000 0.003852 -0.000000 ) +( 0.126316 -0.000000 -0.080320 0.000000 0.003852 0.000000 ) +( 0.105158 -0.000000 0.030074 -0.000000 0.160202 -0.000000 ) +( -0.105158 0.000000 -0.030074 0.000000 0.160202 0.000000 ) +( 0.105158 -0.000000 0.030074 -0.000000 0.160202 -0.000000 ) +( -0.105158 0.000000 -0.030074 0.000000 0.160202 0.000000 ) +( 0.089472 -0.000000 -0.204162 0.000000 -0.139055 0.000000 ) +( -0.089472 0.000000 0.204162 -0.000000 -0.139055 -0.000000 ) +( 0.089472 -0.000000 -0.204162 0.000000 -0.139055 0.000000 ) +( -0.089472 0.000000 0.204162 -0.000000 -0.139055 -0.000000 ) + freq ( 21) = 30.01669265 [THz] = 1001.24909151 [cm-1] +( -0.100999 0.000000 -0.027450 0.000000 0.070158 0.000000 ) +( -0.100999 0.000000 -0.027450 0.000000 -0.070158 0.000000 ) +( -0.100999 0.000000 -0.027450 0.000000 0.070158 0.000000 ) +( -0.100999 0.000000 -0.027450 0.000000 -0.070158 0.000000 ) +( 0.102687 0.000000 -0.007830 0.000000 -0.107811 0.000000 ) +( 0.102687 0.000000 -0.007830 0.000000 0.107811 0.000000 ) +( 0.102687 0.000000 -0.007830 0.000000 -0.107811 0.000000 ) +( 0.102687 0.000000 -0.007830 0.000000 0.107811 0.000000 ) +( -0.065478 0.000000 -0.086838 0.000000 -0.038793 0.000000 ) +( -0.065478 0.000000 -0.086838 0.000000 0.038793 0.000000 ) +( -0.065478 0.000000 -0.086838 0.000000 -0.038793 0.000000 ) +( -0.065478 0.000000 -0.086838 0.000000 0.038793 0.000000 ) +( 0.119293 0.000000 0.300104 0.000000 0.045642 0.000000 ) +( 0.119293 0.000000 0.300104 0.000000 -0.045642 0.000000 ) +( 0.119293 0.000000 0.300104 0.000000 0.045642 0.000000 ) +( 0.119293 0.000000 0.300104 0.000000 -0.045642 0.000000 ) +( -0.028329 0.000000 0.061344 0.000000 0.037965 0.000000 ) +( -0.028329 0.000000 0.061344 0.000000 -0.037965 0.000000 ) +( -0.028329 0.000000 0.061344 0.000000 0.037965 0.000000 ) +( -0.028329 0.000000 0.061344 0.000000 -0.037965 0.000000 ) +( -0.027173 0.000000 -0.239330 0.000000 0.167812 0.000000 ) +( -0.027173 0.000000 -0.239330 0.000000 -0.167812 0.000000 ) +( -0.027173 0.000000 -0.239330 0.000000 0.167812 0.000000 ) +( -0.027173 0.000000 -0.239330 0.000000 -0.167812 0.000000 ) + freq ( 22) = 30.47933629 [THz] = 1016.68122233 [cm-1] +( 0.225873 0.000000 0.098585 0.000000 -0.133320 0.000000 ) +( -0.225873 0.000000 -0.098585 0.000000 -0.133320 0.000000 ) +( -0.225873 0.000000 -0.098585 0.000000 0.133320 0.000000 ) +( 0.225873 0.000000 0.098585 0.000000 0.133320 0.000000 ) +( -0.026514 0.000000 -0.164999 0.000000 0.024233 0.000000 ) +( 0.026514 0.000000 0.164999 0.000000 0.024233 0.000000 ) +( 0.026514 0.000000 0.164999 0.000000 -0.024233 0.000000 ) +( -0.026514 0.000000 -0.164999 0.000000 -0.024233 0.000000 ) +( -0.019275 0.000000 -0.062503 0.000000 -0.055855 0.000000 ) +( 0.019275 0.000000 0.062503 0.000000 -0.055855 0.000000 ) +( 0.019275 0.000000 0.062503 0.000000 0.055855 0.000000 ) +( -0.019275 0.000000 -0.062503 0.000000 0.055855 0.000000 ) +( 0.225831 0.000000 0.148145 0.000000 0.057054 0.000000 ) +( -0.225831 0.000000 -0.148145 0.000000 0.057054 0.000000 ) +( -0.225831 0.000000 -0.148145 0.000000 -0.057054 0.000000 ) +( 0.225831 0.000000 0.148145 0.000000 -0.057054 0.000000 ) +( -0.036398 0.000000 -0.159535 0.000000 -0.083106 0.000000 ) +( 0.036398 0.000000 0.159535 0.000000 -0.083106 0.000000 ) +( 0.036398 0.000000 0.159535 0.000000 0.083106 0.000000 ) +( -0.036398 0.000000 -0.159535 0.000000 0.083106 0.000000 ) +( 0.011489 0.000000 0.159225 0.000000 -0.014356 0.000000 ) +( -0.011489 0.000000 -0.159225 0.000000 -0.014356 0.000000 ) +( -0.011489 0.000000 -0.159225 0.000000 0.014356 0.000000 ) +( 0.011489 0.000000 0.159225 0.000000 0.014356 0.000000 ) + freq ( 23) = 30.68540234 [THz] = 1023.55484576 [cm-1] +( 0.078285 -0.000000 -0.072741 0.000000 0.004506 0.000000 ) +( 0.078285 -0.000000 -0.072741 0.000000 -0.004506 0.000000 ) +( -0.078285 0.000000 0.072741 -0.000000 -0.004506 -0.000000 ) +( -0.078285 0.000000 0.072741 -0.000000 0.004506 -0.000000 ) +( -0.093060 0.000000 0.121624 -0.000000 0.143169 -0.000000 ) +( -0.093060 0.000000 0.121624 -0.000000 -0.143169 -0.000000 ) +( 0.093060 -0.000000 -0.121624 0.000000 -0.143169 0.000000 ) +( 0.093060 -0.000000 -0.121624 0.000000 0.143169 0.000000 ) +( 0.060294 -0.000000 0.002171 -0.000000 0.087462 -0.000000 ) +( 0.060294 -0.000000 0.002171 -0.000000 -0.087462 -0.000000 ) +( -0.060294 0.000000 -0.002171 0.000000 -0.087462 0.000000 ) +( -0.060294 0.000000 -0.002171 0.000000 0.087462 0.000000 ) +( -0.019977 0.000000 -0.293065 0.000000 0.037408 0.000000 ) +( -0.019977 0.000000 -0.293065 0.000000 -0.037408 0.000000 ) +( 0.019977 -0.000000 0.293065 -0.000000 -0.037408 -0.000000 ) +( 0.019977 -0.000000 0.293065 0.000000 0.037408 0.000000 ) +( 0.018950 -0.000000 0.274826 -0.000000 0.124309 -0.000000 ) +( 0.018950 -0.000000 0.274826 -0.000000 -0.124309 -0.000000 ) +( -0.018950 0.000000 -0.274826 0.000000 -0.124309 0.000000 ) +( -0.018950 0.000000 -0.274826 0.000000 0.124309 0.000000 ) +( -0.012431 0.000000 -0.010985 0.000000 -0.063390 0.000000 ) +( -0.012431 0.000000 -0.010985 0.000000 0.063390 0.000000 ) +( 0.012431 -0.000000 0.010985 -0.000000 0.063390 -0.000000 ) +( 0.012431 -0.000000 0.010985 -0.000000 -0.063390 -0.000000 ) + freq ( 24) = 31.71296893 [THz] = 1057.83077769 [cm-1] +( -0.049501 0.000000 -0.162920 0.000000 -0.192296 0.000000 ) +( -0.049501 0.000000 -0.162920 0.000000 0.192296 0.000000 ) +( 0.049501 0.000000 0.162920 0.000000 0.192296 0.000000 ) +( 0.049501 0.000000 0.162920 0.000000 -0.192296 0.000000 ) +( -0.030017 0.000000 -0.127089 0.000000 -0.159414 0.000000 ) +( -0.030017 0.000000 -0.127089 0.000000 0.159414 0.000000 ) +( 0.030017 0.000000 0.127089 0.000000 0.159414 0.000000 ) +( 0.030017 0.000000 0.127089 0.000000 -0.159414 0.000000 ) +( -0.213091 0.000000 0.149144 0.000000 -0.120814 0.000000 ) +( -0.213091 0.000000 0.149144 0.000000 0.120814 0.000000 ) +( 0.213091 0.000000 -0.149144 0.000000 0.120814 0.000000 ) +( 0.213091 0.000000 -0.149144 0.000000 -0.120814 0.000000 ) +( 0.017546 0.000000 -0.104524 0.000000 0.083809 0.000000 ) +( 0.017546 0.000000 -0.104524 0.000000 -0.083809 0.000000 ) +( -0.017546 0.000000 0.104524 0.000000 -0.083809 0.000000 ) +( -0.017546 0.000000 0.104524 0.000000 0.083809 0.000000 ) +( -0.025725 0.000000 0.085783 0.000000 0.021468 0.000000 ) +( -0.025725 0.000000 0.085783 0.000000 -0.021468 0.000000 ) +( 0.025725 0.000000 -0.085783 0.000000 -0.021468 0.000000 ) +( 0.025725 0.000000 -0.085783 0.000000 0.021468 0.000000 ) +( 0.043732 0.000000 0.152200 0.000000 0.086599 0.000000 ) +( 0.043732 0.000000 0.152200 0.000000 -0.086599 0.000000 ) +( -0.043732 0.000000 -0.152200 0.000000 -0.086599 0.000000 ) +( -0.043732 0.000000 -0.152200 0.000000 0.086599 0.000000 ) + freq ( 25) = 31.90321296 [THz] = 1064.17663569 [cm-1] +( -0.040525 0.000000 0.243489 0.000000 0.109319 0.000000 ) +( 0.040525 0.000000 -0.243489 0.000000 0.109319 0.000000 ) +( 0.040525 0.000000 -0.243489 0.000000 -0.109319 0.000000 ) +( -0.040525 0.000000 0.243489 0.000000 -0.109319 0.000000 ) +( 0.056481 0.000000 -0.184242 0.000000 0.078516 0.000000 ) +( -0.056481 0.000000 0.184242 0.000000 0.078516 0.000000 ) +( -0.056481 0.000000 0.184242 0.000000 -0.078516 0.000000 ) +( 0.056481 0.000000 -0.184242 0.000000 -0.078516 0.000000 ) +( 0.159259 0.000000 0.014772 0.000000 -0.033521 0.000000 ) +( -0.159259 0.000000 -0.014772 0.000000 -0.033521 0.000000 ) +( -0.159259 0.000000 -0.014772 0.000000 0.033521 0.000000 ) +( 0.159259 0.000000 0.014772 0.000000 0.033521 0.000000 ) +( -0.152304 0.000000 0.099519 0.000000 -0.202905 0.000000 ) +( 0.152304 0.000000 -0.099519 0.000000 -0.202905 0.000000 ) +( 0.152304 0.000000 -0.099519 0.000000 0.202905 0.000000 ) +( -0.152304 0.000000 0.099519 0.000000 0.202905 0.000000 ) +( 0.033988 0.000000 -0.061363 0.000000 -0.108337 0.000000 ) +( -0.033988 0.000000 0.061363 0.000000 -0.108337 0.000000 ) +( -0.033988 0.000000 0.061363 0.000000 0.108337 0.000000 ) +( 0.033988 0.000000 -0.061363 0.000000 0.108337 0.000000 ) +( -0.016318 0.000000 -0.101589 0.000000 -0.074834 0.000000 ) +( 0.016318 0.000000 0.101589 0.000000 -0.074834 0.000000 ) +( 0.016318 0.000000 0.101589 0.000000 0.074834 0.000000 ) +( -0.016318 0.000000 -0.101589 0.000000 0.074834 0.000000 ) + freq ( 26) = 31.91974274 [THz] = 1064.72800952 [cm-1] +( 0.210894 -0.000000 -0.154871 0.000000 -0.181160 0.000000 ) +( 0.210894 -0.000000 -0.154871 0.000000 0.181160 0.000000 ) +( 0.210894 -0.000000 -0.154871 0.000000 -0.181160 0.000000 ) +( 0.210894 0.000000 -0.154871 0.000000 0.181160 0.000000 ) +( -0.068184 0.000000 -0.077033 0.000000 -0.007681 0.000000 ) +( -0.068184 0.000000 -0.077033 0.000000 0.007681 0.000000 ) +( -0.068184 0.000000 -0.077033 0.000000 -0.007681 0.000000 ) +( -0.068184 0.000000 -0.077033 0.000000 0.007681 0.000000 ) +( -0.181408 0.000000 0.138628 -0.000000 -0.088044 -0.000000 ) +( -0.181408 0.000000 0.138628 -0.000000 0.088044 -0.000000 ) +( -0.181408 0.000000 0.138628 -0.000000 -0.088044 -0.000000 ) +( -0.181408 0.000000 0.138628 -0.000000 0.088044 -0.000000 ) +( 0.201971 -0.000000 -0.000078 0.000000 0.113201 0.000000 ) +( 0.201971 -0.000000 -0.000078 0.000000 -0.113201 0.000000 ) +( 0.201971 -0.000000 -0.000078 0.000000 0.113201 0.000000 ) +( 0.201971 -0.000000 -0.000078 0.000000 -0.113201 0.000000 ) +( -0.091585 0.000000 0.091702 -0.000000 -0.040173 -0.000000 ) +( -0.091585 0.000000 0.091702 -0.000000 0.040173 -0.000000 ) +( -0.091585 0.000000 0.091702 -0.000000 -0.040173 -0.000000 ) +( -0.091585 0.000000 0.091702 -0.000000 0.040173 -0.000000 ) +( -0.071687 0.000000 0.001653 -0.000000 -0.032242 -0.000000 ) +( -0.071687 0.000000 0.001653 -0.000000 0.032242 -0.000000 ) +( -0.071687 0.000000 0.001653 -0.000000 -0.032242 -0.000000 ) +( -0.071687 0.000000 0.001653 -0.000000 0.032242 -0.000000 ) + freq ( 27) = 32.02865539 [THz] = 1068.36094476 [cm-1] +( 0.017165 0.000000 -0.263869 0.000000 -0.073932 0.000000 ) +( 0.017165 0.000000 -0.263869 0.000000 0.073932 0.000000 ) +( -0.017165 0.000000 0.263869 0.000000 0.073932 0.000000 ) +( -0.017165 0.000000 0.263869 0.000000 -0.073932 0.000000 ) +( 0.031999 0.000000 0.129950 0.000000 -0.054326 0.000000 ) +( 0.031999 0.000000 0.129950 0.000000 0.054326 0.000000 ) +( -0.031999 0.000000 -0.129950 0.000000 0.054326 0.000000 ) +( -0.031999 0.000000 -0.129950 0.000000 -0.054326 0.000000 ) +( -0.069667 0.000000 -0.135597 0.000000 0.026859 0.000000 ) +( -0.069667 0.000000 -0.135597 0.000000 -0.026859 0.000000 ) +( 0.069667 0.000000 0.135597 0.000000 -0.026859 0.000000 ) +( 0.069667 0.000000 0.135597 0.000000 0.026859 0.000000 ) +( -0.099720 0.000000 0.228024 0.000000 -0.015139 0.000000 ) +( -0.099720 0.000000 0.228024 0.000000 0.015139 0.000000 ) +( 0.099720 0.000000 -0.228024 0.000000 0.015139 0.000000 ) +( 0.099720 0.000000 -0.228024 0.000000 -0.015139 0.000000 ) +( -0.063113 0.000000 0.177556 0.000000 -0.095227 0.000000 ) +( -0.063113 0.000000 0.177556 0.000000 0.095227 0.000000 ) +( 0.063113 0.000000 -0.177556 0.000000 0.095227 0.000000 ) +( 0.063113 0.000000 -0.177556 0.000000 -0.095227 0.000000 ) +( -0.064597 0.000000 -0.118303 0.000000 -0.069815 0.000000 ) +( -0.064597 0.000000 -0.118303 0.000000 0.069815 0.000000 ) +( 0.064597 0.000000 0.118303 0.000000 0.069815 0.000000 ) +( 0.064597 0.000000 0.118303 0.000000 -0.069815 0.000000 ) + freq ( 28) = 32.18902941 [THz] = 1073.71044623 [cm-1] +( 0.209577 -0.000000 0.058463 -0.000000 -0.199729 -0.000000 ) +( -0.209577 0.000000 -0.058463 0.000000 -0.199729 0.000000 ) +( 0.209577 -0.000000 0.058463 -0.000000 -0.199729 -0.000000 ) +( -0.209577 0.000000 -0.058463 0.000000 -0.199729 0.000000 ) +( -0.084954 0.000000 0.073211 -0.000000 0.004304 -0.000000 ) +( 0.084954 -0.000000 -0.073211 0.000000 0.004304 0.000000 ) +( -0.084954 0.000000 0.073211 -0.000000 0.004304 -0.000000 ) +( 0.084954 -0.000000 -0.073211 0.000000 0.004304 0.000000 ) +( -0.217556 0.000000 0.117475 -0.000000 -0.013020 -0.000000 ) +( 0.217556 0.000000 -0.117475 0.000000 -0.013020 0.000000 ) +( -0.217556 0.000000 0.117475 -0.000000 -0.013020 -0.000000 ) +( 0.217556 -0.000000 -0.117475 0.000000 -0.013020 0.000000 ) +( 0.142048 -0.000000 -0.046252 0.000000 0.191775 0.000000 ) +( -0.142048 0.000000 0.046252 -0.000000 0.191775 -0.000000 ) +( 0.142048 -0.000000 -0.046252 0.000000 0.191775 0.000000 ) +( -0.142048 0.000000 0.046252 -0.000000 0.191775 -0.000000 ) +( -0.081152 0.000000 -0.125648 0.000000 0.059947 0.000000 ) +( 0.081152 -0.000000 0.125648 -0.000000 0.059947 -0.000000 ) +( -0.081152 0.000000 -0.125648 0.000000 0.059947 0.000000 ) +( 0.081152 -0.000000 0.125648 -0.000000 0.059947 -0.000000 ) +( -0.022431 0.000000 -0.037879 0.000000 -0.043277 0.000000 ) +( 0.022431 -0.000000 0.037879 -0.000000 -0.043277 -0.000000 ) +( -0.022431 0.000000 -0.037879 0.000000 -0.043277 0.000000 ) +( 0.022431 -0.000000 0.037879 -0.000000 -0.043277 -0.000000 ) + freq ( 29) = 33.89532160 [THz] = 1130.62622714 [cm-1] +( 0.078147 0.000000 0.068751 0.000000 -0.084340 0.000000 ) +( 0.078147 0.000000 0.068751 0.000000 0.084340 0.000000 ) +( -0.078147 0.000000 -0.068751 0.000000 0.084340 0.000000 ) +( -0.078147 0.000000 -0.068751 0.000000 -0.084340 0.000000 ) +( -0.028372 0.000000 0.092083 0.000000 -0.000978 0.000000 ) +( -0.028372 0.000000 0.092083 0.000000 0.000978 0.000000 ) +( 0.028372 0.000000 -0.092083 0.000000 0.000978 0.000000 ) +( 0.028372 0.000000 -0.092083 0.000000 -0.000978 0.000000 ) +( -0.206443 0.000000 -0.058075 0.000000 -0.011148 0.000000 ) +( -0.206443 0.000000 -0.058075 0.000000 0.011148 0.000000 ) +( 0.206443 0.000000 0.058075 0.000000 0.011148 0.000000 ) +( 0.206443 0.000000 0.058075 0.000000 -0.011148 0.000000 ) +( 0.140732 0.000000 0.027864 0.000000 0.134369 0.000000 ) +( 0.140732 0.000000 0.027864 0.000000 -0.134369 0.000000 ) +( -0.140732 0.000000 -0.027864 0.000000 -0.134369 0.000000 ) +( -0.140732 0.000000 -0.027864 0.000000 0.134369 0.000000 ) +( -0.008431 0.000000 -0.128158 0.000000 0.165821 0.000000 ) +( -0.008431 0.000000 -0.128158 0.000000 -0.165821 0.000000 ) +( 0.008431 0.000000 0.128158 0.000000 -0.165821 0.000000 ) +( 0.008431 0.000000 0.128158 0.000000 0.165821 0.000000 ) +( -0.018714 0.000000 -0.022882 0.000000 -0.305203 0.000000 ) +( -0.018714 0.000000 -0.022882 0.000000 0.305203 0.000000 ) +( 0.018714 0.000000 0.022882 0.000000 0.305203 0.000000 ) +( 0.018714 0.000000 0.022882 0.000000 -0.305203 0.000000 ) + freq ( 30) = 34.13241889 [THz] = 1138.53494123 [cm-1] +( 0.078894 0.000000 0.004119 0.000000 -0.146054 0.000000 ) +( -0.078894 0.000000 -0.004119 0.000000 -0.146054 0.000000 ) +( 0.078894 0.000000 0.004119 0.000000 -0.146054 0.000000 ) +( -0.078894 0.000000 -0.004119 0.000000 -0.146054 0.000000 ) +( -0.034339 0.000000 0.137023 0.000000 -0.001031 0.000000 ) +( 0.034339 0.000000 -0.137023 0.000000 -0.001031 0.000000 ) +( -0.034339 0.000000 0.137023 0.000000 -0.001031 0.000000 ) +( 0.034339 0.000000 -0.137023 0.000000 -0.001031 0.000000 ) +( 0.025606 0.000000 -0.333463 0.000000 0.054720 0.000000 ) +( -0.025606 0.000000 0.333463 0.000000 0.054720 0.000000 ) +( 0.025606 0.000000 -0.333463 0.000000 0.054720 0.000000 ) +( -0.025606 0.000000 0.333463 0.000000 0.054720 0.000000 ) +( -0.068789 0.000000 0.187755 0.000000 0.008445 0.000000 ) +( 0.068789 0.000000 -0.187755 0.000000 0.008445 0.000000 ) +( -0.068789 0.000000 0.187755 0.000000 0.008445 0.000000 ) +( 0.068789 0.000000 -0.187755 0.000000 0.008445 0.000000 ) +( 0.076318 0.000000 -0.120915 0.000000 0.038384 0.000000 ) +( -0.076318 0.000000 0.120915 0.000000 0.038384 0.000000 ) +( 0.076318 0.000000 -0.120915 0.000000 0.038384 0.000000 ) +( -0.076318 0.000000 0.120915 0.000000 0.038384 0.000000 ) +( 0.132100 0.000000 0.078271 0.000000 0.045537 0.000000 ) +( -0.132100 0.000000 -0.078271 0.000000 0.045537 0.000000 ) +( 0.132100 0.000000 0.078271 0.000000 0.045537 0.000000 ) +( -0.132100 0.000000 -0.078271 0.000000 0.045537 0.000000 ) + freq ( 31) = 34.58423469 [THz] = 1153.60589409 [cm-1] +( -0.072498 0.000000 -0.103612 0.000000 0.013560 0.000000 ) +( 0.072498 0.000000 0.103612 0.000000 0.013560 0.000000 ) +( 0.072498 0.000000 0.103612 0.000000 -0.013560 0.000000 ) +( -0.072498 0.000000 -0.103612 0.000000 -0.013560 0.000000 ) +( 0.123547 0.000000 0.080610 0.000000 -0.072839 0.000000 ) +( -0.123547 0.000000 -0.080610 0.000000 -0.072839 0.000000 ) +( -0.123547 0.000000 -0.080610 0.000000 0.072839 0.000000 ) +( 0.123547 0.000000 0.080610 0.000000 0.072839 0.000000 ) +( 0.213916 0.000000 -0.012196 0.000000 0.118482 0.000000 ) +( -0.213916 0.000000 0.012196 0.000000 0.118482 0.000000 ) +( -0.213916 0.000000 0.012196 0.000000 -0.118482 0.000000 ) +( 0.213916 0.000000 -0.012196 0.000000 -0.118482 0.000000 ) +( -0.081288 0.000000 0.052877 0.000000 0.002679 0.000000 ) +( 0.081288 0.000000 -0.052877 0.000000 0.002679 0.000000 ) +( 0.081288 0.000000 -0.052877 0.000000 -0.002679 0.000000 ) +( -0.081288 0.000000 0.052877 0.000000 -0.002679 0.000000 ) +( 0.104878 0.000000 -0.230893 0.000000 0.052827 0.000000 ) +( -0.104878 0.000000 0.230893 0.000000 0.052827 0.000000 ) +( -0.104878 0.000000 0.230893 0.000000 -0.052827 0.000000 ) +( 0.104878 0.000000 -0.230893 0.000000 -0.052827 0.000000 ) +( 0.129410 0.000000 0.231055 0.000000 -0.012829 0.000000 ) +( -0.129410 0.000000 -0.231055 0.000000 -0.012829 0.000000 ) +( -0.129410 0.000000 -0.231055 0.000000 0.012829 0.000000 ) +( 0.129410 0.000000 0.231055 0.000000 0.012829 0.000000 ) + freq ( 32) = 34.59245208 [THz] = 1153.87999689 [cm-1] +( 0.147911 0.000000 0.114024 0.000000 -0.062603 0.000000 ) +( 0.147911 0.000000 0.114024 0.000000 0.062603 0.000000 ) +( 0.147911 0.000000 0.114024 0.000000 -0.062603 0.000000 ) +( 0.147911 0.000000 0.114024 0.000000 0.062603 0.000000 ) +( -0.030496 0.000000 -0.188552 0.000000 0.086938 0.000000 ) +( -0.030496 0.000000 -0.188552 0.000000 -0.086938 0.000000 ) +( -0.030496 0.000000 -0.188552 0.000000 0.086938 0.000000 ) +( -0.030496 0.000000 -0.188552 0.000000 -0.086938 0.000000 ) +( -0.001297 0.000000 -0.112274 0.000000 0.075138 0.000000 ) +( -0.001297 0.000000 -0.112274 0.000000 -0.075138 0.000000 ) +( -0.001297 0.000000 -0.112274 0.000000 0.075138 0.000000 ) +( -0.001297 0.000000 -0.112274 0.000000 -0.075138 0.000000 ) +( -0.073133 0.000000 0.245336 0.000000 -0.047919 0.000000 ) +( -0.073133 0.000000 0.245336 0.000000 0.047919 0.000000 ) +( -0.073133 0.000000 0.245336 0.000000 -0.047919 0.000000 ) +( -0.073133 0.000000 0.245336 0.000000 0.047919 0.000000 ) +( -0.016838 0.000000 -0.050698 0.000000 0.132104 0.000000 ) +( -0.016838 0.000000 -0.050698 0.000000 -0.132104 0.000000 ) +( -0.016838 0.000000 -0.050698 0.000000 0.132104 0.000000 ) +( -0.016838 0.000000 -0.050698 0.000000 -0.132104 0.000000 ) +( -0.026148 0.000000 -0.007836 0.000000 -0.244998 0.000000 ) +( -0.026148 0.000000 -0.007836 0.000000 0.244998 0.000000 ) +( -0.026148 0.000000 -0.007836 0.000000 -0.244998 0.000000 ) +( -0.026148 0.000000 -0.007836 0.000000 0.244998 0.000000 ) + freq ( 33) = 36.03528514 [THz] = 1202.00772719 [cm-1] +( 0.222783 0.000000 -0.044493 0.000000 -0.068257 0.000000 ) +( 0.222783 0.000000 -0.044493 0.000000 0.068257 0.000000 ) +( -0.222783 0.000000 0.044493 0.000000 0.068257 0.000000 ) +( -0.222783 0.000000 0.044493 0.000000 -0.068257 0.000000 ) +( -0.136676 0.000000 0.037775 0.000000 0.121650 0.000000 ) +( -0.136676 0.000000 0.037775 0.000000 -0.121650 0.000000 ) +( 0.136676 0.000000 -0.037775 0.000000 -0.121650 0.000000 ) +( 0.136676 0.000000 -0.037775 0.000000 0.121650 0.000000 ) +( 0.012248 0.000000 0.158368 0.000000 -0.031001 0.000000 ) +( 0.012248 0.000000 0.158368 0.000000 0.031001 0.000000 ) +( -0.012248 0.000000 -0.158368 0.000000 0.031001 0.000000 ) +( -0.012248 0.000000 -0.158368 0.000000 -0.031001 0.000000 ) +( 0.198666 0.000000 0.007668 0.000000 0.039925 0.000000 ) +( 0.198666 0.000000 0.007668 0.000000 -0.039925 0.000000 ) +( -0.198666 0.000000 -0.007668 0.000000 -0.039925 0.000000 ) +( -0.198666 0.000000 -0.007668 0.000000 0.039925 0.000000 ) +( -0.119916 0.000000 -0.067145 0.000000 -0.193235 0.000000 ) +( -0.119916 0.000000 -0.067145 0.000000 0.193235 0.000000 ) +( 0.119916 0.000000 0.067145 0.000000 0.193235 0.000000 ) +( 0.119916 0.000000 0.067145 0.000000 -0.193235 0.000000 ) +( -0.105503 0.000000 -0.115616 0.000000 0.103850 0.000000 ) +( -0.105503 0.000000 -0.115616 0.000000 -0.103850 0.000000 ) +( 0.105503 0.000000 0.115616 0.000000 -0.103850 0.000000 ) +( 0.105503 0.000000 0.115616 0.000000 0.103850 0.000000 ) + freq ( 34) = 36.52639247 [THz] = 1218.38930433 [cm-1] +( -0.150209 0.000000 0.089586 -0.000000 -0.012300 -0.000000 ) +( 0.150209 -0.000000 -0.089586 0.000000 -0.012300 0.000000 ) +( -0.150209 0.000000 0.089586 -0.000000 -0.012300 -0.000000 ) +( 0.150209 -0.000000 -0.089586 0.000000 -0.012300 0.000000 ) +( 0.155801 -0.000000 0.105462 -0.000000 -0.144750 -0.000000 ) +( -0.155801 0.000000 -0.105462 0.000000 -0.144750 0.000000 ) +( 0.155801 -0.000000 0.105462 -0.000000 -0.144750 -0.000000 ) +( -0.155801 0.000000 -0.105462 0.000000 -0.144750 0.000000 ) +( -0.052049 0.000000 0.081067 -0.000000 0.016298 -0.000000 ) +( 0.052049 -0.000000 -0.081067 0.000000 0.016298 0.000000 ) +( -0.052049 0.000000 0.081067 -0.000000 0.016298 -0.000000 ) +( 0.052049 -0.000000 -0.081067 0.000000 0.016298 0.000000 ) +( -0.141638 0.000000 -0.221761 0.000000 0.055592 0.000000 ) +( 0.141638 -0.000000 0.221761 -0.000000 0.055592 -0.000000 ) +( -0.141638 0.000000 -0.221761 0.000000 0.055592 0.000000 ) +( 0.141638 -0.000000 0.221761 0.000000 0.055592 0.000000 ) +( 0.072653 -0.000000 -0.191509 0.000000 0.020033 0.000000 ) +( -0.072653 0.000000 0.191509 -0.000000 0.020033 -0.000000 ) +( 0.072653 -0.000000 -0.191509 0.000000 0.020033 0.000000 ) +( -0.072653 0.000000 0.191509 -0.000000 0.020033 -0.000000 ) +( 0.119479 -0.000000 0.141998 -0.000000 0.065127 -0.000000 ) +( -0.119479 0.000000 -0.141998 0.000000 0.065127 0.000000 ) +( 0.119479 -0.000000 0.141998 -0.000000 0.065127 -0.000000 ) +( -0.119479 0.000000 -0.141998 0.000000 0.065127 0.000000 ) + freq ( 35) = 36.54743844 [THz] = 1219.09132228 [cm-1] +( 0.200996 -0.000000 -0.087060 0.000000 -0.033454 0.000000 ) +( -0.200996 0.000000 0.087060 -0.000000 -0.033454 -0.000000 ) +( -0.200996 0.000000 0.087060 -0.000000 0.033454 -0.000000 ) +( 0.200996 -0.000000 -0.087060 0.000000 0.033454 0.000000 ) +( 0.016265 -0.000000 -0.130037 0.000000 0.098893 0.000000 ) +( -0.016265 0.000000 0.130037 -0.000000 0.098893 -0.000000 ) +( -0.016265 0.000000 0.130037 -0.000000 -0.098893 -0.000000 ) +( 0.016265 -0.000000 -0.130037 0.000000 -0.098893 0.000000 ) +( 0.003681 -0.000000 -0.028007 0.000000 0.084136 0.000000 ) +( -0.003681 0.000000 0.028007 -0.000000 0.084136 -0.000000 ) +( -0.003681 0.000000 0.028007 -0.000000 -0.084136 -0.000000 ) +( 0.003681 -0.000000 -0.028007 0.000000 -0.084136 0.000000 ) +( -0.128505 0.000000 -0.047905 0.000000 -0.061078 0.000000 ) +( 0.128505 -0.000000 0.047905 -0.000000 -0.061078 -0.000000 ) +( 0.128505 -0.000000 0.047905 -0.000000 0.061078 -0.000000 ) +( -0.128505 0.000000 -0.047905 0.000000 0.061078 0.000000 ) +( 0.030989 -0.000000 0.166425 -0.000000 0.199948 -0.000000 ) +( -0.030989 0.000000 -0.166425 0.000000 0.199948 0.000000 ) +( -0.030989 0.000000 -0.166425 0.000000 -0.199948 0.000000 ) +( 0.030989 -0.000000 0.166425 -0.000000 -0.199948 -0.000000 ) +( -0.025140 0.000000 0.119269 -0.000000 -0.245028 -0.000000 ) +( 0.025140 -0.000000 -0.119269 0.000000 -0.245028 0.000000 ) +( 0.025140 -0.000000 -0.119269 0.000000 0.245028 0.000000 ) +( -0.025140 0.000000 0.119269 -0.000000 0.245028 -0.000000 ) + freq ( 36) = 37.16540372 [THz] = 1239.70442530 [cm-1] +( -0.118609 0.000000 -0.061050 0.000000 -0.031436 0.000000 ) +( -0.118609 0.000000 -0.061050 0.000000 0.031436 0.000000 ) +( -0.118609 0.000000 -0.061050 0.000000 -0.031436 0.000000 ) +( -0.118609 0.000000 -0.061050 0.000000 0.031436 0.000000 ) +( 0.015539 -0.000000 0.010232 -0.000000 -0.044637 -0.000000 ) +( 0.015539 -0.000000 0.010232 -0.000000 0.044637 -0.000000 ) +( 0.015539 -0.000000 0.010232 -0.000000 -0.044637 -0.000000 ) +( 0.015539 -0.000000 0.010232 -0.000000 0.044637 -0.000000 ) +( -0.024151 0.000000 -0.220628 0.000000 -0.020316 0.000000 ) +( -0.024151 0.000000 -0.220628 0.000000 0.020316 0.000000 ) +( -0.024151 0.000000 -0.220628 0.000000 -0.020316 0.000000 ) +( -0.024151 0.000000 -0.220628 0.000000 0.020316 0.000000 ) +( 0.011681 -0.000000 -0.095375 0.000000 0.064026 0.000000 ) +( 0.011681 -0.000000 -0.095375 0.000000 -0.064026 0.000000 ) +( 0.011681 -0.000000 -0.095375 0.000000 0.064026 0.000000 ) +( 0.011681 -0.000000 -0.095375 0.000000 -0.064026 0.000000 ) +( 0.047153 -0.000000 0.347746 -0.000000 0.061400 -0.000000 ) +( 0.047153 -0.000000 0.347746 -0.000000 -0.061400 -0.000000 ) +( 0.047153 -0.000000 0.347746 -0.000000 0.061400 -0.000000 ) +( 0.047153 -0.000000 0.347746 0.000000 -0.061400 0.000000 ) +( 0.068388 -0.000000 0.019076 -0.000000 -0.184150 -0.000000 ) +( 0.068388 -0.000000 0.019076 -0.000000 0.184150 -0.000000 ) +( 0.068388 -0.000000 0.019076 -0.000000 -0.184150 -0.000000 ) +( 0.068388 -0.000000 0.019076 -0.000000 0.184150 -0.000000 ) + freq ( 37) = 38.66030479 [THz] = 1289.56895762 [cm-1] +( -0.011106 0.000000 0.181827 0.000000 -0.009489 0.000000 ) +( -0.011106 0.000000 0.181827 0.000000 0.009489 0.000000 ) +( -0.011106 0.000000 0.181827 0.000000 -0.009489 0.000000 ) +( -0.011106 0.000000 0.181827 0.000000 0.009489 0.000000 ) +( -0.048924 0.000000 -0.101672 0.000000 0.027624 0.000000 ) +( -0.048924 0.000000 -0.101672 0.000000 -0.027624 0.000000 ) +( -0.048924 0.000000 -0.101672 0.000000 0.027624 0.000000 ) +( -0.048924 0.000000 -0.101672 0.000000 -0.027624 0.000000 ) +( -0.072057 0.000000 -0.233152 0.000000 0.019344 0.000000 ) +( -0.072057 0.000000 -0.233152 0.000000 -0.019344 0.000000 ) +( -0.072057 0.000000 -0.233152 0.000000 0.019344 0.000000 ) +( -0.072057 0.000000 -0.233152 0.000000 -0.019344 0.000000 ) +( 0.145434 0.000000 -0.018353 0.000000 0.152053 0.000000 ) +( 0.145434 0.000000 -0.018353 0.000000 -0.152053 0.000000 ) +( 0.145434 0.000000 -0.018353 0.000000 0.152053 0.000000 ) +( 0.145434 0.000000 -0.018353 0.000000 -0.152053 0.000000 ) +( -0.053986 0.000000 -0.064909 0.000000 -0.038495 0.000000 ) +( -0.053986 0.000000 -0.064909 0.000000 0.038495 0.000000 ) +( -0.053986 0.000000 -0.064909 0.000000 -0.038495 0.000000 ) +( -0.053986 0.000000 -0.064909 0.000000 0.038495 0.000000 ) +( 0.040639 0.000000 0.236259 0.000000 0.180604 0.000000 ) +( 0.040639 0.000000 0.236259 0.000000 -0.180604 0.000000 ) +( 0.040639 0.000000 0.236259 0.000000 0.180604 0.000000 ) +( 0.040639 0.000000 0.236259 0.000000 -0.180604 0.000000 ) + freq ( 38) = 38.66114737 [THz] = 1289.59706286 [cm-1] +( -0.074185 0.000000 0.018308 0.000000 -0.042328 0.000000 ) +( 0.074185 0.000000 -0.018308 0.000000 -0.042328 0.000000 ) +( -0.074185 0.000000 0.018308 0.000000 -0.042328 0.000000 ) +( 0.074185 0.000000 -0.018308 0.000000 -0.042328 0.000000 ) +( -0.023337 0.000000 0.153777 0.000000 -0.106820 0.000000 ) +( 0.023337 0.000000 -0.153777 0.000000 -0.106820 0.000000 ) +( -0.023337 0.000000 0.153777 0.000000 -0.106820 0.000000 ) +( 0.023337 0.000000 -0.153777 0.000000 -0.106820 0.000000 ) +( -0.051548 0.000000 -0.064655 0.000000 -0.100593 0.000000 ) +( 0.051548 0.000000 0.064655 0.000000 -0.100593 0.000000 ) +( -0.051548 0.000000 -0.064655 0.000000 -0.100593 0.000000 ) +( 0.051548 0.000000 0.064655 0.000000 -0.100593 0.000000 ) +( 0.059990 0.000000 -0.048607 0.000000 0.029839 0.000000 ) +( -0.059990 0.000000 0.048607 0.000000 0.029839 0.000000 ) +( 0.059990 0.000000 -0.048607 0.000000 0.029839 0.000000 ) +( -0.059990 0.000000 0.048607 0.000000 0.029839 0.000000 ) +( -0.020713 0.000000 0.147541 0.000000 -0.096600 0.000000 ) +( 0.020713 0.000000 -0.147541 0.000000 -0.096600 0.000000 ) +( -0.020713 0.000000 0.147541 0.000000 -0.096600 0.000000 ) +( 0.020713 0.000000 -0.147541 0.000000 -0.096600 0.000000 ) +( 0.017133 0.000000 -0.225749 0.000000 0.316502 0.000000 ) +( -0.017133 0.000000 0.225749 0.000000 0.316502 0.000000 ) +( 0.017133 0.000000 -0.225749 0.000000 0.316502 0.000000 ) +( -0.017133 0.000000 0.225749 0.000000 0.316502 0.000000 ) + freq ( 39) = 38.68210754 [THz] = 1290.29621919 [cm-1] +( -0.080195 0.000000 0.090532 -0.000000 -0.083776 -0.000000 ) +( 0.080195 -0.000000 -0.090532 0.000000 -0.083776 0.000000 ) +( 0.080195 -0.000000 -0.090532 0.000000 0.083776 0.000000 ) +( -0.080195 0.000000 0.090532 -0.000000 0.083776 -0.000000 ) +( -0.068433 0.000000 -0.088202 0.000000 0.002777 0.000000 ) +( 0.068433 -0.000000 0.088202 -0.000000 0.002777 -0.000000 ) +( 0.068433 -0.000000 0.088202 -0.000000 -0.002777 -0.000000 ) +( -0.068433 0.000000 -0.088202 0.000000 -0.002777 0.000000 ) +( -0.097956 0.000000 0.314530 0.000000 0.035023 0.000000 ) +( 0.097956 -0.000000 -0.314530 0.000000 0.035023 0.000000 ) +( 0.097956 -0.000000 -0.314530 0.000000 -0.035023 0.000000 ) +( -0.097956 0.000000 0.314530 -0.000000 -0.035023 -0.000000 ) +( -0.022088 0.000000 -0.111966 0.000000 0.147891 0.000000 ) +( 0.022088 -0.000000 0.111966 -0.000000 0.147891 -0.000000 ) +( 0.022088 -0.000000 0.111966 -0.000000 -0.147891 -0.000000 ) +( -0.022088 0.000000 -0.111966 0.000000 -0.147891 0.000000 ) +( 0.028006 -0.000000 -0.166336 0.000000 0.063516 0.000000 ) +( -0.028006 0.000000 0.166336 -0.000000 0.063516 -0.000000 ) +( -0.028006 0.000000 0.166336 -0.000000 -0.063516 -0.000000 ) +( 0.028006 -0.000000 -0.166336 0.000000 -0.063516 0.000000 ) +( 0.087581 -0.000000 -0.057695 0.000000 -0.166587 0.000000 ) +( -0.087581 0.000000 0.057695 -0.000000 -0.166587 -0.000000 ) +( -0.087581 0.000000 0.057695 -0.000000 0.166587 -0.000000 ) +( 0.087581 -0.000000 -0.057695 0.000000 0.166587 0.000000 ) + freq ( 40) = 40.71951603 [THz] = 1358.25685087 [cm-1] +( 0.117934 -0.000000 0.135668 -0.000000 -0.084508 -0.000000 ) +( 0.117934 -0.000000 0.135668 -0.000000 0.084508 -0.000000 ) +( 0.117934 -0.000000 0.135668 -0.000000 -0.084508 -0.000000 ) +( 0.117934 -0.000000 0.135668 -0.000000 0.084508 -0.000000 ) +( -0.047690 0.000000 0.348059 0.000000 0.017593 0.000000 ) +( -0.047690 0.000000 0.348059 -0.000000 -0.017593 -0.000000 ) +( -0.047690 0.000000 0.348059 -0.000000 0.017593 -0.000000 ) +( -0.047690 0.000000 0.348059 -0.000000 -0.017593 -0.000000 ) +( -0.039458 0.000000 -0.142703 0.000000 0.017883 0.000000 ) +( -0.039458 0.000000 -0.142703 0.000000 -0.017883 0.000000 ) +( -0.039458 0.000000 -0.142703 0.000000 0.017883 0.000000 ) +( -0.039458 0.000000 -0.142703 0.000000 -0.017883 0.000000 ) +( 0.064971 -0.000000 -0.073312 0.000000 0.061624 0.000000 ) +( 0.064971 -0.000000 -0.073312 0.000000 -0.061624 0.000000 ) +( 0.064971 -0.000000 -0.073312 0.000000 0.061624 0.000000 ) +( 0.064971 -0.000000 -0.073312 0.000000 -0.061624 0.000000 ) +( -0.047489 0.000000 -0.096595 0.000000 0.056654 0.000000 ) +( -0.047489 0.000000 -0.096595 0.000000 -0.056654 0.000000 ) +( -0.047489 0.000000 -0.096595 0.000000 0.056654 0.000000 ) +( -0.047489 0.000000 -0.096595 0.000000 -0.056654 0.000000 ) +( -0.048268 0.000000 -0.171117 0.000000 -0.069101 0.000000 ) +( -0.048268 0.000000 -0.171117 0.000000 0.069101 0.000000 ) +( -0.048268 0.000000 -0.171117 0.000000 -0.069101 0.000000 ) +( -0.048268 0.000000 -0.171117 0.000000 0.069101 0.000000 ) + freq ( 41) = 40.79719523 [THz] = 1360.84795018 [cm-1] +( -0.075686 0.000000 -0.167291 0.000000 0.024877 0.000000 ) +( 0.075686 0.000000 0.167291 0.000000 0.024877 0.000000 ) +( 0.075686 0.000000 0.167291 0.000000 -0.024877 0.000000 ) +( -0.075686 0.000000 -0.167291 0.000000 -0.024877 0.000000 ) +( 0.021736 0.000000 -0.290747 0.000000 -0.061075 0.000000 ) +( -0.021736 0.000000 0.290747 0.000000 -0.061075 0.000000 ) +( -0.021736 0.000000 0.290747 0.000000 0.061075 0.000000 ) +( 0.021736 0.000000 -0.290747 0.000000 0.061075 0.000000 ) +( 0.085408 0.000000 0.202781 0.000000 -0.030545 0.000000 ) +( -0.085408 0.000000 -0.202781 0.000000 -0.030545 0.000000 ) +( -0.085408 0.000000 -0.202781 0.000000 0.030545 0.000000 ) +( 0.085408 0.000000 0.202781 0.000000 0.030545 0.000000 ) +( 0.044971 0.000000 0.011577 0.000000 0.000669 0.000000 ) +( -0.044971 0.000000 -0.011577 0.000000 0.000669 0.000000 ) +( -0.044971 0.000000 -0.011577 0.000000 -0.000669 0.000000 ) +( 0.044971 0.000000 0.011577 0.000000 -0.000669 0.000000 ) +( 0.018349 0.000000 0.168335 0.000000 -0.063884 0.000000 ) +( -0.018349 0.000000 -0.168335 0.000000 -0.063884 0.000000 ) +( -0.018349 0.000000 -0.168335 0.000000 0.063884 0.000000 ) +( 0.018349 0.000000 0.168335 0.000000 0.063884 0.000000 ) +( 0.024119 0.000000 0.101671 0.000000 0.178192 0.000000 ) +( -0.024119 0.000000 -0.101671 0.000000 0.178192 0.000000 ) +( -0.024119 0.000000 -0.101671 0.000000 -0.178192 0.000000 ) +( 0.024119 0.000000 0.101671 0.000000 -0.178192 0.000000 ) + freq ( 42) = 41.34918543 [THz] = 1379.26036131 [cm-1] +( 0.074398 0.000000 0.055621 0.000000 -0.040886 0.000000 ) +( -0.074398 0.000000 -0.055621 0.000000 -0.040886 0.000000 ) +( 0.074398 0.000000 0.055621 0.000000 -0.040886 0.000000 ) +( -0.074398 0.000000 -0.055621 0.000000 -0.040886 0.000000 ) +( 0.025315 0.000000 0.033146 0.000000 0.037543 0.000000 ) +( -0.025315 0.000000 -0.033146 0.000000 0.037543 0.000000 ) +( 0.025315 0.000000 0.033146 0.000000 0.037543 0.000000 ) +( -0.025315 0.000000 -0.033146 0.000000 0.037543 0.000000 ) +( -0.086883 0.000000 -0.185310 0.000000 0.044593 0.000000 ) +( 0.086883 0.000000 0.185310 0.000000 0.044593 0.000000 ) +( -0.086883 0.000000 -0.185310 0.000000 0.044593 0.000000 ) +( 0.086883 0.000000 0.185310 0.000000 0.044593 0.000000 ) +( -0.113249 0.000000 -0.257506 0.000000 0.032810 0.000000 ) +( 0.113249 0.000000 0.257506 0.000000 0.032810 0.000000 ) +( -0.113249 0.000000 -0.257506 0.000000 0.032810 0.000000 ) +( 0.113249 0.000000 0.257506 0.000000 0.032810 0.000000 ) +( 0.014306 0.000000 0.287044 0.000000 0.079159 0.000000 ) +( -0.014306 0.000000 -0.287044 0.000000 0.079159 0.000000 ) +( 0.014306 0.000000 0.287044 0.000000 0.079159 0.000000 ) +( -0.014306 0.000000 -0.287044 0.000000 0.079159 0.000000 ) +( -0.004933 0.000000 0.009881 0.000000 -0.153218 0.000000 ) +( 0.004933 0.000000 -0.009881 0.000000 -0.153218 0.000000 ) +( -0.004933 0.000000 0.009881 0.000000 -0.153218 0.000000 ) +( 0.004933 0.000000 -0.009881 0.000000 -0.153218 0.000000 ) + freq ( 43) = 42.50821503 [THz] = 1417.92142706 [cm-1] +( -0.096669 0.000000 -0.095104 0.000000 0.039041 0.000000 ) +( -0.096669 0.000000 -0.095104 0.000000 -0.039041 0.000000 ) +( 0.096669 0.000000 0.095104 0.000000 -0.039041 0.000000 ) +( 0.096669 0.000000 0.095104 0.000000 0.039041 0.000000 ) +( 0.058085 0.000000 0.071426 0.000000 -0.029255 0.000000 ) +( 0.058085 0.000000 0.071426 0.000000 0.029255 0.000000 ) +( -0.058085 0.000000 -0.071426 0.000000 0.029255 0.000000 ) +( -0.058085 0.000000 -0.071426 0.000000 -0.029255 0.000000 ) +( 0.017626 0.000000 0.346695 0.000000 0.048809 0.000000 ) +( 0.017626 0.000000 0.346695 0.000000 -0.048809 0.000000 ) +( -0.017626 0.000000 -0.346695 0.000000 -0.048809 0.000000 ) +( -0.017626 0.000000 -0.346695 0.000000 0.048809 0.000000 ) +( -0.124885 0.000000 0.004360 0.000000 0.014514 0.000000 ) +( -0.124885 0.000000 0.004360 0.000000 -0.014514 0.000000 ) +( 0.124885 0.000000 -0.004360 0.000000 -0.014514 0.000000 ) +( 0.124885 0.000000 -0.004360 0.000000 0.014514 0.000000 ) +( 0.047784 0.000000 -0.096443 0.000000 0.105447 0.000000 ) +( 0.047784 0.000000 -0.096443 0.000000 -0.105447 0.000000 ) +( -0.047784 0.000000 0.096443 0.000000 -0.105447 0.000000 ) +( -0.047784 0.000000 0.096443 0.000000 0.105447 0.000000 ) +( 0.020761 0.000000 -0.235585 0.000000 -0.058336 0.000000 ) +( 0.020761 0.000000 -0.235585 0.000000 0.058336 0.000000 ) +( -0.020761 0.000000 0.235585 0.000000 0.058336 0.000000 ) +( -0.020761 0.000000 0.235585 0.000000 -0.058336 0.000000 ) + freq ( 44) = 45.97637865 [THz] = 1533.60691312 [cm-1] +( -0.025238 0.000000 0.293846 -0.000000 0.004843 -0.000000 ) +( 0.025238 -0.000000 -0.293846 0.000000 0.004843 0.000000 ) +( -0.025238 0.000000 0.293846 -0.000000 0.004843 -0.000000 ) +( 0.025238 -0.000000 -0.293846 0.000000 0.004843 0.000000 ) +( 0.058873 -0.000000 -0.135964 0.000000 -0.013167 0.000000 ) +( -0.058873 0.000000 0.135964 -0.000000 -0.013167 -0.000000 ) +( 0.058873 -0.000000 -0.135964 0.000000 -0.013167 0.000000 ) +( -0.058873 0.000000 0.135964 -0.000000 -0.013167 -0.000000 ) +( 0.004994 -0.000000 -0.042532 0.000000 0.035976 0.000000 ) +( -0.004994 0.000000 0.042532 -0.000000 0.035976 -0.000000 ) +( 0.004994 -0.000000 -0.042532 0.000000 0.035976 0.000000 ) +( -0.004994 0.000000 0.042532 -0.000000 0.035976 -0.000000 ) +( -0.099565 0.000000 0.049205 -0.000000 -0.027278 -0.000000 ) +( 0.099565 -0.000000 -0.049205 0.000000 -0.027278 0.000000 ) +( -0.099565 0.000000 0.049205 -0.000000 -0.027278 -0.000000 ) +( 0.099565 -0.000000 -0.049205 0.000000 -0.027278 0.000000 ) +( 0.016116 -0.000000 -0.111311 0.000000 0.074480 0.000000 ) +( -0.016116 0.000000 0.111311 -0.000000 0.074480 -0.000000 ) +( 0.016116 -0.000000 -0.111311 0.000000 0.074480 0.000000 ) +( -0.016116 0.000000 0.111311 -0.000000 0.074480 -0.000000 ) +( 0.005336 -0.000000 -0.317542 0.000000 -0.074854 0.000000 ) +( -0.005336 0.000000 0.317542 -0.000000 -0.074854 -0.000000 ) +( 0.005336 -0.000000 -0.317542 0.000000 -0.074854 0.000000 ) +( -0.005336 0.000000 0.317542 0.000000 -0.074854 0.000000 ) + freq ( 45) = 46.81188124 [THz] = 1561.47627972 [cm-1] +( -0.022037 0.000000 -0.203954 0.000000 -0.047504 0.000000 ) +( 0.022037 0.000000 0.203954 0.000000 -0.047504 0.000000 ) +( 0.022037 0.000000 0.203954 0.000000 0.047504 0.000000 ) +( -0.022037 0.000000 -0.203954 0.000000 0.047504 0.000000 ) +( -0.037669 0.000000 0.015645 0.000000 0.002418 0.000000 ) +( 0.037669 0.000000 -0.015645 0.000000 0.002418 0.000000 ) +( 0.037669 0.000000 -0.015645 0.000000 -0.002418 0.000000 ) +( -0.037669 0.000000 0.015645 0.000000 -0.002418 0.000000 ) +( 0.003995 0.000000 0.046505 0.000000 0.010979 0.000000 ) +( -0.003995 0.000000 -0.046505 0.000000 0.010979 0.000000 ) +( -0.003995 0.000000 -0.046505 0.000000 -0.010979 0.000000 ) +( 0.003995 0.000000 0.046505 0.000000 -0.010979 0.000000 ) +( 0.008852 0.000000 0.376500 0.000000 0.017232 0.000000 ) +( -0.008852 0.000000 -0.376500 0.000000 0.017232 0.000000 ) +( -0.008852 0.000000 -0.376500 0.000000 -0.017232 0.000000 ) +( 0.008852 0.000000 0.376500 0.000000 -0.017232 0.000000 ) +( 0.008409 0.000000 -0.004591 0.000000 0.041351 0.000000 ) +( -0.008409 0.000000 0.004591 0.000000 0.041351 0.000000 ) +( -0.008409 0.000000 0.004591 0.000000 -0.041351 0.000000 ) +( 0.008409 0.000000 -0.004591 0.000000 -0.041351 0.000000 ) +( 0.032420 0.000000 -0.212270 0.000000 -0.107946 0.000000 ) +( -0.032420 0.000000 0.212270 0.000000 -0.107946 0.000000 ) +( -0.032420 0.000000 0.212270 0.000000 0.107946 0.000000 ) +( 0.032420 0.000000 -0.212270 0.000000 0.107946 0.000000 ) + freq ( 46) = 53.56914465 [THz] = 1786.87432489 [cm-1] +( -0.018005 0.000000 -0.262342 0.000000 0.016822 0.000000 ) +( 0.018005 -0.000000 0.262342 0.000000 0.016822 0.000000 ) +( -0.018005 0.000000 -0.262342 0.000000 0.016822 0.000000 ) +( 0.018005 -0.000000 0.262342 -0.000000 0.016822 -0.000000 ) +( -0.000874 0.000000 -0.152352 0.000000 0.000448 0.000000 ) +( 0.000874 -0.000000 0.152352 -0.000000 0.000448 -0.000000 ) +( -0.000874 0.000000 -0.152352 0.000000 0.000448 0.000000 ) +( 0.000874 -0.000000 0.152352 -0.000000 0.000448 -0.000000 ) +( 0.019800 -0.000000 -0.187695 0.000000 0.013575 0.000000 ) +( -0.019800 0.000000 0.187695 -0.000000 0.013575 -0.000000 ) +( 0.019800 -0.000000 -0.187695 0.000000 0.013575 0.000000 ) +( -0.019800 0.000000 0.187695 -0.000000 0.013575 -0.000000 ) +( 0.073289 -0.000000 -0.216643 0.000000 0.046736 0.000000 ) +( -0.073289 0.000000 0.216643 -0.000000 0.046736 -0.000000 ) +( 0.073289 -0.000000 -0.216643 0.000000 0.046736 0.000000 ) +( -0.073289 0.000000 0.216643 -0.000000 0.046736 -0.000000 ) +( -0.020550 0.000000 -0.203560 0.000000 -0.054929 0.000000 ) +( 0.020550 -0.000000 0.203560 -0.000000 -0.054929 -0.000000 ) +( -0.020550 0.000000 -0.203560 0.000000 -0.054929 0.000000 ) +( 0.020550 -0.000000 0.203560 -0.000000 -0.054929 -0.000000 ) +( -0.008432 0.000000 -0.146974 0.000000 -0.022651 0.000000 ) +( 0.008432 -0.000000 0.146974 -0.000000 -0.022651 -0.000000 ) +( -0.008432 0.000000 -0.146974 0.000000 -0.022651 0.000000 ) +( 0.008432 -0.000000 0.146974 -0.000000 -0.022651 -0.000000 ) + freq ( 47) = 55.03019875 [THz] = 1835.60984392 [cm-1] +( -0.062124 0.000000 0.171070 0.000000 -0.000888 0.000000 ) +( -0.062124 0.000000 0.171070 0.000000 0.000888 0.000000 ) +( 0.062124 0.000000 -0.171070 0.000000 0.000888 0.000000 ) +( 0.062124 0.000000 -0.171070 0.000000 -0.000888 0.000000 ) +( -0.060193 0.000000 0.164131 0.000000 -0.012242 0.000000 ) +( -0.060193 0.000000 0.164131 0.000000 0.012242 0.000000 ) +( 0.060193 0.000000 -0.164131 0.000000 0.012242 0.000000 ) +( 0.060193 0.000000 -0.164131 0.000000 -0.012242 0.000000 ) +( 0.059302 0.000000 0.206687 0.000000 0.011339 0.000000 ) +( 0.059302 0.000000 0.206687 0.000000 -0.011339 0.000000 ) +( -0.059302 0.000000 -0.206687 0.000000 -0.011339 0.000000 ) +( -0.059302 0.000000 -0.206687 0.000000 0.011339 0.000000 ) +( 0.066175 0.000000 0.228813 0.000000 0.014379 0.000000 ) +( 0.066175 0.000000 0.228813 0.000000 -0.014379 0.000000 ) +( -0.066175 0.000000 -0.228813 0.000000 -0.014379 0.000000 ) +( -0.066175 0.000000 -0.228813 0.000000 0.014379 0.000000 ) +( -0.026815 0.000000 0.196674 0.000000 0.025723 0.000000 ) +( -0.026815 0.000000 0.196674 0.000000 -0.025723 0.000000 ) +( 0.026815 0.000000 -0.196674 0.000000 -0.025723 0.000000 ) +( 0.026815 0.000000 -0.196674 0.000000 0.025723 0.000000 ) +( -0.012032 0.000000 0.204802 0.000000 -0.026578 0.000000 ) +( -0.012032 0.000000 0.204802 0.000000 0.026578 0.000000 ) +( 0.012032 0.000000 -0.204802 0.000000 0.026578 0.000000 ) +( 0.012032 0.000000 -0.204802 0.000000 -0.026578 0.000000 ) + freq ( 48) = 57.73992927 [THz] = 1925.99672470 [cm-1] +( 0.104319 -0.000000 0.000638 -0.000000 0.021822 -0.000000 ) +( 0.104319 -0.000000 0.000638 -0.000000 -0.021822 -0.000000 ) +( 0.104319 -0.000000 0.000638 -0.000000 0.021822 -0.000000 ) +( 0.104319 -0.000000 0.000638 -0.000000 -0.021822 -0.000000 ) +( 0.307522 -0.000000 0.007427 -0.000000 -0.095881 -0.000000 ) +( 0.307522 -0.000000 0.007427 -0.000000 0.095881 -0.000000 ) +( 0.307522 0.000000 0.007427 -0.000000 -0.095881 -0.000000 ) +( 0.307522 -0.000000 0.007427 -0.000000 0.095881 -0.000000 ) +( -0.066409 0.000000 -0.031814 0.000000 0.158763 0.000000 ) +( -0.066409 0.000000 -0.031814 0.000000 -0.158763 0.000000 ) +( -0.066409 0.000000 -0.031814 0.000000 0.158763 0.000000 ) +( -0.066409 0.000000 -0.031814 0.000000 -0.158763 0.000000 ) +( -0.155036 0.000000 -0.015829 0.000000 0.115043 0.000000 ) +( -0.155036 0.000000 -0.015829 0.000000 -0.115043 0.000000 ) +( -0.155036 0.000000 -0.015829 0.000000 0.115043 0.000000 ) +( -0.155036 0.000000 -0.015829 0.000000 -0.115043 0.000000 ) +( -0.133753 0.000000 0.014219 -0.000000 -0.205903 -0.000000 ) +( -0.133753 0.000000 0.014219 -0.000000 0.205903 -0.000000 ) +( -0.133753 0.000000 0.014219 -0.000000 -0.205903 -0.000000 ) +( -0.133753 0.000000 0.014219 -0.000000 0.205903 -0.000000 ) +( -0.056642 0.000000 0.025359 -0.000000 -0.048309 -0.000000 ) +( -0.056642 0.000000 0.025359 -0.000000 0.048309 -0.000000 ) +( -0.056642 0.000000 0.025359 -0.000000 -0.048309 -0.000000 ) +( -0.056642 0.000000 0.025359 -0.000000 0.048309 -0.000000 ) + freq ( 49) = 58.48366789 [THz] = 1950.80517448 [cm-1] +( -0.042218 0.000000 -0.038175 0.000000 -0.152088 0.000000 ) +( -0.042218 0.000000 -0.038175 0.000000 0.152088 0.000000 ) +( 0.042218 0.000000 0.038175 0.000000 0.152088 0.000000 ) +( 0.042218 0.000000 0.038175 0.000000 -0.152088 0.000000 ) +( 0.005000 0.000000 -0.064577 0.000000 -0.200197 0.000000 ) +( 0.005000 0.000000 -0.064577 0.000000 0.200197 0.000000 ) +( -0.005000 0.000000 0.064577 0.000000 0.200197 0.000000 ) +( -0.005000 0.000000 0.064577 0.000000 -0.200197 0.000000 ) +( 0.271691 0.000000 -0.048143 0.000000 0.134615 0.000000 ) +( 0.271691 0.000000 -0.048143 0.000000 -0.134615 0.000000 ) +( -0.271691 0.000000 0.048143 0.000000 -0.134615 0.000000 ) +( -0.271691 0.000000 0.048143 0.000000 0.134615 0.000000 ) +( 0.112109 0.000000 -0.005051 0.000000 0.062405 0.000000 ) +( 0.112109 0.000000 -0.005051 0.000000 -0.062405 0.000000 ) +( -0.112109 0.000000 0.005051 0.000000 -0.062405 0.000000 ) +( -0.112109 0.000000 0.005051 0.000000 0.062405 0.000000 ) +( -0.150097 0.000000 -0.033787 0.000000 0.159789 0.000000 ) +( -0.150097 0.000000 -0.033787 0.000000 -0.159789 0.000000 ) +( 0.150097 0.000000 0.033787 0.000000 -0.159789 0.000000 ) +( 0.150097 0.000000 0.033787 0.000000 0.159789 0.000000 ) +( -0.135741 0.000000 -0.025751 0.000000 0.017893 0.000000 ) +( -0.135741 0.000000 -0.025751 0.000000 -0.017893 0.000000 ) +( 0.135741 0.000000 0.025751 0.000000 -0.017893 0.000000 ) +( 0.135741 0.000000 0.025751 0.000000 0.017893 0.000000 ) + freq ( 50) = 60.21886190 [THz] = 2008.68501643 [cm-1] +( 0.138204 -0.000000 0.058021 -0.000000 -0.206528 -0.000000 ) +( -0.138204 0.000000 -0.058021 0.000000 -0.206528 0.000000 ) +( -0.138204 0.000000 -0.058021 0.000000 0.206528 0.000000 ) +( 0.138204 -0.000000 0.058021 -0.000000 0.206528 -0.000000 ) +( 0.171382 -0.000000 -0.040343 0.000000 -0.178575 0.000000 ) +( -0.171382 0.000000 0.040343 -0.000000 -0.178575 -0.000000 ) +( -0.171382 0.000000 0.040343 -0.000000 0.178575 -0.000000 ) +( 0.171382 -0.000000 -0.040343 0.000000 0.178575 0.000000 ) +( 0.049735 -0.000000 0.033835 -0.000000 0.046826 -0.000000 ) +( -0.049735 0.000000 -0.033835 0.000000 0.046826 0.000000 ) +( -0.049735 0.000000 -0.033835 0.000000 -0.046826 0.000000 ) +( 0.049735 -0.000000 0.033835 -0.000000 -0.046826 -0.000000 ) +( -0.130197 0.000000 -0.006560 0.000000 -0.003199 0.000000 ) +( 0.130197 -0.000000 0.006560 -0.000000 -0.003199 -0.000000 ) +( 0.130197 -0.000000 0.006560 -0.000000 0.003199 -0.000000 ) +( -0.130197 0.000000 -0.006560 0.000000 0.003199 0.000000 ) +( -0.128873 0.000000 -0.049526 0.000000 0.152904 0.000000 ) +( 0.128873 -0.000000 0.049526 -0.000000 0.152904 -0.000000 ) +( 0.128873 -0.000000 0.049526 -0.000000 -0.152904 -0.000000 ) +( -0.128873 0.000000 -0.049526 0.000000 -0.152904 0.000000 ) +( -0.070484 0.000000 -0.141478 0.000000 0.178187 0.000000 ) +( 0.070484 -0.000000 0.141478 -0.000000 0.178187 -0.000000 ) +( 0.070484 -0.000000 0.141478 -0.000000 -0.178187 -0.000000 ) +( -0.070484 0.000000 -0.141478 0.000000 -0.178187 0.000000 ) + freq ( 51) = 60.38373067 [THz] = 2014.18444662 [cm-1] +( -0.155584 0.000000 0.008914 0.000000 0.164337 0.000000 ) +( -0.155584 0.000000 0.008914 0.000000 -0.164337 0.000000 ) +( -0.155584 0.000000 0.008914 0.000000 0.164337 0.000000 ) +( -0.155584 0.000000 0.008914 0.000000 -0.164337 0.000000 ) +( -0.087379 0.000000 -0.004648 0.000000 0.048152 0.000000 ) +( -0.087379 0.000000 -0.004648 0.000000 -0.048152 0.000000 ) +( -0.087379 0.000000 -0.004648 0.000000 0.048152 0.000000 ) +( -0.087379 0.000000 -0.004648 0.000000 -0.048152 0.000000 ) +( 0.050663 0.000000 0.064655 0.000000 0.093043 0.000000 ) +( 0.050663 0.000000 0.064655 0.000000 -0.093043 0.000000 ) +( 0.050663 0.000000 0.064655 0.000000 0.093043 0.000000 ) +( 0.050663 0.000000 0.064655 0.000000 -0.093043 0.000000 ) +( 0.207085 0.000000 0.044342 0.000000 0.133210 0.000000 ) +( 0.207085 0.000000 0.044342 0.000000 -0.133210 0.000000 ) +( 0.207085 0.000000 0.044342 0.000000 0.133210 0.000000 ) +( 0.207085 0.000000 0.044342 0.000000 -0.133210 0.000000 ) +( 0.020163 0.000000 -0.079084 0.000000 -0.211038 0.000000 ) +( 0.020163 0.000000 -0.079084 0.000000 0.211038 0.000000 ) +( 0.020163 0.000000 -0.079084 0.000000 -0.211038 0.000000 ) +( 0.020163 0.000000 -0.079084 0.000000 0.211038 0.000000 ) +( -0.034948 0.000000 -0.034179 0.000000 -0.239051 0.000000 ) +( -0.034948 0.000000 -0.034179 0.000000 0.239051 0.000000 ) +( -0.034948 0.000000 -0.034179 0.000000 -0.239051 0.000000 ) +( -0.034948 0.000000 -0.034179 0.000000 0.239051 0.000000 ) + freq ( 52) = 62.15559350 [THz] = 2073.28742889 [cm-1] +( -0.207677 0.000000 -0.151258 0.000000 0.134769 0.000000 ) +( -0.207677 0.000000 -0.151258 0.000000 -0.134769 0.000000 ) +( 0.207677 0.000000 0.151258 0.000000 -0.134769 0.000000 ) +( 0.207677 0.000000 0.151258 0.000000 0.134769 0.000000 ) +( -0.140366 0.000000 -0.207983 0.000000 0.085037 0.000000 ) +( -0.140366 0.000000 -0.207983 0.000000 -0.085037 0.000000 ) +( 0.140366 0.000000 0.207983 0.000000 -0.085037 0.000000 ) +( 0.140366 0.000000 0.207983 0.000000 0.085037 0.000000 ) +( 0.073592 0.000000 0.015109 0.000000 0.005302 0.000000 ) +( 0.073592 0.000000 0.015109 0.000000 -0.005302 0.000000 ) +( -0.073592 0.000000 -0.015109 0.000000 -0.005302 0.000000 ) +( -0.073592 0.000000 -0.015109 0.000000 0.005302 0.000000 ) +( 0.179308 0.000000 0.043867 0.000000 0.057535 0.000000 ) +( 0.179308 0.000000 0.043867 0.000000 -0.057535 0.000000 ) +( -0.179308 0.000000 -0.043867 0.000000 -0.057535 0.000000 ) +( -0.179308 0.000000 -0.043867 0.000000 0.057535 0.000000 ) +( 0.064302 0.000000 0.047355 0.000000 -0.096443 0.000000 ) +( 0.064302 0.000000 0.047355 0.000000 0.096443 0.000000 ) +( -0.064302 0.000000 -0.047355 0.000000 0.096443 0.000000 ) +( -0.064302 0.000000 -0.047355 0.000000 -0.096443 0.000000 ) +( 0.023369 0.000000 -0.001709 0.000000 -0.190662 0.000000 ) +( 0.023369 0.000000 -0.001709 0.000000 0.190662 0.000000 ) +( -0.023369 0.000000 0.001709 0.000000 0.190662 0.000000 ) +( -0.023369 0.000000 0.001709 0.000000 -0.190662 0.000000 ) + freq ( 53) = 62.74513187 [THz] = 2092.95231200 [cm-1] +( 0.026609 -0.000000 -0.011179 0.000000 -0.123056 0.000000 ) +( -0.026609 0.000000 0.011179 -0.000000 -0.123056 -0.000000 ) +( 0.026609 -0.000000 -0.011179 0.000000 -0.123056 0.000000 ) +( -0.026609 0.000000 0.011179 -0.000000 -0.123056 -0.000000 ) +( -0.169515 0.000000 -0.151786 0.000000 0.007105 0.000000 ) +( 0.169515 -0.000000 0.151786 -0.000000 0.007105 -0.000000 ) +( -0.169515 0.000000 -0.151786 0.000000 0.007105 0.000000 ) +( 0.169515 -0.000000 0.151786 -0.000000 0.007105 -0.000000 ) +( 0.058462 -0.000000 0.040340 -0.000000 -0.164889 -0.000000 ) +( -0.058462 0.000000 -0.040340 0.000000 -0.164889 0.000000 ) +( 0.058462 -0.000000 0.040340 -0.000000 -0.164889 -0.000000 ) +( -0.058462 0.000000 -0.040340 0.000000 -0.164889 0.000000 ) +( -0.026324 0.000000 -0.095451 0.000000 -0.156346 0.000000 ) +( 0.026324 -0.000000 0.095451 -0.000000 -0.156346 -0.000000 ) +( -0.026324 0.000000 -0.095451 0.000000 -0.156346 0.000000 ) +( 0.026324 -0.000000 0.095451 -0.000000 -0.156346 -0.000000 ) +( 0.082640 -0.000000 -0.004933 0.000000 0.288950 0.000000 ) +( -0.082640 0.000000 0.004933 -0.000000 0.288950 -0.000000 ) +( 0.082640 -0.000000 -0.004933 0.000000 0.288950 0.000000 ) +( -0.082640 0.000000 0.004933 -0.000000 0.288950 -0.000000 ) +( 0.040334 -0.000000 0.042091 -0.000000 0.148236 -0.000000 ) +( -0.040334 0.000000 -0.042091 0.000000 0.148236 0.000000 ) +( 0.040334 -0.000000 0.042091 -0.000000 0.148236 -0.000000 ) +( -0.040334 0.000000 -0.042091 0.000000 0.148236 0.000000 ) + freq ( 54) = 63.23276472 [THz] = 2109.21799332 [cm-1] +( 0.110723 0.000000 -0.044496 0.000000 0.005310 0.000000 ) +( -0.110723 0.000000 0.044496 0.000000 0.005310 0.000000 ) +( -0.110723 0.000000 0.044496 0.000000 -0.005310 0.000000 ) +( 0.110723 0.000000 -0.044496 0.000000 -0.005310 0.000000 ) +( 0.063904 0.000000 0.042543 0.000000 0.108440 0.000000 ) +( -0.063904 0.000000 -0.042543 0.000000 0.108440 0.000000 ) +( -0.063904 0.000000 -0.042543 0.000000 -0.108440 0.000000 ) +( 0.063904 0.000000 0.042543 0.000000 -0.108440 0.000000 ) +( -0.263506 0.000000 0.069960 0.000000 -0.160559 0.000000 ) +( 0.263506 0.000000 -0.069960 0.000000 -0.160559 0.000000 ) +( 0.263506 0.000000 -0.069960 0.000000 0.160559 0.000000 ) +( -0.263506 0.000000 0.069960 0.000000 0.160559 0.000000 ) +( -0.192102 0.000000 0.060055 0.000000 -0.101549 0.000000 ) +( 0.192102 0.000000 -0.060055 0.000000 -0.101549 0.000000 ) +( 0.192102 0.000000 -0.060055 0.000000 0.101549 0.000000 ) +( -0.192102 0.000000 0.060055 0.000000 0.101549 0.000000 ) +( 0.122585 0.000000 -0.062440 0.000000 -0.020612 0.000000 ) +( -0.122585 0.000000 0.062440 0.000000 -0.020612 0.000000 ) +( -0.122585 0.000000 0.062440 0.000000 0.020612 0.000000 ) +( 0.122585 0.000000 -0.062440 0.000000 0.020612 0.000000 ) +( 0.145252 0.000000 0.063171 0.000000 0.150695 0.000000 ) +( -0.145252 0.000000 -0.063171 0.000000 0.150695 0.000000 ) +( -0.145252 0.000000 -0.063171 0.000000 -0.150695 0.000000 ) +( 0.145252 0.000000 0.063171 0.000000 -0.150695 0.000000 ) + freq ( 55) = 63.82083241 [THz] = 2128.83382000 [cm-1] +( -0.060613 0.000000 -0.105069 0.000000 -0.119896 0.000000 ) +( -0.060613 0.000000 -0.105069 0.000000 0.119896 0.000000 ) +( -0.060613 0.000000 -0.105069 0.000000 -0.119896 0.000000 ) +( -0.060613 0.000000 -0.105069 0.000000 0.119896 0.000000 ) +( -0.013443 0.000000 0.021681 -0.000000 -0.207851 -0.000000 ) +( -0.013443 0.000000 0.021681 -0.000000 0.207851 -0.000000 ) +( -0.013443 0.000000 0.021681 -0.000000 -0.207851 -0.000000 ) +( -0.013443 0.000000 0.021681 -0.000000 0.207851 -0.000000 ) +( 0.260274 -0.000000 0.002866 -0.000000 0.155274 -0.000000 ) +( 0.260274 -0.000000 0.002866 -0.000000 -0.155274 -0.000000 ) +( 0.260274 -0.000000 0.002866 -0.000000 0.155274 -0.000000 ) +( 0.260274 0.000000 0.002866 -0.000000 -0.155274 -0.000000 ) +( 0.090185 -0.000000 0.015193 -0.000000 0.030229 -0.000000 ) +( 0.090185 -0.000000 0.015193 -0.000000 -0.030229 -0.000000 ) +( 0.090185 -0.000000 0.015193 -0.000000 0.030229 -0.000000 ) +( 0.090185 -0.000000 0.015193 -0.000000 -0.030229 -0.000000 ) +( -0.141762 0.000000 -0.041296 0.000000 0.156891 0.000000 ) +( -0.141762 0.000000 -0.041296 0.000000 -0.156891 0.000000 ) +( -0.141762 0.000000 -0.041296 0.000000 0.156891 0.000000 ) +( -0.141762 0.000000 -0.041296 0.000000 -0.156891 0.000000 ) +( -0.134641 0.000000 0.106625 -0.000000 -0.002471 -0.000000 ) +( -0.134641 0.000000 0.106625 -0.000000 0.002471 -0.000000 ) +( -0.134641 0.000000 0.106625 -0.000000 -0.002471 -0.000000 ) +( -0.134641 0.000000 0.106625 -0.000000 0.002471 -0.000000 ) + freq ( 56) = 64.12708205 [THz] = 2139.04920831 [cm-1] +( 0.208361 -0.000000 -0.112958 0.000000 -0.011289 0.000000 ) +( -0.208361 0.000000 0.112958 -0.000000 -0.011289 -0.000000 ) +( 0.208361 -0.000000 -0.112958 0.000000 -0.011289 0.000000 ) +( -0.208361 0.000000 0.112958 -0.000000 -0.011289 -0.000000 ) +( 0.208928 -0.000000 -0.173063 0.000000 0.007249 0.000000 ) +( -0.208928 0.000000 0.173063 -0.000000 0.007249 -0.000000 ) +( 0.208928 0.000000 -0.173063 0.000000 0.007249 0.000000 ) +( -0.208928 0.000000 0.173063 -0.000000 0.007249 -0.000000 ) +( -0.197765 0.000000 0.039513 -0.000000 -0.023446 -0.000000 ) +( 0.197765 -0.000000 -0.039513 0.000000 -0.023446 0.000000 ) +( -0.197765 0.000000 0.039513 -0.000000 -0.023446 -0.000000 ) +( 0.197765 -0.000000 -0.039513 0.000000 -0.023446 0.000000 ) +( -0.207091 0.000000 0.079849 -0.000000 -0.045876 -0.000000 ) +( 0.207091 -0.000000 -0.079849 0.000000 -0.045876 0.000000 ) +( -0.207091 0.000000 0.079849 -0.000000 -0.045876 -0.000000 ) +( 0.207091 -0.000000 -0.079849 0.000000 -0.045876 0.000000 ) +( 0.003503 -0.000000 0.028500 -0.000000 -0.071389 -0.000000 ) +( -0.003503 0.000000 -0.028500 0.000000 -0.071389 0.000000 ) +( 0.003503 -0.000000 0.028500 -0.000000 -0.071389 -0.000000 ) +( -0.003503 0.000000 -0.028500 0.000000 -0.071389 0.000000 ) +( 0.024079 -0.000000 0.001190 -0.000000 0.144751 -0.000000 ) +( -0.024079 0.000000 -0.001190 0.000000 0.144751 0.000000 ) +( 0.024079 -0.000000 0.001190 -0.000000 0.144751 -0.000000 ) +( -0.024079 0.000000 -0.001190 0.000000 0.144751 0.000000 ) + freq ( 57) = 64.35101067 [THz] = 2146.51866295 [cm-1] +( -0.035125 0.000000 -0.053676 0.000000 -0.067239 0.000000 ) +( -0.035125 0.000000 -0.053676 0.000000 0.067239 0.000000 ) +( 0.035125 0.000000 0.053676 0.000000 0.067239 0.000000 ) +( 0.035125 0.000000 0.053676 0.000000 -0.067239 0.000000 ) +( -0.244476 0.000000 0.042321 0.000000 0.052450 0.000000 ) +( -0.244476 0.000000 0.042321 0.000000 -0.052450 0.000000 ) +( 0.244476 0.000000 -0.042321 0.000000 -0.052450 0.000000 ) +( 0.244476 0.000000 -0.042321 0.000000 0.052450 0.000000 ) +( 0.034843 0.000000 -0.069108 0.000000 -0.189910 0.000000 ) +( 0.034843 0.000000 -0.069108 0.000000 0.189910 0.000000 ) +( -0.034843 0.000000 0.069108 0.000000 0.189910 0.000000 ) +( -0.034843 0.000000 0.069108 0.000000 -0.189910 0.000000 ) +( 0.047051 0.000000 0.104127 0.000000 -0.159572 0.000000 ) +( 0.047051 0.000000 0.104127 0.000000 0.159572 0.000000 ) +( -0.047051 0.000000 -0.104127 0.000000 0.159572 0.000000 ) +( -0.047051 0.000000 -0.104127 0.000000 -0.159572 0.000000 ) +( 0.096809 0.000000 -0.026515 0.000000 0.236790 0.000000 ) +( 0.096809 0.000000 -0.026515 0.000000 -0.236790 0.000000 ) +( -0.096809 0.000000 0.026515 0.000000 -0.236790 0.000000 ) +( -0.096809 0.000000 0.026515 0.000000 0.236790 0.000000 ) +( 0.074711 0.000000 -0.089316 0.000000 0.129517 0.000000 ) +( 0.074711 0.000000 -0.089316 0.000000 -0.129517 0.000000 ) +( -0.074711 0.000000 0.089316 0.000000 -0.129517 0.000000 ) +( -0.074711 0.000000 0.089316 0.000000 0.129517 0.000000 ) + freq ( 58) = 66.32211930 [THz] = 2212.26776946 [cm-1] +( 0.064385 0.000000 -0.054067 0.000000 0.088090 0.000000 ) +( -0.064385 0.000000 0.054067 0.000000 0.088090 0.000000 ) +( -0.064385 0.000000 0.054067 0.000000 -0.088090 0.000000 ) +( 0.064385 0.000000 -0.054067 0.000000 -0.088090 0.000000 ) +( 0.259520 0.000000 -0.004285 0.000000 -0.014993 0.000000 ) +( -0.259520 0.000000 0.004285 0.000000 -0.014993 0.000000 ) +( -0.259520 0.000000 0.004285 0.000000 0.014993 0.000000 ) +( 0.259520 0.000000 -0.004285 0.000000 0.014993 0.000000 ) +( -0.119140 0.000000 0.018502 0.000000 0.169660 0.000000 ) +( 0.119140 0.000000 -0.018502 0.000000 0.169660 0.000000 ) +( 0.119140 0.000000 -0.018502 0.000000 -0.169660 0.000000 ) +( -0.119140 0.000000 0.018502 0.000000 -0.169660 0.000000 ) +( -0.065075 0.000000 0.004882 0.000000 0.141636 0.000000 ) +( 0.065075 0.000000 -0.004882 0.000000 0.141636 0.000000 ) +( 0.065075 0.000000 -0.004882 0.000000 -0.141636 0.000000 ) +( -0.065075 0.000000 0.004882 0.000000 -0.141636 0.000000 ) +( -0.096689 0.000000 0.021267 0.000000 -0.280215 0.000000 ) +( 0.096689 0.000000 -0.021267 0.000000 -0.280215 0.000000 ) +( 0.096689 0.000000 -0.021267 0.000000 0.280215 0.000000 ) +( -0.096689 0.000000 0.021267 0.000000 0.280215 0.000000 ) +( -0.039301 0.000000 -0.006926 0.000000 -0.100116 0.000000 ) +( 0.039301 0.000000 0.006926 0.000000 -0.100116 0.000000 ) +( 0.039301 0.000000 0.006926 0.000000 0.100116 0.000000 ) +( -0.039301 0.000000 -0.006926 0.000000 0.100116 0.000000 ) + freq ( 59) = 66.47207297 [THz] = 2217.26968569 [cm-1] +( -0.054369 0.000000 0.048645 0.000000 0.132215 0.000000 ) +( 0.054369 0.000000 -0.048645 0.000000 0.132215 0.000000 ) +( -0.054369 0.000000 0.048645 0.000000 0.132215 0.000000 ) +( 0.054369 0.000000 -0.048645 0.000000 0.132215 0.000000 ) +( -0.111356 0.000000 0.027964 0.000000 0.254980 0.000000 ) +( 0.111356 0.000000 -0.027964 0.000000 0.254980 0.000000 ) +( -0.111356 0.000000 0.027964 0.000000 0.254980 0.000000 ) +( 0.111356 0.000000 -0.027964 0.000000 0.254980 0.000000 ) +( -0.199683 0.000000 -0.009939 0.000000 -0.167385 0.000000 ) +( 0.199683 0.000000 0.009939 0.000000 -0.167385 0.000000 ) +( -0.199683 0.000000 -0.009939 0.000000 -0.167385 0.000000 ) +( 0.199683 0.000000 0.009939 0.000000 -0.167385 0.000000 ) +( 0.021399 0.000000 -0.022238 0.000000 -0.047012 0.000000 ) +( -0.021399 0.000000 0.022238 0.000000 -0.047012 0.000000 ) +( 0.021399 0.000000 -0.022238 0.000000 -0.047012 0.000000 ) +( -0.021399 0.000000 0.022238 0.000000 -0.047012 0.000000 ) +( 0.171858 0.000000 -0.045609 0.000000 -0.126269 0.000000 ) +( -0.171858 0.000000 0.045609 0.000000 -0.126269 0.000000 ) +( 0.171858 0.000000 -0.045609 0.000000 -0.126269 0.000000 ) +( -0.171858 0.000000 0.045609 0.000000 -0.126269 0.000000 ) +( 0.167412 0.000000 -0.009855 0.000000 -0.046529 0.000000 ) +( -0.167412 0.000000 0.009855 0.000000 -0.046529 0.000000 ) +( 0.167412 0.000000 -0.009855 0.000000 -0.046529 0.000000 ) +( -0.167412 0.000000 0.009855 0.000000 -0.046529 0.000000 ) + freq ( 60) = 74.12447177 [THz] = 2472.52623349 [cm-1] +( 0.009672 0.000000 0.221809 0.000000 -0.016234 0.000000 ) +( -0.009672 0.000000 -0.221809 0.000000 -0.016234 0.000000 ) +( -0.009672 0.000000 -0.221809 0.000000 0.016234 0.000000 ) +( 0.009672 0.000000 0.221809 0.000000 0.016234 0.000000 ) +( 0.006026 0.000000 0.203599 0.000000 -0.037002 0.000000 ) +( -0.006026 0.000000 -0.203599 0.000000 -0.037002 0.000000 ) +( -0.006026 0.000000 -0.203599 0.000000 0.037002 0.000000 ) +( 0.006026 0.000000 0.203599 0.000000 0.037002 0.000000 ) +( 0.026225 0.000000 0.203728 0.000000 0.022453 0.000000 ) +( -0.026225 0.000000 -0.203728 0.000000 0.022453 0.000000 ) +( -0.026225 0.000000 -0.203728 0.000000 -0.022453 0.000000 ) +( 0.026225 0.000000 0.203728 0.000000 -0.022453 0.000000 ) +( -0.007326 0.000000 0.188594 0.000000 0.017928 0.000000 ) +( 0.007326 0.000000 -0.188594 0.000000 0.017928 0.000000 ) +( 0.007326 0.000000 -0.188594 0.000000 -0.017928 0.000000 ) +( -0.007326 0.000000 0.188594 0.000000 -0.017928 0.000000 ) +( -0.047910 0.000000 0.207680 0.000000 0.019976 0.000000 ) +( 0.047910 0.000000 -0.207680 0.000000 0.019976 0.000000 ) +( 0.047910 0.000000 -0.207680 0.000000 -0.019976 0.000000 ) +( -0.047910 0.000000 0.207680 0.000000 -0.019976 0.000000 ) +( -0.017817 0.000000 0.181096 0.000000 -0.002648 0.000000 ) +( 0.017817 0.000000 -0.181096 0.000000 -0.002648 0.000000 ) +( 0.017817 0.000000 -0.181096 0.000000 0.002648 0.000000 ) +( -0.017817 0.000000 0.181096 0.000000 0.002648 0.000000 ) + freq ( 61) = 95.03858225 [THz] = 3170.14586695 [cm-1] +( -0.101472 0.000000 -0.008996 0.000000 -0.098553 0.000000 ) +( 0.101472 -0.000000 0.008996 -0.000000 -0.098553 -0.000000 ) +( 0.101472 -0.000000 0.008996 -0.000000 0.098553 -0.000000 ) +( -0.101472 0.000000 -0.008996 0.000000 0.098553 0.000000 ) +( 0.092201 -0.000000 0.000665 -0.000000 0.186595 -0.000000 ) +( -0.092201 0.000000 -0.000665 0.000000 0.186595 0.000000 ) +( -0.092201 0.000000 -0.000665 0.000000 -0.186595 0.000000 ) +( 0.092201 -0.000000 0.000665 -0.000000 -0.186595 -0.000000 ) +( 0.099158 -0.000000 -0.063311 0.000000 -0.173743 0.000000 ) +( -0.099158 0.000000 0.063311 -0.000000 -0.173743 -0.000000 ) +( -0.099158 0.000000 0.063311 -0.000000 0.173743 -0.000000 ) +( 0.099158 -0.000000 -0.063311 0.000000 0.173743 0.000000 ) +( -0.047292 0.000000 -0.022283 0.000000 0.098099 0.000000 ) +( 0.047292 -0.000000 0.022283 -0.000000 0.098099 -0.000000 ) +( 0.047292 -0.000000 0.022283 -0.000000 -0.098099 -0.000000 ) +( -0.047292 0.000000 -0.022283 0.000000 -0.098099 0.000000 ) +( -0.276917 0.000000 0.056301 -0.000000 0.012256 -0.000000 ) +( 0.276917 -0.000000 -0.056301 0.000000 0.012256 0.000000 ) +( 0.276917 0.000000 -0.056301 0.000000 -0.012256 0.000000 ) +( -0.276917 0.000000 0.056301 -0.000000 -0.012256 -0.000000 ) +( 0.220965 -0.000000 0.013960 -0.000000 -0.034392 -0.000000 ) +( -0.220965 0.000000 -0.013960 0.000000 -0.034392 0.000000 ) +( -0.220965 0.000000 -0.013960 0.000000 0.034392 0.000000 ) +( 0.220965 -0.000000 0.013960 -0.000000 0.034392 -0.000000 ) + freq ( 62) = 101.21494444 [THz] = 3376.16713334 [cm-1] +( 0.114933 0.000000 0.014405 0.000000 0.156036 0.000000 ) +( -0.114933 0.000000 -0.014405 0.000000 0.156036 0.000000 ) +( 0.114933 0.000000 0.014405 0.000000 0.156036 0.000000 ) +( -0.114933 0.000000 -0.014405 0.000000 0.156036 0.000000 ) +( -0.135292 0.000000 0.026076 0.000000 -0.210513 0.000000 ) +( 0.135292 0.000000 -0.026076 0.000000 -0.210513 0.000000 ) +( -0.135292 0.000000 0.026076 0.000000 -0.210513 0.000000 ) +( 0.135292 0.000000 -0.026076 0.000000 -0.210513 0.000000 ) +( -0.125873 0.000000 -0.013523 0.000000 0.169503 0.000000 ) +( 0.125873 0.000000 0.013523 0.000000 0.169503 0.000000 ) +( -0.125873 0.000000 -0.013523 0.000000 0.169503 0.000000 ) +( 0.125873 0.000000 0.013523 0.000000 0.169503 0.000000 ) +( 0.052005 0.000000 -0.020745 0.000000 -0.125303 0.000000 ) +( -0.052005 0.000000 0.020745 0.000000 -0.125303 0.000000 ) +( 0.052005 0.000000 -0.020745 0.000000 -0.125303 0.000000 ) +( -0.052005 0.000000 0.020745 0.000000 -0.125303 0.000000 ) +( 0.245802 0.000000 -0.031813 0.000000 -0.010519 0.000000 ) +( -0.245802 0.000000 0.031813 0.000000 -0.010519 0.000000 ) +( 0.245802 0.000000 -0.031813 0.000000 -0.010519 0.000000 ) +( -0.245802 0.000000 0.031813 0.000000 -0.010519 0.000000 ) +( -0.152837 0.000000 0.003023 0.000000 0.020796 0.000000 ) +( 0.152837 0.000000 -0.003023 0.000000 0.020796 0.000000 ) +( -0.152837 0.000000 0.003023 0.000000 0.020796 0.000000 ) +( 0.152837 0.000000 -0.003023 0.000000 0.020796 0.000000 ) + freq ( 63) = 104.24354789 [THz] = 3477.19047012 [cm-1] +( -0.187005 0.000000 -0.002232 0.000000 -0.262730 0.000000 ) +( -0.187005 0.000000 -0.002232 0.000000 0.262730 0.000000 ) +( -0.187005 0.000000 -0.002232 0.000000 -0.262730 0.000000 ) +( -0.187005 0.000000 -0.002232 0.000000 0.262730 0.000000 ) +( 0.194242 0.000000 0.004548 0.000000 0.267660 0.000000 ) +( 0.194242 0.000000 0.004548 0.000000 -0.267660 0.000000 ) +( 0.194242 0.000000 0.004548 0.000000 0.267660 0.000000 ) +( 0.194242 0.000000 0.004548 0.000000 -0.267660 0.000000 ) +( 0.028265 0.000000 0.009739 0.000000 -0.021117 0.000000 ) +( 0.028265 0.000000 0.009739 0.000000 0.021117 0.000000 ) +( 0.028265 0.000000 0.009739 0.000000 -0.021117 0.000000 ) +( 0.028265 0.000000 0.009739 0.000000 0.021117 0.000000 ) +( 0.028643 0.000000 0.013217 0.000000 0.027470 0.000000 ) +( 0.028643 0.000000 0.013217 0.000000 -0.027470 0.000000 ) +( 0.028643 0.000000 0.013217 0.000000 0.027470 0.000000 ) +( 0.028643 0.000000 0.013217 0.000000 -0.027470 0.000000 ) +( 0.090748 0.000000 -0.028199 0.000000 -0.013173 0.000000 ) +( 0.090748 0.000000 -0.028199 0.000000 0.013173 0.000000 ) +( 0.090748 0.000000 -0.028199 0.000000 -0.013173 0.000000 ) +( 0.090748 0.000000 -0.028199 0.000000 0.013173 0.000000 ) +( -0.154891 0.000000 0.002926 0.000000 0.017653 0.000000 ) +( -0.154891 0.000000 0.002926 0.000000 -0.017653 0.000000 ) +( -0.154891 0.000000 0.002926 0.000000 0.017653 0.000000 ) +( -0.154891 0.000000 0.002926 0.000000 -0.017653 0.000000 ) + freq ( 64) = 106.57960446 [THz] = 3555.11292969 [cm-1] +( -0.058893 0.000000 -0.010673 0.000000 -0.038469 0.000000 ) +( -0.058893 0.000000 -0.010673 0.000000 0.038469 0.000000 ) +( 0.058893 -0.000000 0.010673 -0.000000 0.038469 -0.000000 ) +( 0.058893 -0.000000 0.010673 -0.000000 -0.038469 -0.000000 ) +( 0.018966 -0.000000 -0.007807 0.000000 0.019993 0.000000 ) +( 0.018966 -0.000000 -0.007807 0.000000 -0.019993 0.000000 ) +( -0.018966 0.000000 0.007807 -0.000000 -0.019993 -0.000000 ) +( -0.018966 0.000000 0.007807 -0.000000 0.019993 -0.000000 ) +( -0.163466 0.000000 0.021864 -0.000000 0.296885 -0.000000 ) +( -0.163466 0.000000 0.021864 -0.000000 -0.296885 -0.000000 ) +( 0.163466 -0.000000 -0.021864 0.000000 -0.296885 0.000000 ) +( 0.163466 -0.000000 -0.021864 0.000000 0.296885 0.000000 ) +( 0.158684 -0.000000 -0.013565 0.000000 -0.293209 0.000000 ) +( 0.158684 -0.000000 -0.013565 0.000000 0.293209 0.000000 ) +( -0.158684 0.000000 0.013565 -0.000000 0.293209 -0.000000 ) +( -0.158684 0.000000 0.013565 -0.000000 -0.293209 -0.000000 ) +( -0.073699 0.000000 0.001261 -0.000000 0.017696 -0.000000 ) +( -0.073699 0.000000 0.001261 -0.000000 -0.017696 -0.000000 ) +( 0.073699 -0.000000 -0.001261 0.000000 -0.017696 0.000000 ) +( 0.073699 -0.000000 -0.001261 0.000000 0.017696 0.000000 ) +( 0.102964 -0.000000 -0.005597 0.000000 0.032600 0.000000 ) +( 0.102964 -0.000000 -0.005597 0.000000 -0.032600 0.000000 ) +( -0.102964 0.000000 0.005597 -0.000000 -0.032600 -0.000000 ) +( -0.102964 0.000000 0.005597 -0.000000 0.032600 -0.000000 ) + freq ( 65) = 109.26296088 [THz] = 3644.62006517 [cm-1] +( -0.170059 0.000000 0.009717 -0.000000 -0.257307 -0.000000 ) +( -0.170059 0.000000 0.009717 -0.000000 0.257307 -0.000000 ) +( 0.170059 -0.000000 -0.009717 0.000000 0.257307 0.000000 ) +( 0.170059 -0.000000 -0.009717 0.000000 -0.257307 0.000000 ) +( 0.173112 -0.000000 0.008623 -0.000000 0.261249 -0.000000 ) +( 0.173112 -0.000000 0.008623 -0.000000 -0.261249 -0.000000 ) +( -0.173112 0.000000 -0.008623 0.000000 -0.261249 0.000000 ) +( -0.173112 0.000000 -0.008623 0.000000 0.261249 0.000000 ) +( 0.005413 -0.000000 -0.006443 0.000000 -0.005748 0.000000 ) +( 0.005413 -0.000000 -0.006443 0.000000 0.005748 0.000000 ) +( -0.005413 0.000000 0.006443 -0.000000 0.005748 -0.000000 ) +( -0.005413 0.000000 0.006443 -0.000000 -0.005748 -0.000000 ) +( 0.031751 -0.000000 0.008484 -0.000000 0.008131 -0.000000 ) +( 0.031751 -0.000000 0.008484 -0.000000 -0.008131 -0.000000 ) +( -0.031751 0.000000 -0.008484 0.000000 -0.008131 0.000000 ) +( -0.031751 0.000000 -0.008484 0.000000 0.008131 0.000000 ) +( 0.147515 -0.000000 -0.018631 0.000000 -0.010620 0.000000 ) +( 0.147515 -0.000000 -0.018631 0.000000 0.010620 0.000000 ) +( -0.147515 0.000000 0.018631 -0.000000 0.010620 -0.000000 ) +( -0.147515 0.000000 0.018631 -0.000000 -0.010620 -0.000000 ) +( -0.176486 0.000000 0.017038 -0.000000 0.039712 -0.000000 ) +( -0.176486 0.000000 0.017038 -0.000000 -0.039712 -0.000000 ) +( 0.176486 -0.000000 -0.017038 0.000000 -0.039712 0.000000 ) +( 0.176486 -0.000000 -0.017038 0.000000 0.039712 0.000000 ) + freq ( 66) = 109.73247380 [THz] = 3660.28133040 [cm-1] +( 0.003298 -0.000000 0.003426 -0.000000 -0.010126 -0.000000 ) +( 0.003298 -0.000000 0.003426 -0.000000 0.010126 -0.000000 ) +( 0.003298 -0.000000 0.003426 -0.000000 -0.010126 -0.000000 ) +( 0.003298 -0.000000 0.003426 -0.000000 0.010126 -0.000000 ) +( -0.009590 0.000000 0.002073 -0.000000 -0.056966 -0.000000 ) +( -0.009590 0.000000 0.002073 -0.000000 0.056966 -0.000000 ) +( -0.009590 0.000000 0.002073 -0.000000 -0.056966 -0.000000 ) +( -0.009590 0.000000 0.002073 -0.000000 0.056966 -0.000000 ) +( -0.190988 0.000000 -0.016248 0.000000 0.298962 0.000000 ) +( -0.190988 0.000000 -0.016248 0.000000 -0.298962 0.000000 ) +( -0.190988 0.000000 -0.016248 0.000000 0.298962 0.000000 ) +( -0.190988 0.000000 -0.016248 0.000000 -0.298962 0.000000 ) +( 0.124369 -0.000000 -0.041561 0.000000 -0.246605 0.000000 ) +( 0.124369 -0.000000 -0.041561 0.000000 0.246605 0.000000 ) +( 0.124369 -0.000000 -0.041561 0.000000 -0.246605 0.000000 ) +( 0.124369 -0.000000 -0.041561 0.000000 0.246605 0.000000 ) +( 0.171434 -0.000000 0.036065 -0.000000 -0.010001 -0.000000 ) +( 0.171434 -0.000000 0.036065 -0.000000 0.010001 -0.000000 ) +( 0.171434 -0.000000 0.036065 -0.000000 -0.010001 -0.000000 ) +( 0.171434 -0.000000 0.036065 -0.000000 0.010001 -0.000000 ) +( -0.098524 0.000000 0.016245 -0.000000 0.040549 -0.000000 ) +( -0.098524 0.000000 0.016245 -0.000000 -0.040549 -0.000000 ) +( -0.098524 0.000000 0.016245 -0.000000 0.040549 -0.000000 ) +( -0.098524 0.000000 0.016245 -0.000000 -0.040549 -0.000000 ) + freq ( 67) = 110.20328582 [THz] = 3675.98592880 [cm-1] +( 0.126863 0.000000 -0.009059 0.000000 0.123486 0.000000 ) +( -0.126863 0.000000 0.009059 0.000000 0.123486 0.000000 ) +( -0.126863 0.000000 0.009059 0.000000 -0.123486 0.000000 ) +( 0.126863 0.000000 -0.009059 0.000000 -0.123486 0.000000 ) +( -0.060885 0.000000 0.009113 0.000000 -0.110910 0.000000 ) +( 0.060885 0.000000 -0.009113 0.000000 -0.110910 0.000000 ) +( 0.060885 0.000000 -0.009113 0.000000 0.110910 0.000000 ) +( -0.060885 0.000000 0.009113 0.000000 0.110910 0.000000 ) +( 0.128880 0.000000 -0.013087 0.000000 -0.261458 0.000000 ) +( -0.128880 0.000000 0.013087 0.000000 -0.261458 0.000000 ) +( -0.128880 0.000000 0.013087 0.000000 0.261458 0.000000 ) +( 0.128880 0.000000 -0.013087 0.000000 0.261458 0.000000 ) +( -0.155521 0.000000 0.003615 0.000000 0.275650 0.000000 ) +( 0.155521 0.000000 -0.003615 0.000000 0.275650 0.000000 ) +( 0.155521 0.000000 -0.003615 0.000000 -0.275650 0.000000 ) +( -0.155521 0.000000 0.003615 0.000000 -0.275650 0.000000 ) +( 0.083567 0.000000 -0.001236 0.000000 -0.021278 0.000000 ) +( -0.083567 0.000000 0.001236 0.000000 -0.021278 0.000000 ) +( -0.083567 0.000000 0.001236 0.000000 0.021278 0.000000 ) +( 0.083567 0.000000 -0.001236 0.000000 0.021278 0.000000 ) +( -0.089915 0.000000 -0.007914 0.000000 -0.039677 0.000000 ) +( 0.089915 0.000000 0.007914 0.000000 -0.039677 0.000000 ) +( 0.089915 0.000000 0.007914 0.000000 0.039677 0.000000 ) +( -0.089915 0.000000 -0.007914 0.000000 0.039677 0.000000 ) + freq ( 68) = 110.38050213 [THz] = 3681.89722860 [cm-1] +( 0.139362 -0.000000 0.016369 -0.000000 0.193583 -0.000000 ) +( -0.139362 0.000000 -0.016369 0.000000 0.193583 0.000000 ) +( 0.139362 -0.000000 0.016369 -0.000000 0.193583 -0.000000 ) +( -0.139362 0.000000 -0.016369 0.000000 0.193583 0.000000 ) +( -0.110110 0.000000 -0.012590 0.000000 -0.147360 0.000000 ) +( 0.110110 -0.000000 0.012590 -0.000000 -0.147360 -0.000000 ) +( -0.110110 0.000000 -0.012590 0.000000 -0.147360 0.000000 ) +( 0.110110 -0.000000 0.012590 -0.000000 -0.147360 -0.000000 ) +( 0.118921 -0.000000 -0.026156 0.000000 -0.242230 0.000000 ) +( -0.118921 0.000000 0.026156 -0.000000 -0.242230 -0.000000 ) +( 0.118921 -0.000000 -0.026156 0.000000 -0.242230 0.000000 ) +( -0.118921 0.000000 0.026156 -0.000000 -0.242230 -0.000000 ) +( -0.146529 0.000000 0.021084 -0.000000 0.247732 -0.000000 ) +( 0.146529 -0.000000 -0.021084 0.000000 0.247732 0.000000 ) +( -0.146529 0.000000 0.021084 -0.000000 0.247732 -0.000000 ) +( 0.146529 -0.000000 -0.021084 0.000000 0.247732 0.000000 ) +( 0.010413 -0.000000 -0.009608 0.000000 -0.013341 0.000000 ) +( -0.010413 0.000000 0.009608 -0.000000 -0.013341 -0.000000 ) +( 0.010413 -0.000000 -0.009608 0.000000 -0.013341 0.000000 ) +( -0.010413 0.000000 0.009608 -0.000000 -0.013341 -0.000000 ) +( -0.003109 0.000000 0.013733 -0.000000 -0.038383 -0.000000 ) +( 0.003109 -0.000000 -0.013733 0.000000 -0.038383 0.000000 ) +( -0.003109 0.000000 0.013733 -0.000000 -0.038383 -0.000000 ) +( 0.003109 -0.000000 -0.013733 0.000000 -0.038383 0.000000 ) + freq ( 69) = 113.49648204 [THz] = 3785.83513052 [cm-1] +( 0.098943 0.000000 -0.004693 0.000000 0.077273 0.000000 ) +( 0.098943 0.000000 -0.004693 0.000000 -0.077273 0.000000 ) +( -0.098943 0.000000 0.004693 0.000000 -0.077273 0.000000 ) +( -0.098943 0.000000 0.004693 0.000000 0.077273 0.000000 ) +( -0.088618 0.000000 -0.024679 0.000000 -0.165706 0.000000 ) +( -0.088618 0.000000 -0.024679 0.000000 0.165706 0.000000 ) +( 0.088618 0.000000 0.024679 0.000000 0.165706 0.000000 ) +( 0.088618 0.000000 0.024679 0.000000 -0.165706 0.000000 ) +( -0.071211 0.000000 0.019153 0.000000 0.111992 0.000000 ) +( -0.071211 0.000000 0.019153 0.000000 -0.111992 0.000000 ) +( 0.071211 0.000000 -0.019153 0.000000 -0.111992 0.000000 ) +( 0.071211 0.000000 -0.019153 0.000000 0.111992 0.000000 ) +( 0.022050 0.000000 0.007113 0.000000 -0.052507 0.000000 ) +( 0.022050 0.000000 0.007113 0.000000 0.052507 0.000000 ) +( -0.022050 0.000000 -0.007113 0.000000 0.052507 0.000000 ) +( -0.022050 0.000000 -0.007113 0.000000 -0.052507 0.000000 ) +( 0.320102 0.000000 0.008956 0.000000 -0.004904 0.000000 ) +( 0.320102 0.000000 0.008956 0.000000 0.004904 0.000000 ) +( -0.320102 0.000000 -0.008956 0.000000 0.004904 0.000000 ) +( -0.320102 0.000000 -0.008956 0.000000 -0.004904 0.000000 ) +( -0.269929 0.000000 0.024003 0.000000 0.031863 0.000000 ) +( -0.269929 0.000000 0.024003 0.000000 -0.031863 0.000000 ) +( 0.269929 0.000000 -0.024003 0.000000 -0.031863 0.000000 ) +( 0.269929 0.000000 -0.024003 0.000000 0.031863 0.000000 ) + freq ( 70) = 114.07071926 [THz] = 3804.98962235 [cm-1] +( 0.068278 -0.000000 0.005064 -0.000000 0.152802 -0.000000 ) +( -0.068278 0.000000 -0.005064 0.000000 0.152802 0.000000 ) +( 0.068278 -0.000000 0.005064 -0.000000 0.152802 -0.000000 ) +( -0.068278 0.000000 -0.005064 0.000000 0.152802 0.000000 ) +( -0.104628 0.000000 -0.007796 0.000000 -0.127218 0.000000 ) +( 0.104628 -0.000000 0.007796 -0.000000 -0.127218 -0.000000 ) +( -0.104628 0.000000 -0.007796 0.000000 -0.127218 0.000000 ) +( 0.104628 -0.000000 0.007796 -0.000000 -0.127218 -0.000000 ) +( -0.057565 0.000000 0.003377 -0.000000 0.091165 -0.000000 ) +( 0.057565 -0.000000 -0.003377 0.000000 0.091165 0.000000 ) +( -0.057565 0.000000 0.003377 -0.000000 0.091165 -0.000000 ) +( 0.057565 -0.000000 -0.003377 0.000000 0.091165 0.000000 ) +( 0.030351 -0.000000 -0.016828 0.000000 -0.129682 0.000000 ) +( -0.030351 0.000000 0.016828 -0.000000 -0.129682 -0.000000 ) +( 0.030351 -0.000000 -0.016828 0.000000 -0.129682 0.000000 ) +( -0.030351 0.000000 0.016828 -0.000000 -0.129682 -0.000000 ) +( -0.268261 0.000000 0.012352 -0.000000 0.031319 -0.000000 ) +( 0.268261 -0.000000 -0.012352 0.000000 0.031319 0.000000 ) +( -0.268261 0.000000 0.012352 -0.000000 0.031319 -0.000000 ) +( 0.268261 -0.000000 -0.012352 0.000000 0.031319 0.000000 ) +( 0.302775 0.000000 -0.002385 0.000000 -0.018386 0.000000 ) +( -0.302775 0.000000 0.002385 -0.000000 -0.018386 -0.000000 ) +( 0.302775 -0.000000 -0.002385 0.000000 -0.018386 0.000000 ) +( -0.302775 0.000000 0.002385 -0.000000 -0.018386 -0.000000 ) + freq ( 71) = 114.51437281 [THz] = 3819.78831202 [cm-1] +( 0.092261 -0.000000 0.015245 -0.000000 0.058815 -0.000000 ) +( 0.092261 -0.000000 0.015245 -0.000000 -0.058815 -0.000000 ) +( 0.092261 -0.000000 0.015245 -0.000000 0.058815 -0.000000 ) +( 0.092261 -0.000000 0.015245 -0.000000 -0.058815 -0.000000 ) +( -0.053627 0.000000 -0.015693 0.000000 -0.124834 0.000000 ) +( -0.053627 0.000000 -0.015693 0.000000 0.124834 0.000000 ) +( -0.053627 0.000000 -0.015693 0.000000 -0.124834 0.000000 ) +( -0.053627 0.000000 -0.015693 0.000000 0.124834 0.000000 ) +( 0.041501 -0.000000 -0.041864 0.000000 -0.103793 0.000000 ) +( 0.041501 -0.000000 -0.041864 0.000000 0.103793 0.000000 ) +( 0.041501 -0.000000 -0.041864 0.000000 -0.103793 0.000000 ) +( 0.041501 -0.000000 -0.041864 0.000000 0.103793 0.000000 ) +( -0.092925 0.000000 0.009860 -0.000000 0.153504 -0.000000 ) +( -0.092925 0.000000 0.009860 -0.000000 -0.153504 -0.000000 ) +( -0.092925 0.000000 0.009860 -0.000000 0.153504 -0.000000 ) +( -0.092925 0.000000 0.009860 -0.000000 -0.153504 -0.000000 ) +( 0.298665 -0.000000 -0.000060 0.000000 -0.016796 0.000000 ) +( 0.298665 0.000000 -0.000060 0.000000 0.016796 0.000000 ) +( 0.298665 -0.000000 -0.000060 0.000000 -0.016796 0.000000 ) +( 0.298665 -0.000000 -0.000060 0.000000 0.016796 0.000000 ) +( -0.285874 0.000000 0.032511 -0.000000 0.016843 -0.000000 ) +( -0.285874 0.000000 0.032511 -0.000000 -0.016843 -0.000000 ) +( -0.285874 0.000000 0.032511 -0.000000 0.016843 -0.000000 ) +( -0.285874 0.000000 0.032511 -0.000000 -0.016843 -0.000000 ) + freq ( 72) = 114.65001805 [THz] = 3824.31295007 [cm-1] +( 0.125133 0.000000 0.005881 0.000000 0.226705 0.000000 ) +( -0.125133 0.000000 -0.005881 0.000000 0.226705 0.000000 ) +( -0.125133 0.000000 -0.005881 0.000000 -0.226705 0.000000 ) +( 0.125133 0.000000 0.005881 0.000000 -0.226705 0.000000 ) +( -0.146720 0.000000 -0.023337 0.000000 -0.220923 0.000000 ) +( 0.146720 0.000000 0.023337 0.000000 -0.220923 0.000000 ) +( 0.146720 0.000000 0.023337 0.000000 0.220923 0.000000 ) +( -0.146720 0.000000 -0.023337 0.000000 0.220923 0.000000 ) +( -0.038441 0.000000 -0.001762 0.000000 0.050312 0.000000 ) +( 0.038441 0.000000 0.001762 0.000000 0.050312 0.000000 ) +( 0.038441 0.000000 0.001762 0.000000 -0.050312 0.000000 ) +( -0.038441 0.000000 -0.001762 0.000000 -0.050312 0.000000 ) +( -0.011507 0.000000 -0.002187 0.000000 -0.081015 0.000000 ) +( 0.011507 0.000000 0.002187 0.000000 -0.081015 0.000000 ) +( 0.011507 0.000000 0.002187 0.000000 0.081015 0.000000 ) +( -0.011507 0.000000 -0.002187 0.000000 0.081015 0.000000 ) +( -0.201711 0.000000 -0.013947 0.000000 0.025099 0.000000 ) +( 0.201711 0.000000 0.013947 0.000000 0.025099 0.000000 ) +( 0.201711 0.000000 0.013947 0.000000 -0.025099 0.000000 ) +( -0.201711 0.000000 -0.013947 0.000000 -0.025099 0.000000 ) +( 0.243469 0.000000 -0.012908 0.000000 -0.019122 0.000000 ) +( -0.243469 0.000000 0.012908 0.000000 -0.019122 0.000000 ) +( -0.243469 0.000000 0.012908 0.000000 0.019122 0.000000 ) +( 0.243469 0.000000 -0.012908 0.000000 0.019122 0.000000 ) +*************************************************************************** diff --git a/tests/aiida_ensemble/dyn2 b/tests/aiida_ensemble/dyn2 new file mode 100644 index 00000000..5796261e --- /dev/null +++ b/tests/aiida_ensemble/dyn2 @@ -0,0 +1,6457 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 24 0 5.36307068 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 +Basis vectors + 0.49334568 0.01129550 -0.85311514 + -0.03458521 1.75181777 0.00000000 + 0.49334568 0.01129550 0.85311514 + 1 'H ' 918.73579607 + 1 1 0.5519365595 0.2313707631 -0.1692669144 + 2 1 0.4174621950 0.6671291184 -0.1692669144 + 3 1 0.4001695915 1.5430380039 0.1692669144 + 4 1 0.5346439560 1.1072796486 0.1692669144 + 5 1 0.6981106437 0.2360660957 0.0464225528 + 6 1 0.2712881108 0.6624337858 0.0464225528 + 7 1 0.2539955073 1.5383426713 -0.0464225528 + 8 1 0.6808180402 1.1119749812 -0.0464225528 + 9 1 0.6732076478 0.2102400630 0.5104913056 + 10 1 0.2961911067 0.6882598185 0.5104913056 + 11 1 0.2788985032 1.5641687040 -0.5104913056 + 12 1 0.6559150443 1.0861489485 -0.5104913056 + 13 1 0.0576044735 0.2147663837 -0.1115184507 + 14 1 0.9117942810 0.6837334978 -0.1115184507 + 15 1 0.8945016775 1.5596423833 0.1115184507 + 16 1 0.0403118700 1.0906752692 0.1115184507 + 17 1 1.0881087549 0.2679292681 0.2995449619 + 18 1 -0.1187100004 0.6305706134 0.2995449619 + 19 1 -0.1360026039 1.5064794989 -0.2995449619 + 20 1 1.0708161514 1.1438381536 -0.2995449619 + 21 1 0.3617723689 0.2328409067 0.2806304477 + 22 1 0.6076263856 0.6656589748 0.2806304477 + 23 1 0.5903337821 1.5415678603 -0.2806304477 + 24 1 0.3444797654 1.1087497922 -0.2806304477 + + Dynamical Matrix in cartesian axes + + q = ( -0.506515122 -0.009999859 -0.293043680 ) + + 1 1 + 0.28523917 0.00000000 0.00849660 0.00000000 0.18943566 0.00000000 + 0.00849660 0.00000000 0.14808426 0.00000000 0.00387384 0.00000000 + 0.18943566 0.00000000 0.00387384 0.00000000 0.42122864 0.00000000 + 1 2 + 0.01396076 0.00000000 0.01594562 0.00000000 0.00620378 0.00000000 + 0.01403963 0.00000000 -0.04000784 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0.00000000 -0.00161796 0.00000000 + -0.02099850 0.00000000 -0.01639416 0.00000000 0.00631512 0.00000000 + 0.00976021 0.00000000 0.00152555 0.00000000 0.01530323 0.00000000 + 24 24 + 0.57485620 0.00000000 -0.01932785 0.00000000 0.02781041 0.00000000 + -0.01932785 0.00000000 0.14161730 0.00000000 -0.00602426 0.00000000 + 0.02781041 0.00000000 -0.00602426 0.00000000 0.16942295 0.00000000 + + Diagonalizing the dynamical matrix + + q = ( -0.506515122 -0.009999859 -0.293043680 ) + +*************************************************************************** + freq ( 1) = 10.22249717 [THz] = 340.98580162 [cm-1] +( 0.110219 -0.000000 -0.103565 0.000000 0.146368 0.000000 ) +( 0.040210 -0.000000 0.004668 -0.000000 -0.009104 -0.000000 ) +( -0.110219 0.000000 0.103565 -0.000000 -0.146368 -0.000000 ) +( -0.040210 0.000000 -0.004668 0.000000 0.009104 0.000000 ) +( 0.050157 -0.000000 0.067993 -0.000000 0.152450 -0.000000 ) +( 0.072985 -0.000000 -0.006329 0.000000 0.015163 0.000000 ) +( -0.050157 0.000000 -0.067993 0.000000 -0.152450 0.000000 ) +( -0.072985 0.000000 0.006329 -0.000000 -0.015163 -0.000000 ) +( -0.007907 0.000000 0.034288 -0.000000 -0.076644 -0.000000 ) +( -0.007469 0.000000 -0.011701 0.000000 -0.257147 0.000000 ) +( 0.007907 -0.000000 -0.034288 0.000000 0.076644 0.000000 ) +( 0.007469 -0.000000 0.011701 -0.000000 0.257147 -0.000000 ) +( 0.014707 -0.000000 -0.013240 0.000000 0.052248 0.000000 ) +( -0.072567 0.000000 0.052168 -0.000000 -0.249404 -0.000000 ) +( -0.014707 0.000000 0.013240 -0.000000 -0.052248 -0.000000 ) +( 0.072567 -0.000000 -0.052168 0.000000 0.249404 0.000000 ) +( 0.215258 -0.000000 -0.010685 0.000000 -0.093147 0.000000 ) +( -0.275583 0.000000 -0.039048 0.000000 0.045848 0.000000 ) +( -0.215258 0.000000 0.010685 -0.000000 0.093147 -0.000000 ) +( 0.275583 -0.000000 0.039048 -0.000000 -0.045848 -0.000000 ) +( -0.223273 0.000000 0.031473 -0.000000 0.058541 -0.000000 ) +( 0.284908 0.000000 -0.006843 0.000000 -0.032796 0.000000 ) +( 0.223273 -0.000000 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0.104674 0.000000 -0.016097 0.000000 0.004836 0.000000 ) +( 0.057145 0.000000 0.047239 0.000000 0.214653 0.000000 ) +( 0.105484 0.000000 -0.078198 0.000000 -0.078928 0.000000 ) +( 0.142545 0.000000 0.028813 0.000000 0.058019 0.000000 ) +( 0.105484 0.000000 -0.078198 0.000000 -0.078928 0.000000 ) +( 0.142545 0.000000 0.028813 0.000000 0.058019 0.000000 ) +( -0.143963 0.000000 0.104218 0.000000 0.200836 0.000000 ) +( -0.179349 0.000000 0.042050 0.000000 0.104513 0.000000 ) +( -0.143963 0.000000 0.104218 0.000000 0.200836 0.000000 ) +( -0.179349 0.000000 0.042050 0.000000 0.104513 0.000000 ) + freq ( 3) = 14.10603220 [THz] = 470.52658643 [cm-1] +( 0.116033 -0.000000 -0.045838 0.000000 0.264881 0.000000 ) +( 0.032548 -0.000000 -0.070613 0.000000 -0.032814 0.000000 ) +( 0.116033 -0.000000 -0.045838 0.000000 0.264881 0.000000 ) +( 0.032548 -0.000000 -0.070613 0.000000 -0.032814 0.000000 ) +( 0.090680 -0.000000 0.084795 -0.000000 0.253750 -0.000000 ) +( 0.085201 -0.000000 -0.042575 0.000000 0.011046 0.000000 ) +( 0.090680 -0.000000 0.084795 -0.000000 0.253750 -0.000000 ) +( 0.085201 -0.000000 -0.042575 0.000000 0.011046 0.000000 ) +( -0.021572 0.000000 -0.024311 0.000000 0.011668 0.000000 ) +( -0.046562 0.000000 -0.075171 0.000000 -0.194043 0.000000 ) +( -0.021572 0.000000 -0.024311 0.000000 0.011668 0.000000 ) +( -0.046562 0.000000 -0.075171 0.000000 -0.194043 0.000000 ) +( 0.013885 -0.000000 -0.017112 0.000000 0.000169 0.000000 ) +( -0.061843 0.000000 0.025195 -0.000000 -0.182975 -0.000000 ) +( 0.013885 -0.000000 -0.017112 0.000000 0.000169 0.000000 ) +( -0.061843 0.000000 0.025195 -0.000000 -0.182975 -0.000000 ) +( 0.217255 -0.000000 -0.010186 0.000000 -0.125416 0.000000 ) +( -0.237216 0.000000 -0.067189 0.000000 -0.025257 0.000000 ) +( 0.217255 -0.000000 -0.010186 0.000000 -0.125416 0.000000 ) +( -0.237216 0.000000 -0.067189 0.000000 -0.025257 0.000000 ) +( -0.219516 0.000000 0.021225 -0.000000 0.082234 -0.000000 ) +( 0.224002 -0.000000 -0.051095 0.000000 0.020544 0.000000 ) +( -0.219516 0.000000 0.021225 -0.000000 0.082234 -0.000000 ) +( 0.224002 -0.000000 -0.051095 0.000000 0.020544 0.000000 ) + freq ( 4) = 17.08054393 [THz] = 569.74561751 [cm-1] +( -0.022197 0.000000 -0.086755 0.000000 -0.257475 0.000000 ) +( 0.115486 -0.000000 -0.047211 0.000000 -0.045873 0.000000 ) +( 0.022197 -0.000000 0.086755 -0.000000 0.257475 -0.000000 ) +( -0.115486 0.000000 0.047211 -0.000000 0.045873 -0.000000 ) +( 0.088306 -0.000000 -0.002737 0.000000 -0.303580 0.000000 ) +( 0.019835 -0.000000 0.071987 -0.000000 -0.120726 -0.000000 ) +( -0.088306 0.000000 0.002737 -0.000000 0.303580 -0.000000 ) +( -0.019835 0.000000 -0.071987 0.000000 0.120726 0.000000 ) +( 0.027467 -0.000000 -0.100175 0.000000 -0.198104 0.000000 ) +( 0.090165 -0.000000 0.054435 -0.000000 -0.165888 -0.000000 ) +( -0.027467 0.000000 0.100175 -0.000000 0.198104 -0.000000 ) +( -0.090165 0.000000 -0.054435 0.000000 0.165888 0.000000 ) +( -0.192520 0.000000 -0.006728 0.000000 0.110552 0.000000 ) +( -0.018029 0.000000 -0.077321 0.000000 -0.119589 0.000000 ) +( 0.192520 -0.000000 0.006728 -0.000000 -0.110552 -0.000000 ) +( 0.018029 -0.000000 0.077321 -0.000000 0.119589 -0.000000 ) +( -0.144690 0.000000 -0.058640 0.000000 0.036569 0.000000 ) +( -0.080488 0.000000 -0.010350 0.000000 -0.059620 0.000000 ) +( 0.144690 -0.000000 0.058640 -0.000000 -0.036569 -0.000000 ) +( 0.080488 -0.000000 0.010350 -0.000000 0.059620 -0.000000 ) +( 0.142246 -0.000000 0.095514 -0.000000 -0.169755 -0.000000 ) +( 0.119955 -0.000000 -0.055456 0.000000 -0.133526 0.000000 ) +( -0.142246 0.000000 -0.095514 0.000000 0.169755 0.000000 ) +( -0.119955 0.000000 0.055456 -0.000000 0.133526 -0.000000 ) + freq ( 5) = 18.21853062 [THz] = 607.70476751 [cm-1] +( -0.050670 0.000000 0.292022 -0.000000 -0.021573 -0.000000 ) +( 0.008883 -0.000000 0.256324 -0.000000 -0.064399 -0.000000 ) +( -0.050670 0.000000 0.292022 0.000000 -0.021573 0.000000 ) +( 0.008883 -0.000000 0.256324 -0.000000 -0.064399 -0.000000 ) +( 0.104791 -0.000000 0.138924 -0.000000 -0.109426 -0.000000 ) +( 0.134524 -0.000000 0.167865 -0.000000 0.014844 -0.000000 ) +( 0.104791 -0.000000 0.138924 -0.000000 -0.109426 -0.000000 ) +( 0.134524 -0.000000 0.167865 -0.000000 0.014844 -0.000000 ) +( -0.009562 0.000000 0.076162 -0.000000 -0.197300 -0.000000 ) +( 0.073960 -0.000000 0.172811 -0.000000 -0.101966 -0.000000 ) +( -0.009562 0.000000 0.076162 -0.000000 -0.197300 -0.000000 ) +( 0.073960 -0.000000 0.172811 -0.000000 -0.101966 -0.000000 ) +( -0.173828 0.000000 0.048068 -0.000000 0.098884 -0.000000 ) +( -0.166118 0.000000 0.050123 -0.000000 0.017755 -0.000000 ) +( -0.173828 0.000000 0.048068 -0.000000 0.098884 -0.000000 ) +( -0.166118 0.000000 0.050123 -0.000000 0.017755 -0.000000 ) +( 0.062229 -0.000000 -0.155465 0.000000 -0.083721 0.000000 ) +( -0.012609 0.000000 0.010900 -0.000000 -0.041062 -0.000000 ) +( 0.062229 -0.000000 -0.155465 0.000000 -0.083721 0.000000 ) +( -0.012609 0.000000 0.010900 -0.000000 -0.041062 -0.000000 ) +( -0.079261 0.000000 0.152331 -0.000000 -0.107575 -0.000000 ) +( 0.010141 -0.000000 0.103932 -0.000000 0.027480 -0.000000 ) +( -0.079261 0.000000 0.152331 -0.000000 -0.107575 -0.000000 ) +( 0.010141 -0.000000 0.103932 -0.000000 0.027480 -0.000000 ) + freq ( 6) = 19.71715893 [THz] = 657.69362722 [cm-1] +( 0.053919 -0.000000 0.103330 -0.000000 -0.102100 -0.000000 ) +( -0.098286 0.000000 0.176687 -0.000000 -0.080805 -0.000000 ) +( -0.053919 0.000000 -0.103330 0.000000 0.102100 0.000000 ) +( 0.098286 -0.000000 -0.176687 0.000000 0.080805 0.000000 ) +( -0.184358 0.000000 -0.042066 0.000000 0.033371 0.000000 ) +( 0.093899 -0.000000 -0.035228 0.000000 0.046764 0.000000 ) +( 0.184358 -0.000000 0.042066 -0.000000 -0.033371 -0.000000 ) +( -0.093899 0.000000 0.035228 -0.000000 -0.046764 -0.000000 ) +( -0.037804 0.000000 -0.157160 0.000000 0.222011 0.000000 ) +( 0.041106 -0.000000 -0.005946 0.000000 -0.133242 0.000000 ) +( 0.037804 -0.000000 0.157160 -0.000000 -0.222011 -0.000000 ) +( -0.041106 0.000000 0.005946 -0.000000 0.133242 -0.000000 ) +( 0.165417 -0.000000 -0.012042 0.000000 -0.156052 0.000000 ) +( -0.112326 0.000000 -0.048046 0.000000 -0.057654 0.000000 ) +( -0.165417 0.000000 0.012042 -0.000000 0.156052 -0.000000 ) +( 0.112326 -0.000000 0.048046 -0.000000 0.057654 -0.000000 ) +( -0.158347 0.000000 -0.184314 0.000000 0.151506 0.000000 ) +( -0.140143 0.000000 0.065765 -0.000000 -0.052368 -0.000000 ) +( 0.158347 -0.000000 0.184314 -0.000000 -0.151506 -0.000000 ) +( 0.140143 -0.000000 -0.065765 0.000000 0.052368 0.000000 ) +( 0.181488 -0.000000 -0.128184 0.000000 0.114614 0.000000 ) +( 0.156668 -0.000000 -0.136627 0.000000 0.006156 0.000000 ) +( -0.181488 0.000000 0.128184 -0.000000 -0.114614 -0.000000 ) +( -0.156668 0.000000 0.136627 -0.000000 -0.006156 -0.000000 ) + freq ( 7) = 21.82061143 [THz] = 727.85725031 [cm-1] +( 0.109142 -0.000000 0.029716 -0.000000 0.066743 -0.000000 ) +( 0.030920 -0.000000 0.121044 -0.000000 -0.012935 -0.000000 ) +( -0.109142 0.000000 -0.029716 0.000000 -0.066743 0.000000 ) +( -0.030920 0.000000 -0.121044 0.000000 0.012935 0.000000 ) +( 0.107471 -0.000000 -0.166155 0.000000 0.082809 0.000000 ) +( 0.088754 -0.000000 0.058662 -0.000000 0.014208 -0.000000 ) +( -0.107471 0.000000 0.166155 -0.000000 -0.082809 -0.000000 ) +( -0.088754 0.000000 -0.058662 0.000000 -0.014208 0.000000 ) +( -0.037796 0.000000 -0.255889 0.000000 -0.115665 0.000000 ) +( 0.043735 -0.000000 -0.027121 0.000000 0.060544 0.000000 ) +( 0.037796 -0.000000 0.255889 0.000000 0.115665 0.000000 ) +( -0.043735 0.000000 0.027121 -0.000000 -0.060544 -0.000000 ) +( -0.102946 0.000000 0.241192 -0.000000 0.054374 -0.000000 ) +( -0.073291 0.000000 -0.200608 0.000000 0.131637 0.000000 ) +( 0.102946 -0.000000 -0.241192 0.000000 -0.054374 0.000000 ) +( 0.073291 -0.000000 0.200608 -0.000000 -0.131637 -0.000000 ) +( 0.105354 -0.000000 -0.124563 0.000000 -0.108794 0.000000 ) +( 0.031718 -0.000000 0.207786 -0.000000 -0.027857 -0.000000 ) +( -0.105354 0.000000 0.124563 -0.000000 0.108794 -0.000000 ) +( -0.031718 0.000000 -0.207786 0.000000 0.027857 0.000000 ) +( -0.132694 0.000000 0.005550 -0.000000 -0.088685 -0.000000 ) +( -0.057306 0.000000 -0.237723 0.000000 0.139501 0.000000 ) +( 0.132694 -0.000000 -0.005550 0.000000 0.088685 0.000000 ) +( 0.057306 -0.000000 0.237723 -0.000000 -0.139501 -0.000000 ) + freq ( 8) = 21.98387472 [THz] = 733.30312722 [cm-1] +( 0.050823 -0.000000 0.041281 -0.000000 -0.070615 -0.000000 ) +( 0.075613 -0.000000 -0.088501 0.000000 -0.060600 0.000000 ) +( 0.050823 -0.000000 0.041281 -0.000000 -0.070615 -0.000000 ) +( 0.075613 -0.000000 -0.088501 0.000000 -0.060600 0.000000 ) +( -0.137027 0.000000 0.072447 -0.000000 0.048380 -0.000000 ) +( 0.015116 -0.000000 0.211495 -0.000000 -0.088508 -0.000000 ) +( -0.137027 0.000000 0.072447 -0.000000 0.048380 -0.000000 ) +( 0.015116 -0.000000 0.211495 -0.000000 -0.088508 -0.000000 ) +( -0.023281 0.000000 -0.053306 0.000000 0.230514 0.000000 ) +( -0.002768 0.000000 0.089383 -0.000000 -0.091615 -0.000000 ) +( -0.023281 0.000000 -0.053306 0.000000 0.230514 0.000000 ) +( -0.002768 0.000000 0.089383 -0.000000 -0.091615 -0.000000 ) +( 0.160531 -0.000000 -0.133750 0.000000 -0.151470 0.000000 ) +( -0.035002 0.000000 0.214808 -0.000000 -0.091972 -0.000000 ) +( 0.160531 -0.000000 -0.133750 0.000000 -0.151470 0.000000 ) +( -0.035002 0.000000 0.214808 -0.000000 -0.091972 -0.000000 ) +( -0.114961 0.000000 -0.191367 0.000000 0.168177 0.000000 ) +( -0.076921 0.000000 0.146933 -0.000000 -0.058179 -0.000000 ) +( -0.114961 0.000000 -0.191367 0.000000 0.168177 0.000000 ) +( -0.076921 0.000000 0.146933 -0.000000 -0.058179 -0.000000 ) +( 0.139585 -0.000000 0.222089 -0.000000 0.047297 -0.000000 ) +( 0.104356 -0.000000 0.081015 -0.000000 -0.038695 -0.000000 ) +( 0.139585 -0.000000 0.222089 -0.000000 0.047297 -0.000000 ) +( 0.104356 -0.000000 0.081015 -0.000000 -0.038695 -0.000000 ) + freq ( 9) = 23.52268769 [THz] = 784.63240278 [cm-1] +( 0.011601 0.000000 0.107555 0.000000 -0.078438 0.000000 ) +( -0.015877 0.000000 0.078850 0.000000 0.280406 0.000000 ) +( -0.011601 0.000000 -0.107555 0.000000 0.078438 0.000000 ) +( 0.015877 0.000000 -0.078850 0.000000 -0.280406 0.000000 ) +( -0.024015 0.000000 -0.120052 0.000000 -0.040187 0.000000 ) +( -0.241628 0.000000 -0.030520 0.000000 0.130131 0.000000 ) +( 0.024015 0.000000 0.120052 0.000000 0.040187 0.000000 ) +( 0.241628 0.000000 0.030520 0.000000 -0.130131 0.000000 ) +( -0.032982 0.000000 0.009800 0.000000 -0.014721 0.000000 ) +( -0.149885 0.000000 -0.054124 0.000000 0.026048 0.000000 ) +( 0.032982 0.000000 -0.009800 0.000000 0.014721 0.000000 ) +( 0.149885 0.000000 0.054124 0.000000 -0.026048 0.000000 ) +( -0.042668 0.000000 0.119630 0.000000 -0.040834 0.000000 ) +( 0.202645 0.000000 -0.090154 0.000000 -0.192637 0.000000 ) +( 0.042668 0.000000 -0.119630 0.000000 0.040834 0.000000 ) +( -0.202645 0.000000 0.090154 0.000000 0.192637 0.000000 ) +( -0.023303 0.000000 0.049129 0.000000 0.039677 0.000000 ) +( -0.072569 0.000000 0.075918 0.000000 0.375842 0.000000 ) +( 0.023303 0.000000 -0.049129 0.000000 -0.039677 0.000000 ) +( 0.072569 0.000000 -0.075918 0.000000 -0.375842 0.000000 ) +( 0.026300 0.000000 -0.046636 0.000000 -0.065169 0.000000 ) +( 0.065433 0.000000 -0.056279 0.000000 -0.035191 0.000000 ) +( -0.026300 0.000000 0.046636 0.000000 0.065169 0.000000 ) +( -0.065433 0.000000 0.056279 0.000000 0.035191 0.000000 ) + freq ( 10) = 24.55060969 [THz] = 818.92019002 [cm-1] +( 0.094846 0.000000 0.060086 0.000000 -0.063615 0.000000 ) +( -0.004198 0.000000 0.072504 0.000000 0.282759 0.000000 ) +( 0.094846 0.000000 0.060086 0.000000 -0.063615 0.000000 ) +( -0.004198 0.000000 0.072504 0.000000 0.282759 0.000000 ) +( 0.039741 0.000000 0.117331 0.000000 -0.015430 0.000000 ) +( -0.250737 0.000000 0.064110 0.000000 0.087685 0.000000 ) +( 0.039741 0.000000 0.117331 0.000000 -0.015430 0.000000 ) +( -0.250737 0.000000 0.064110 0.000000 0.087685 0.000000 ) +( -0.094895 0.000000 -0.040628 0.000000 -0.069773 0.000000 ) +( -0.154236 0.000000 0.109032 0.000000 0.035239 0.000000 ) +( -0.094895 0.000000 -0.040628 0.000000 -0.069773 0.000000 ) +( -0.154236 0.000000 0.109032 0.000000 0.035239 0.000000 ) +( -0.090772 0.000000 0.048831 0.000000 -0.035834 0.000000 ) +( 0.272284 0.000000 0.053372 0.000000 -0.224406 0.000000 ) +( -0.090772 0.000000 0.048831 0.000000 -0.035834 0.000000 ) +( 0.272284 0.000000 0.053372 0.000000 -0.224406 0.000000 ) +( 0.011675 0.000000 0.067342 0.000000 0.029116 0.000000 ) +( -0.065181 0.000000 -0.058416 0.000000 0.266378 0.000000 ) +( 0.011675 0.000000 0.067342 0.000000 0.029116 0.000000 ) +( -0.065181 0.000000 -0.058416 0.000000 0.266378 0.000000 ) +( 0.000452 0.000000 0.122186 0.000000 -0.069746 0.000000 ) +( 0.059338 0.000000 0.003994 0.000000 -0.093291 0.000000 ) +( 0.000452 0.000000 0.122186 0.000000 -0.069746 0.000000 ) +( 0.059338 0.000000 0.003994 0.000000 -0.093291 0.000000 ) + freq ( 11) = 25.20129749 [THz] = 840.62479859 [cm-1] +( -0.278137 0.000000 -0.089330 0.000000 0.114883 0.000000 ) +( -0.054313 0.000000 -0.001208 0.000000 -0.049831 0.000000 ) +( 0.278137 0.000000 0.089330 0.000000 -0.114883 0.000000 ) +( 0.054313 0.000000 0.001208 0.000000 0.049831 0.000000 ) +( -0.022387 0.000000 0.115331 0.000000 -0.061998 0.000000 ) +( -0.077912 0.000000 0.202991 0.000000 -0.067898 0.000000 ) +( 0.022387 0.000000 -0.115331 0.000000 0.061998 0.000000 ) +( 0.077912 0.000000 -0.202991 0.000000 0.067898 0.000000 ) +( 0.206655 0.000000 0.007048 0.000000 0.048072 0.000000 ) +( 0.015657 0.000000 0.013917 0.000000 0.015527 0.000000 ) +( -0.206655 0.000000 -0.007048 0.000000 -0.048072 0.000000 ) +( -0.015657 0.000000 -0.013917 0.000000 -0.015527 0.000000 ) +( 0.220482 0.000000 0.161751 0.000000 0.164883 0.000000 ) +( 0.182489 0.000000 -0.160011 0.000000 -0.091773 0.000000 ) +( -0.220482 0.000000 -0.161751 0.000000 -0.164883 0.000000 ) +( -0.182489 0.000000 0.160011 0.000000 0.091773 0.000000 ) +( 0.002397 0.000000 -0.142287 0.000000 -0.084544 0.000000 ) +( 0.039748 0.000000 0.006853 0.000000 -0.022904 0.000000 ) +( -0.002397 0.000000 0.142287 0.000000 0.084544 0.000000 ) +( -0.039748 0.000000 -0.006853 0.000000 0.022904 0.000000 ) +( -0.027286 0.000000 -0.029629 0.000000 0.185181 0.000000 ) +( -0.015372 0.000000 -0.145706 0.000000 -0.156611 0.000000 ) +( 0.027286 0.000000 0.029629 0.000000 -0.185181 0.000000 ) +( 0.015372 0.000000 0.145706 0.000000 0.156611 0.000000 ) + freq ( 12) = 26.59802642 [THz] = 887.21466092 [cm-1] +( 0.209068 -0.000000 -0.004243 0.000000 -0.076121 0.000000 ) +( 0.074352 -0.000000 -0.081564 0.000000 0.017776 0.000000 ) +( 0.209068 -0.000000 -0.004243 0.000000 -0.076121 0.000000 ) +( 0.074352 -0.000000 -0.081564 0.000000 0.017776 0.000000 ) +( -0.046914 0.000000 -0.129978 0.000000 0.122932 0.000000 ) +( 0.000611 -0.000000 -0.149583 0.000000 -0.038136 0.000000 ) +( -0.046914 0.000000 -0.129978 0.000000 0.122932 0.000000 ) +( 0.000611 -0.000000 -0.149583 0.000000 -0.038136 0.000000 ) +( -0.241249 0.000000 -0.053530 0.000000 -0.094315 0.000000 ) +( 0.027593 -0.000000 -0.013485 0.000000 0.073979 0.000000 ) +( -0.241249 0.000000 -0.053530 0.000000 -0.094315 0.000000 ) +( 0.027593 -0.000000 -0.013485 0.000000 0.073979 0.000000 ) +( -0.093428 0.000000 -0.027396 0.000000 -0.076589 0.000000 ) +( 0.027432 -0.000000 -0.003048 0.000000 0.085800 0.000000 ) +( -0.093428 0.000000 -0.027396 0.000000 -0.076589 0.000000 ) +( 0.027432 -0.000000 -0.003048 0.000000 0.085800 0.000000 ) +( 0.159096 -0.000000 -0.005875 0.000000 0.023186 0.000000 ) +( 0.061672 -0.000000 0.362911 -0.000000 -0.021224 -0.000000 ) +( 0.159096 -0.000000 -0.005875 0.000000 0.023186 0.000000 ) +( 0.061672 -0.000000 0.362911 0.000000 -0.021224 0.000000 ) +( -0.149567 0.000000 0.102750 -0.000000 -0.208750 -0.000000 ) +( -0.058783 0.000000 0.137821 -0.000000 0.138928 -0.000000 ) +( -0.149567 0.000000 0.102750 -0.000000 -0.208750 -0.000000 ) +( -0.058783 0.000000 0.137821 -0.000000 0.138928 -0.000000 ) + freq ( 13) = 27.98104285 [THz] = 933.34712314 [cm-1] +( -0.148503 0.000000 0.021620 0.000000 0.014315 0.000000 ) +( 0.114801 0.000000 -0.099521 0.000000 0.056423 0.000000 ) +( -0.148503 0.000000 0.021620 0.000000 0.014315 0.000000 ) +( 0.114801 0.000000 -0.099521 0.000000 0.056423 0.000000 ) +( -0.060067 0.000000 -0.136239 0.000000 -0.036200 0.000000 ) +( -0.039040 0.000000 -0.079940 0.000000 -0.077332 0.000000 ) +( -0.060067 0.000000 -0.136239 0.000000 -0.036200 0.000000 ) +( -0.039040 0.000000 -0.079940 0.000000 -0.077332 0.000000 ) +( 0.134395 0.000000 0.219289 0.000000 -0.085809 0.000000 ) +( 0.051247 0.000000 0.145198 0.000000 -0.068409 0.000000 ) +( 0.134395 0.000000 0.219289 0.000000 -0.085809 0.000000 ) +( 0.051247 0.000000 0.145198 0.000000 -0.068409 0.000000 ) +( 0.055218 0.000000 0.004786 0.000000 0.156638 0.000000 ) +( 0.152534 0.000000 -0.029785 0.000000 -0.153922 0.000000 ) +( 0.055218 0.000000 0.004786 0.000000 0.156638 0.000000 ) +( 0.152534 0.000000 -0.029785 0.000000 -0.153922 0.000000 ) +( 0.064574 0.000000 -0.232521 0.000000 -0.034739 0.000000 ) +( 0.012509 0.000000 0.258168 0.000000 0.058490 0.000000 ) +( 0.064574 0.000000 -0.232521 0.000000 -0.034739 0.000000 ) +( 0.012509 0.000000 0.258168 0.000000 0.058490 0.000000 ) +( -0.088895 0.000000 -0.177914 0.000000 0.147269 0.000000 ) +( 0.020041 0.000000 0.083115 0.000000 -0.195075 0.000000 ) +( -0.088895 0.000000 -0.177914 0.000000 0.147269 0.000000 ) +( 0.020041 0.000000 0.083115 0.000000 -0.195075 0.000000 ) + freq ( 14) = 28.25815780 [THz] = 942.59068314 [cm-1] +( -0.149263 0.000000 0.291856 0.000000 0.156178 0.000000 ) +( -0.006622 0.000000 0.200970 -0.000000 -0.083343 -0.000000 ) +( 0.149263 -0.000000 -0.291856 0.000000 -0.156178 0.000000 ) +( 0.006622 -0.000000 -0.200970 0.000000 0.083343 0.000000 ) +( 0.130847 -0.000000 -0.141937 0.000000 -0.049379 0.000000 ) +( -0.049063 0.000000 -0.117879 0.000000 -0.091846 0.000000 ) +( -0.130847 0.000000 0.141937 -0.000000 0.049379 -0.000000 ) +( 0.049063 -0.000000 0.117879 -0.000000 0.091846 -0.000000 ) +( -0.047579 0.000000 -0.044637 0.000000 -0.006135 0.000000 ) +( 0.048184 -0.000000 -0.026965 0.000000 -0.039752 0.000000 ) +( 0.047579 -0.000000 0.044637 -0.000000 0.006135 -0.000000 ) +( -0.048184 0.000000 0.026965 -0.000000 0.039752 -0.000000 ) +( -0.091857 0.000000 -0.191665 0.000000 -0.027534 0.000000 ) +( 0.061728 -0.000000 0.153698 -0.000000 -0.059397 -0.000000 ) +( 0.091857 -0.000000 0.191665 -0.000000 0.027534 -0.000000 ) +( -0.061728 0.000000 -0.153698 0.000000 0.059397 0.000000 ) +( 0.026675 -0.000000 0.135974 -0.000000 -0.094183 -0.000000 ) +( 0.045680 -0.000000 -0.030160 0.000000 -0.099424 0.000000 ) +( -0.026675 0.000000 -0.135974 0.000000 0.094183 0.000000 ) +( -0.045680 0.000000 0.030160 -0.000000 0.099424 -0.000000 ) +( -0.055218 0.000000 -0.108206 0.000000 -0.015800 0.000000 ) +( -0.019207 0.000000 -0.215146 0.000000 -0.260567 0.000000 ) +( 0.055218 -0.000000 0.108206 -0.000000 0.015800 -0.000000 ) +( 0.019207 -0.000000 0.215146 -0.000000 0.260567 -0.000000 ) + freq ( 15) = 28.34766675 [THz] = 945.57638010 [cm-1] +( 0.093206 0.000000 -0.050232 0.000000 -0.070482 0.000000 ) +( -0.077293 0.000000 0.072406 0.000000 -0.102912 0.000000 ) +( 0.093206 0.000000 -0.050232 0.000000 -0.070482 0.000000 ) +( -0.077293 0.000000 0.072406 0.000000 -0.102912 0.000000 ) +( -0.141195 0.000000 0.369400 0.000000 0.076796 0.000000 ) +( 0.016918 0.000000 0.014111 0.000000 -0.034625 0.000000 ) +( -0.141195 0.000000 0.369400 0.000000 0.076796 0.000000 ) +( 0.016918 0.000000 0.014111 0.000000 -0.034625 0.000000 ) +( 0.029199 0.000000 0.073011 0.000000 0.016050 0.000000 ) +( 0.078584 0.000000 -0.241020 0.000000 0.047836 0.000000 ) +( 0.029199 0.000000 0.073011 0.000000 0.016050 0.000000 ) +( 0.078584 0.000000 -0.241020 0.000000 0.047836 0.000000 ) +( -0.003517 0.000000 0.334277 0.000000 -0.019174 0.000000 ) +( 0.135417 0.000000 -0.069068 0.000000 0.020825 0.000000 ) +( -0.003517 0.000000 0.334277 0.000000 -0.019174 0.000000 ) +( 0.135417 0.000000 -0.069068 0.000000 0.020825 0.000000 ) +( 0.010390 0.000000 -0.054400 0.000000 0.052575 0.000000 ) +( -0.016685 0.000000 0.051555 0.000000 -0.031113 0.000000 ) +( 0.010390 0.000000 -0.054400 0.000000 0.052575 0.000000 ) +( -0.016685 0.000000 0.051555 0.000000 -0.031113 0.000000 ) +( 0.009583 0.000000 -0.108166 0.000000 0.032345 0.000000 ) +( 0.028272 0.000000 0.249304 0.000000 -0.062097 0.000000 ) +( 0.009583 0.000000 -0.108166 0.000000 0.032345 0.000000 ) +( 0.028272 0.000000 0.249304 0.000000 -0.062097 0.000000 ) + freq ( 16) = 28.70493961 [THz] = 957.49371992 [cm-1] +( -0.060086 0.000000 -0.079917 0.000000 -0.068013 0.000000 ) +( -0.111798 0.000000 0.118049 0.000000 0.001598 0.000000 ) +( 0.060086 0.000000 0.079917 0.000000 0.068013 0.000000 ) +( 0.111798 0.000000 -0.118049 0.000000 -0.001598 0.000000 ) +( 0.007664 0.000000 0.257391 0.000000 -0.104683 0.000000 ) +( 0.013736 0.000000 -0.004097 0.000000 0.065754 0.000000 ) +( -0.007664 0.000000 -0.257391 0.000000 0.104683 0.000000 ) +( -0.013736 0.000000 0.004097 0.000000 -0.065754 0.000000 ) +( -0.001376 0.000000 -0.013727 0.000000 -0.108454 0.000000 ) +( -0.070669 0.000000 -0.222854 0.000000 0.025368 0.000000 ) +( 0.001376 0.000000 0.013727 0.000000 0.108454 0.000000 ) +( 0.070669 0.000000 0.222854 0.000000 -0.025368 0.000000 ) +( 0.007571 0.000000 -0.158758 0.000000 0.142212 0.000000 ) +( 0.008628 0.000000 0.255338 0.000000 0.029043 0.000000 ) +( -0.007571 0.000000 0.158758 0.000000 -0.142212 0.000000 ) +( -0.008628 0.000000 -0.255338 0.000000 -0.029043 0.000000 ) +( 0.040305 0.000000 -0.219021 0.000000 -0.005919 0.000000 ) +( 0.010238 0.000000 0.209158 0.000000 0.060078 0.000000 ) +( -0.040305 0.000000 0.219021 0.000000 0.005919 0.000000 ) +( -0.010238 0.000000 -0.209158 0.000000 -0.060078 0.000000 ) +( -0.058265 0.000000 -0.256818 0.000000 -0.148192 0.000000 ) +( -0.027203 0.000000 -0.006433 0.000000 0.095420 0.000000 ) +( 0.058265 0.000000 0.256818 0.000000 0.148192 0.000000 ) +( 0.027203 0.000000 0.006433 0.000000 -0.095420 0.000000 ) + freq ( 17) = 29.49293940 [THz] = 983.77856383 [cm-1] +( 0.123660 -0.000000 0.204959 -0.000000 -0.153834 -0.000000 ) +( -0.015444 0.000000 0.022510 -0.000000 0.053636 -0.000000 ) +( 0.123660 -0.000000 0.204959 -0.000000 -0.153834 -0.000000 ) +( -0.015444 0.000000 0.022510 -0.000000 0.053636 -0.000000 ) +( -0.198234 0.000000 -0.148092 0.000000 0.091469 0.000000 ) +( 0.127169 -0.000000 0.020866 -0.000000 0.148680 -0.000000 ) +( -0.198234 0.000000 -0.148092 0.000000 0.091469 0.000000 ) +( 0.127169 -0.000000 0.020866 -0.000000 0.148680 -0.000000 ) +( 0.022672 -0.000000 0.109137 -0.000000 0.024062 -0.000000 ) +( -0.059322 0.000000 0.150530 -0.000000 -0.064897 -0.000000 ) +( 0.022672 -0.000000 0.109137 -0.000000 0.024062 -0.000000 ) +( -0.059322 0.000000 0.150530 -0.000000 -0.064897 -0.000000 ) +( 0.210916 -0.000000 0.196732 -0.000000 0.045098 -0.000000 ) +( -0.155532 0.000000 -0.099903 0.000000 -0.007772 0.000000 ) +( 0.210916 0.000000 0.196732 -0.000000 0.045098 -0.000000 ) +( -0.155532 0.000000 -0.099903 0.000000 -0.007772 0.000000 ) +( 0.081481 -0.000000 0.194964 -0.000000 0.170993 -0.000000 ) +( -0.049914 0.000000 -0.030493 0.000000 0.149381 0.000000 ) +( 0.081481 -0.000000 0.194964 -0.000000 0.170993 -0.000000 ) +( -0.049914 0.000000 -0.030493 0.000000 0.149381 0.000000 ) +( -0.024004 0.000000 -0.047745 0.000000 0.139811 0.000000 ) +( 0.016424 -0.000000 0.014471 -0.000000 0.147480 -0.000000 ) +( -0.024004 0.000000 -0.047745 0.000000 0.139811 0.000000 ) +( 0.016424 -0.000000 0.014471 -0.000000 0.147480 -0.000000 ) + freq ( 18) = 30.46513202 [THz] = 1016.20741898 [cm-1] +( -0.180438 0.000000 0.138010 0.000000 0.024969 0.000000 ) +( -0.031502 0.000000 -0.103704 0.000000 -0.065184 0.000000 ) +( 0.180438 0.000000 -0.138010 0.000000 -0.024969 0.000000 ) +( 0.031502 0.000000 0.103704 0.000000 0.065184 0.000000 ) +( -0.018970 0.000000 -0.161812 0.000000 -0.084662 0.000000 ) +( 0.075957 0.000000 0.098042 0.000000 0.052809 0.000000 ) +( 0.018970 0.000000 0.161812 0.000000 0.084662 0.000000 ) +( -0.075957 0.000000 -0.098042 0.000000 -0.052809 0.000000 ) +( -0.035897 0.000000 0.298568 0.000000 -0.004478 0.000000 ) +( 0.035317 0.000000 -0.218836 0.000000 -0.116350 0.000000 ) +( 0.035897 0.000000 -0.298568 0.000000 0.004478 0.000000 ) +( -0.035317 0.000000 0.218836 0.000000 0.116350 0.000000 ) +( -0.063455 0.000000 0.165831 0.000000 -0.058364 0.000000 ) +( -0.158481 0.000000 -0.050825 0.000000 0.009122 0.000000 ) +( 0.063455 0.000000 -0.165831 0.000000 0.058364 0.000000 ) +( 0.158481 0.000000 0.050825 0.000000 -0.009122 0.000000 ) +( 0.022065 0.000000 0.042899 0.000000 0.063918 0.000000 ) +( -0.008233 0.000000 0.330875 0.000000 -0.055245 0.000000 ) +( -0.022065 0.000000 -0.042899 0.000000 -0.063918 0.000000 ) +( 0.008233 0.000000 -0.330875 0.000000 0.055245 0.000000 ) +( -0.030105 0.000000 -0.020975 0.000000 0.030061 0.000000 ) +( 0.044860 0.000000 0.182489 0.000000 -0.086478 0.000000 ) +( 0.030105 0.000000 0.020975 0.000000 -0.030061 0.000000 ) +( -0.044860 0.000000 -0.182489 0.000000 0.086478 0.000000 ) + freq ( 19) = 30.73268147 [THz] = 1025.13190778 [cm-1] +( -0.140156 0.000000 -0.093188 0.000000 0.006854 0.000000 ) +( 0.151286 0.000000 -0.197747 0.000000 0.015955 0.000000 ) +( -0.140156 0.000000 -0.093188 0.000000 0.006854 0.000000 ) +( 0.151286 0.000000 -0.197747 0.000000 0.015955 0.000000 ) +( 0.060617 0.000000 -0.040916 0.000000 -0.113385 0.000000 ) +( 0.006575 0.000000 0.282286 0.000000 -0.063362 0.000000 ) +( 0.060617 0.000000 -0.040916 0.000000 -0.113385 0.000000 ) +( 0.006575 0.000000 0.282286 0.000000 -0.063362 0.000000 ) +( 0.100651 0.000000 -0.039846 0.000000 -0.134008 0.000000 ) +( -0.056372 0.000000 -0.215006 0.000000 0.014071 0.000000 ) +( 0.100651 0.000000 -0.039846 0.000000 -0.134008 0.000000 ) +( -0.056372 0.000000 -0.215006 0.000000 0.014071 0.000000 ) +( 0.038105 0.000000 0.168168 0.000000 0.227798 0.000000 ) +( -0.014348 0.000000 0.179014 0.000000 0.011996 0.000000 ) +( 0.038105 0.000000 0.168168 0.000000 0.227798 0.000000 ) +( -0.014348 0.000000 0.179014 0.000000 0.011996 0.000000 ) +( 0.061414 0.000000 0.247232 0.000000 0.038166 0.000000 ) +( -0.005882 0.000000 0.120980 0.000000 0.021193 0.000000 ) +( 0.061414 0.000000 0.247232 0.000000 0.038166 0.000000 ) +( -0.005882 0.000000 0.120980 0.000000 0.021193 0.000000 ) +( -0.049808 0.000000 0.162680 0.000000 0.002639 0.000000 ) +( 0.013753 0.000000 0.020816 0.000000 0.055536 0.000000 ) +( -0.049808 0.000000 0.162680 0.000000 0.002639 0.000000 ) +( 0.013753 0.000000 0.020816 0.000000 0.055536 0.000000 ) + freq ( 20) = 31.21611678 [THz] = 1041.25757387 [cm-1] +( -0.044079 0.000000 -0.084241 0.000000 -0.046148 0.000000 ) +( -0.175830 0.000000 0.151388 0.000000 -0.066694 0.000000 ) +( 0.044079 0.000000 0.084241 0.000000 0.046148 0.000000 ) +( 0.175830 0.000000 -0.151388 0.000000 0.066694 0.000000 ) +( -0.094287 0.000000 -0.054314 0.000000 -0.019458 0.000000 ) +( -0.022149 0.000000 -0.094059 0.000000 0.069406 0.000000 ) +( 0.094287 0.000000 0.054314 0.000000 0.019458 0.000000 ) +( 0.022149 0.000000 0.094059 0.000000 -0.069406 0.000000 ) +( 0.112323 0.000000 -0.263452 0.000000 -0.040674 0.000000 ) +( -0.146782 0.000000 -0.171396 0.000000 0.050847 0.000000 ) +( -0.112323 0.000000 0.263452 0.000000 0.040674 0.000000 ) +( 0.146782 0.000000 0.171396 0.000000 -0.050847 0.000000 ) +( 0.058851 0.000000 -0.120043 0.000000 0.133680 0.000000 ) +( -0.036976 0.000000 -0.032454 0.000000 -0.023666 0.000000 ) +( -0.058851 0.000000 0.120043 0.000000 -0.133680 0.000000 ) +( 0.036976 0.000000 0.032454 0.000000 0.023666 0.000000 ) +( 0.016858 0.000000 0.229807 0.000000 -0.052990 0.000000 ) +( 0.008651 0.000000 0.150427 0.000000 -0.043599 0.000000 ) +( -0.016858 0.000000 -0.229807 0.000000 0.052990 0.000000 ) +( -0.008651 0.000000 -0.150427 0.000000 0.043599 0.000000 ) +( 0.029427 0.000000 0.335182 0.000000 0.098759 0.000000 ) +( 0.051028 0.000000 0.143754 0.000000 -0.039016 0.000000 ) +( -0.029427 0.000000 -0.335182 0.000000 -0.098759 0.000000 ) +( -0.051028 0.000000 -0.143754 0.000000 0.039016 0.000000 ) + freq ( 21) = 31.76330890 [THz] = 1059.50993840 [cm-1] +( -0.043152 0.000000 -0.194485 0.000000 0.005327 0.000000 ) +( 0.306706 0.000000 0.187019 -0.000000 -0.001745 -0.000000 ) +( -0.043152 0.000000 -0.194485 0.000000 0.005327 0.000000 ) +( 0.306706 -0.000000 0.187019 -0.000000 -0.001745 -0.000000 ) +( -0.071795 0.000000 0.078990 -0.000000 0.053639 -0.000000 ) +( 0.053223 -0.000000 -0.039453 0.000000 -0.215222 0.000000 ) +( -0.071795 0.000000 0.078990 -0.000000 0.053639 -0.000000 ) +( 0.053223 -0.000000 -0.039453 0.000000 -0.215222 0.000000 ) +( -0.001556 0.000000 -0.230362 0.000000 0.037635 0.000000 ) +( 0.068321 -0.000000 0.197939 -0.000000 -0.119903 -0.000000 ) +( -0.001556 0.000000 -0.230362 0.000000 0.037635 0.000000 ) +( 0.068321 -0.000000 0.197939 -0.000000 -0.119903 -0.000000 ) +( 0.127748 -0.000000 0.040421 -0.000000 0.047553 -0.000000 ) +( -0.010070 0.000000 -0.212494 0.000000 -0.080207 0.000000 ) +( 0.127748 -0.000000 0.040421 -0.000000 0.047553 -0.000000 ) +( -0.010070 0.000000 -0.212494 0.000000 -0.080207 0.000000 ) +( 0.002163 -0.000000 0.142688 -0.000000 -0.099591 -0.000000 ) +( 0.098436 -0.000000 -0.057870 0.000000 0.040066 0.000000 ) +( 0.002163 -0.000000 0.142688 -0.000000 -0.099591 -0.000000 ) +( 0.098436 -0.000000 -0.057870 0.000000 0.040066 0.000000 ) +( -0.000238 0.000000 0.096068 -0.000000 -0.034623 -0.000000 ) +( -0.117324 0.000000 0.096675 -0.000000 -0.056376 -0.000000 ) +( -0.000238 0.000000 0.096068 -0.000000 -0.034623 -0.000000 ) +( -0.117324 0.000000 0.096675 -0.000000 -0.056376 -0.000000 ) + freq ( 22) = 32.42434351 [THz] = 1081.55967941 [cm-1] +( 0.184456 0.000000 0.049796 0.000000 -0.030957 0.000000 ) +( -0.164007 0.000000 -0.217764 0.000000 -0.094909 0.000000 ) +( -0.184456 0.000000 -0.049796 0.000000 0.030957 0.000000 ) +( 0.164007 0.000000 0.217764 0.000000 0.094909 0.000000 ) +( -0.049773 0.000000 -0.020302 0.000000 0.122961 0.000000 ) +( -0.017848 0.000000 0.437408 0.000000 0.020904 0.000000 ) +( 0.049773 0.000000 0.020302 0.000000 -0.122961 0.000000 ) +( 0.017848 0.000000 -0.437408 0.000000 -0.020904 0.000000 ) +( -0.105244 0.000000 -0.089191 0.000000 0.038929 0.000000 ) +( -0.021372 0.000000 -0.107021 0.000000 0.018447 0.000000 ) +( 0.105244 0.000000 0.089191 0.000000 -0.038929 0.000000 ) +( 0.021372 0.000000 0.107021 0.000000 -0.018447 0.000000 ) +( 0.026815 0.000000 -0.057776 0.000000 -0.057587 0.000000 ) +( 0.161257 0.000000 0.151650 0.000000 -0.066218 0.000000 ) +( -0.026815 0.000000 0.057776 0.000000 0.057587 0.000000 ) +( -0.161257 0.000000 -0.151650 0.000000 0.066218 0.000000 ) +( 0.011695 0.000000 0.081513 0.000000 0.085294 0.000000 ) +( 0.030518 0.000000 0.029657 0.000000 -0.057218 0.000000 ) +( -0.011695 0.000000 -0.081513 0.000000 -0.085294 0.000000 ) +( -0.030518 0.000000 -0.029657 0.000000 0.057218 0.000000 ) +( -0.017980 0.000000 0.086377 0.000000 -0.147489 0.000000 ) +( -0.003976 0.000000 -0.129543 0.000000 -0.100440 0.000000 ) +( 0.017980 0.000000 -0.086377 0.000000 0.147489 0.000000 ) +( 0.003976 0.000000 0.129543 0.000000 0.100440 0.000000 ) + freq ( 23) = 33.11881758 [THz] = 1104.72484098 [cm-1] +( 0.001205 0.000000 0.024237 0.000000 0.099042 0.000000 ) +( 0.321021 0.000000 -0.102735 0.000000 0.141791 0.000000 ) +( -0.001205 0.000000 -0.024237 0.000000 -0.099042 0.000000 ) +( -0.321021 0.000000 0.102735 0.000000 -0.141791 0.000000 ) +( 0.037153 0.000000 -0.078066 0.000000 0.096438 0.000000 ) +( -0.127941 0.000000 0.026278 0.000000 -0.133027 0.000000 ) +( -0.037153 0.000000 0.078066 0.000000 -0.096438 0.000000 ) +( 0.127941 0.000000 -0.026278 0.000000 0.133027 0.000000 ) +( 0.031808 0.000000 -0.240433 0.000000 0.112989 0.000000 ) +( 0.181772 0.000000 -0.116453 0.000000 -0.057640 0.000000 ) +( -0.031808 0.000000 0.240433 0.000000 -0.112989 0.000000 ) +( -0.181772 0.000000 0.116453 0.000000 0.057640 0.000000 ) +( 0.106178 0.000000 -0.003639 0.000000 0.015016 0.000000 ) +( 0.068584 0.000000 0.196462 0.000000 0.056703 0.000000 ) +( -0.106178 0.000000 0.003639 0.000000 -0.015016 0.000000 ) +( -0.068584 0.000000 -0.196462 0.000000 -0.056703 0.000000 ) +( -0.092088 0.000000 -0.099159 0.000000 -0.140356 0.000000 ) +( -0.030437 0.000000 0.156823 0.000000 0.029021 0.000000 ) +( 0.092088 0.000000 0.099159 0.000000 0.140356 0.000000 ) +( 0.030437 0.000000 -0.156823 0.000000 -0.029021 0.000000 ) +( 0.095800 0.000000 0.011153 0.000000 0.006234 0.000000 ) +( 0.031914 0.000000 0.221693 0.000000 -0.030598 0.000000 ) +( -0.095800 0.000000 -0.011153 0.000000 -0.006234 0.000000 ) +( -0.031914 0.000000 -0.221693 0.000000 0.030598 0.000000 ) + freq ( 24) = 33.62231228 [THz] = 1121.51961634 [cm-1] +( 0.165942 0.000000 -0.032062 0.000000 -0.005249 0.000000 ) +( -0.091333 0.000000 -0.247641 0.000000 -0.214953 0.000000 ) +( 0.165942 0.000000 -0.032062 0.000000 -0.005249 0.000000 ) +( -0.091333 0.000000 -0.247641 0.000000 -0.214953 0.000000 ) +( 0.041440 0.000000 0.041678 0.000000 0.070011 0.000000 ) +( 0.069721 0.000000 0.139796 0.000000 -0.074055 0.000000 ) +( 0.041440 0.000000 0.041678 0.000000 0.070011 0.000000 ) +( 0.069721 0.000000 0.139796 0.000000 -0.074055 0.000000 ) +( -0.089942 0.000000 0.127561 0.000000 -0.077944 0.000000 ) +( -0.069811 0.000000 0.295277 0.000000 0.117069 0.000000 ) +( -0.089942 0.000000 0.127561 0.000000 -0.077944 0.000000 ) +( -0.069811 0.000000 0.295277 0.000000 0.117069 0.000000 ) +( -0.043294 0.000000 0.079493 0.000000 0.002533 0.000000 ) +( 0.098304 0.000000 -0.025949 0.000000 -0.036358 0.000000 ) +( -0.043294 0.000000 0.079493 0.000000 0.002533 0.000000 ) +( 0.098304 0.000000 -0.025949 0.000000 -0.036358 0.000000 ) +( 0.047173 0.000000 0.111666 0.000000 0.027810 0.000000 ) +( 0.137734 0.000000 -0.120365 0.000000 -0.191826 0.000000 ) +( 0.047173 0.000000 0.111666 0.000000 0.027810 0.000000 ) +( 0.137734 0.000000 -0.120365 0.000000 -0.191826 0.000000 ) +( -0.052785 0.000000 0.049722 0.000000 0.016136 0.000000 ) +( -0.087118 0.000000 -0.098342 0.000000 -0.229622 0.000000 ) +( -0.052785 0.000000 0.049722 0.000000 0.016136 0.000000 ) +( -0.087118 0.000000 -0.098342 0.000000 -0.229622 0.000000 ) + freq ( 25) = 34.13719551 [THz] = 1138.69427243 [cm-1] +( -0.028127 0.000000 -0.119546 0.000000 -0.035550 0.000000 ) +( 0.146666 0.000000 0.255347 0.000000 -0.110690 0.000000 ) +( 0.028127 0.000000 0.119546 0.000000 0.035550 0.000000 ) +( -0.146666 0.000000 -0.255347 0.000000 0.110690 0.000000 ) +( -0.040952 0.000000 0.129515 0.000000 -0.027818 0.000000 ) +( 0.026027 0.000000 -0.001348 0.000000 -0.195215 0.000000 ) +( 0.040952 0.000000 -0.129515 0.000000 0.027818 0.000000 ) +( -0.026027 0.000000 0.001348 0.000000 0.195215 0.000000 ) +( -0.046756 0.000000 0.117358 0.000000 0.125084 0.000000 ) +( -0.046641 0.000000 -0.202095 0.000000 -0.036919 0.000000 ) +( 0.046756 0.000000 -0.117358 0.000000 -0.125084 0.000000 ) +( 0.046641 0.000000 0.202095 0.000000 0.036919 0.000000 ) +( 0.073997 0.000000 0.288004 0.000000 -0.150989 0.000000 ) +( 0.016269 0.000000 0.141193 0.000000 -0.042986 0.000000 ) +( -0.073997 0.000000 -0.288004 0.000000 0.150989 0.000000 ) +( -0.016269 0.000000 -0.141193 0.000000 0.042986 0.000000 ) +( -0.036155 0.000000 0.171626 0.000000 -0.074411 0.000000 ) +( 0.012149 0.000000 -0.068362 0.000000 0.020721 0.000000 ) +( 0.036155 0.000000 -0.171626 0.000000 0.074411 0.000000 ) +( -0.012149 0.000000 0.068362 0.000000 -0.020721 0.000000 ) +( 0.031592 0.000000 0.138382 0.000000 -0.176403 0.000000 ) +( -0.031130 0.000000 -0.113344 0.000000 0.103878 0.000000 ) +( -0.031592 0.000000 -0.138382 0.000000 0.176403 0.000000 ) +( 0.031130 0.000000 0.113344 0.000000 -0.103878 0.000000 ) + freq ( 26) = 34.24556893 [THz] = 1142.30922030 [cm-1] +( 0.047374 0.000000 -0.108233 0.000000 -0.018060 0.000000 ) +( 0.264580 0.000000 -0.077679 0.000000 0.150772 0.000000 ) +( 0.047374 0.000000 -0.108233 0.000000 -0.018060 0.000000 ) +( 0.264580 0.000000 -0.077679 0.000000 0.150772 0.000000 ) +( -0.065746 0.000000 -0.018285 0.000000 0.062943 0.000000 ) +( -0.071977 0.000000 0.244288 0.000000 -0.082849 0.000000 ) +( -0.065746 0.000000 -0.018285 0.000000 0.062943 0.000000 ) +( -0.071977 0.000000 0.244288 0.000000 -0.082849 0.000000 ) +( -0.080436 0.000000 0.107627 0.000000 -0.016616 0.000000 ) +( 0.125686 0.000000 -0.042179 0.000000 -0.047392 0.000000 ) +( -0.080436 0.000000 0.107627 0.000000 -0.016616 0.000000 ) +( 0.125686 0.000000 -0.042179 0.000000 -0.047392 0.000000 ) +( -0.156138 0.000000 0.098127 0.000000 -0.127495 0.000000 ) +( -0.118189 0.000000 -0.046029 0.000000 0.115515 0.000000 ) +( -0.156138 0.000000 0.098127 0.000000 -0.127495 0.000000 ) +( -0.118189 0.000000 -0.046029 0.000000 0.115515 0.000000 ) +( 0.037511 0.000000 -0.226554 0.000000 0.133253 0.000000 ) +( -0.006159 0.000000 -0.173252 0.000000 0.099778 0.000000 ) +( 0.037511 0.000000 -0.226554 0.000000 0.133253 0.000000 ) +( -0.006159 0.000000 -0.173252 0.000000 0.099778 0.000000 ) +( -0.081545 0.000000 -0.155375 0.000000 -0.055911 0.000000 ) +( -0.077255 0.000000 -0.192933 0.000000 0.033944 0.000000 ) +( -0.081545 0.000000 -0.155375 0.000000 -0.055911 0.000000 ) +( -0.077255 0.000000 -0.192933 0.000000 0.033944 0.000000 ) + freq ( 27) = 34.40554464 [THz] = 1147.64543566 [cm-1] +( -0.103868 0.000000 -0.203207 0.000000 -0.002563 0.000000 ) +( -0.076157 0.000000 -0.251616 0.000000 -0.029951 0.000000 ) +( -0.103868 0.000000 -0.203207 0.000000 -0.002563 0.000000 ) +( -0.076157 0.000000 -0.251616 0.000000 -0.029951 0.000000 ) +( -0.006205 0.000000 0.162206 0.000000 -0.098312 0.000000 ) +( 0.086229 0.000000 -0.049439 0.000000 0.088482 0.000000 ) +( -0.006205 0.000000 0.162206 0.000000 -0.098312 0.000000 ) +( 0.086229 0.000000 -0.049439 0.000000 0.088482 0.000000 ) +( 0.119721 0.000000 -0.067391 0.000000 -0.030135 0.000000 ) +( -0.109907 0.000000 0.199171 0.000000 0.044429 0.000000 ) +( 0.119721 0.000000 -0.067391 0.000000 -0.030135 0.000000 ) +( -0.109907 0.000000 0.199171 0.000000 0.044429 0.000000 ) +( -0.181650 0.000000 0.023643 0.000000 0.000216 0.000000 ) +( -0.034235 0.000000 -0.252343 0.000000 -0.012452 0.000000 ) +( -0.181650 0.000000 0.023643 0.000000 0.000216 0.000000 ) +( -0.034235 0.000000 -0.252343 0.000000 -0.012452 0.000000 ) +( -0.043542 0.000000 -0.143495 0.000000 0.064089 0.000000 ) +( -0.088178 0.000000 0.052968 0.000000 0.119212 0.000000 ) +( -0.043542 0.000000 -0.143495 0.000000 0.064089 0.000000 ) +( -0.088178 0.000000 0.052968 0.000000 0.119212 0.000000 ) +( 0.030624 0.000000 0.117634 0.000000 0.050046 0.000000 ) +( 0.048712 0.000000 0.034971 0.000000 0.282584 0.000000 ) +( 0.030624 0.000000 0.117634 0.000000 0.050046 0.000000 ) +( 0.048712 0.000000 0.034971 0.000000 0.282584 0.000000 ) + freq ( 28) = 35.13517703 [THz] = 1171.98335251 [cm-1] +( -0.178874 0.000000 0.121175 0.000000 0.058505 0.000000 ) +( 0.051933 0.000000 -0.097722 0.000000 0.106856 0.000000 ) +( 0.178874 0.000000 -0.121175 0.000000 -0.058505 0.000000 ) +( -0.051933 0.000000 0.097722 0.000000 -0.106856 0.000000 ) +( 0.072851 0.000000 -0.041117 0.000000 -0.087789 0.000000 ) +( 0.144181 0.000000 0.175999 0.000000 0.153511 0.000000 ) +( -0.072851 0.000000 0.041117 0.000000 0.087789 0.000000 ) +( -0.144181 0.000000 -0.175999 0.000000 -0.153511 0.000000 ) +( 0.188457 0.000000 -0.125073 0.000000 0.019698 0.000000 ) +( -0.007751 0.000000 -0.080545 0.000000 -0.120538 0.000000 ) +( -0.188457 0.000000 0.125073 0.000000 -0.019698 0.000000 ) +( 0.007751 0.000000 0.080545 0.000000 0.120538 0.000000 ) +( 0.013884 0.000000 -0.002394 0.000000 0.110390 0.000000 ) +( -0.183395 0.000000 0.113544 0.000000 0.027299 0.000000 ) +( -0.013884 0.000000 0.002394 0.000000 -0.110390 0.000000 ) +( 0.183395 0.000000 -0.113544 0.000000 -0.027299 0.000000 ) +( -0.053913 0.000000 0.216584 0.000000 0.051071 0.000000 ) +( -0.036056 0.000000 -0.187198 0.000000 0.130682 0.000000 ) +( 0.053913 0.000000 -0.216584 0.000000 -0.051071 0.000000 ) +( 0.036056 0.000000 0.187198 0.000000 -0.130682 0.000000 ) +( 0.052939 0.000000 -0.062229 0.000000 0.051990 0.000000 ) +( -0.018507 0.000000 -0.130864 0.000000 0.266887 0.000000 ) +( -0.052939 0.000000 0.062229 0.000000 -0.051990 0.000000 ) +( 0.018507 0.000000 0.130864 0.000000 -0.266887 0.000000 ) + freq ( 29) = 36.14719123 [THz] = 1205.74051270 [cm-1] +( -0.133717 0.000000 0.221325 0.000000 0.047821 0.000000 ) +( 0.066219 0.000000 0.027490 0.000000 -0.054072 0.000000 ) +( -0.133717 0.000000 0.221325 0.000000 0.047821 0.000000 ) +( 0.066219 0.000000 0.027490 0.000000 -0.054072 0.000000 ) +( -0.016796 0.000000 -0.135815 0.000000 -0.045759 0.000000 ) +( -0.038648 0.000000 -0.098360 0.000000 -0.074609 0.000000 ) +( -0.016796 0.000000 -0.135815 0.000000 -0.045759 0.000000 ) +( -0.038648 0.000000 -0.098360 0.000000 -0.074609 0.000000 ) +( 0.018855 0.000000 -0.085686 0.000000 0.036218 0.000000 ) +( 0.173536 0.000000 -0.094815 0.000000 0.043916 0.000000 ) +( 0.018855 0.000000 -0.085686 0.000000 0.036218 0.000000 ) +( 0.173536 0.000000 -0.094815 0.000000 0.043916 0.000000 ) +( -0.135697 0.000000 0.106296 0.000000 -0.105876 0.000000 ) +( 0.168481 0.000000 -0.233678 0.000000 0.035641 0.000000 ) +( -0.135697 0.000000 0.106296 0.000000 -0.105876 0.000000 ) +( 0.168481 0.000000 -0.233678 0.000000 0.035641 0.000000 ) +( 0.064190 0.000000 0.030634 0.000000 0.219493 0.000000 ) +( -0.088934 0.000000 -0.025055 0.000000 -0.111876 0.000000 ) +( 0.064190 0.000000 0.030634 0.000000 0.219493 0.000000 ) +( -0.088934 0.000000 -0.025055 0.000000 -0.111876 0.000000 ) +( -0.038181 0.000000 0.269807 0.000000 0.141707 0.000000 ) +( 0.120051 0.000000 -0.137074 0.000000 -0.090420 0.000000 ) +( -0.038181 0.000000 0.269807 0.000000 0.141707 0.000000 ) +( 0.120051 0.000000 -0.137074 0.000000 -0.090420 0.000000 ) + freq ( 30) = 37.25991602 [THz] = 1242.85701632 [cm-1] +( 0.003121 -0.000000 0.288509 0.000000 -0.148711 0.000000 ) +( -0.067206 0.000000 0.139057 -0.000000 0.001577 -0.000000 ) +( -0.003121 0.000000 -0.288509 0.000000 0.148711 0.000000 ) +( 0.067206 -0.000000 -0.139057 0.000000 -0.001577 0.000000 ) +( -0.158949 0.000000 -0.053821 0.000000 -0.000610 0.000000 ) +( -0.096672 0.000000 0.081906 -0.000000 0.003653 -0.000000 ) +( 0.158949 -0.000000 0.053821 -0.000000 0.000610 -0.000000 ) +( 0.096672 -0.000000 -0.081906 0.000000 -0.003653 0.000000 ) +( 0.052908 -0.000000 0.173004 -0.000000 -0.077278 -0.000000 ) +( 0.181491 -0.000000 0.183604 -0.000000 0.020075 -0.000000 ) +( -0.052908 0.000000 -0.173004 0.000000 0.077278 0.000000 ) +( -0.181491 0.000000 -0.183604 0.000000 -0.020075 0.000000 ) +( 0.190917 -0.000000 -0.002743 0.000000 0.194702 0.000000 ) +( 0.041150 -0.000000 0.064410 -0.000000 0.131190 -0.000000 ) +( -0.190917 0.000000 0.002743 -0.000000 -0.194702 -0.000000 ) +( -0.041150 0.000000 -0.064410 0.000000 -0.131190 0.000000 ) +( 0.041016 -0.000000 -0.008868 0.000000 -0.150961 0.000000 ) +( -0.130484 0.000000 -0.018365 0.000000 -0.042089 0.000000 ) +( -0.041016 0.000000 0.008868 -0.000000 0.150961 -0.000000 ) +( 0.130484 -0.000000 0.018365 -0.000000 0.042089 -0.000000 ) +( -0.047466 0.000000 0.122743 -0.000000 -0.161141 -0.000000 ) +( 0.110880 -0.000000 0.045977 -0.000000 0.148330 -0.000000 ) +( 0.047466 -0.000000 -0.122743 0.000000 0.161141 0.000000 ) +( -0.110880 0.000000 -0.045977 0.000000 -0.148330 0.000000 ) + freq ( 31) = 37.74106259 [THz] = 1258.90633835 [cm-1] +( 0.032194 -0.000000 -0.106958 0.000000 -0.162113 0.000000 ) +( 0.239598 -0.000000 -0.052507 0.000000 0.004594 0.000000 ) +( -0.032194 0.000000 0.106958 -0.000000 0.162113 -0.000000 ) +( -0.239598 0.000000 0.052507 -0.000000 -0.004594 -0.000000 ) +( -0.179583 0.000000 -0.180579 0.000000 0.002334 0.000000 ) +( -0.005528 0.000000 -0.032854 0.000000 -0.183393 0.000000 ) +( 0.179583 -0.000000 0.180579 -0.000000 -0.002334 -0.000000 ) +( 0.005528 -0.000000 0.032854 -0.000000 0.183393 -0.000000 ) +( 0.109318 -0.000000 0.114903 -0.000000 0.028737 -0.000000 ) +( -0.044008 0.000000 0.042317 -0.000000 -0.007600 -0.000000 ) +( -0.109318 0.000000 -0.114903 0.000000 -0.028737 0.000000 ) +( 0.044008 -0.000000 -0.042317 0.000000 0.007600 0.000000 ) +( 0.078931 -0.000000 -0.191659 0.000000 0.077432 0.000000 ) +( -0.062240 0.000000 0.071870 -0.000000 0.033036 -0.000000 ) +( -0.078931 0.000000 0.191659 -0.000000 -0.077432 -0.000000 ) +( 0.062240 -0.000000 -0.071870 0.000000 -0.033036 0.000000 ) +( 0.160229 -0.000000 0.016170 -0.000000 0.194743 -0.000000 ) +( 0.055690 -0.000000 0.172287 -0.000000 0.116784 -0.000000 ) +( -0.160229 0.000000 -0.016170 0.000000 -0.194743 0.000000 ) +( -0.055690 0.000000 -0.172287 0.000000 -0.116784 0.000000 ) +( -0.120216 0.000000 0.052493 -0.000000 0.109377 -0.000000 ) +( -0.081036 0.000000 -0.257954 0.000000 -0.006049 0.000000 ) +( 0.120216 -0.000000 -0.052493 0.000000 -0.109377 0.000000 ) +( 0.081036 -0.000000 0.257954 0.000000 0.006049 0.000000 ) + freq ( 32) = 38.55161273 [THz] = 1285.94338085 [cm-1] +( 0.174146 -0.000000 0.036984 -0.000000 -0.052785 -0.000000 ) +( 0.004294 -0.000000 -0.085738 0.000000 -0.026657 0.000000 ) +( 0.174146 -0.000000 0.036984 -0.000000 -0.052785 -0.000000 ) +( 0.004294 -0.000000 -0.085738 0.000000 -0.026657 0.000000 ) +( 0.009630 -0.000000 -0.100423 0.000000 0.112170 0.000000 ) +( -0.182346 0.000000 -0.006142 0.000000 -0.121450 0.000000 ) +( 0.009630 -0.000000 -0.100423 0.000000 0.112170 0.000000 ) +( -0.182346 0.000000 -0.006142 0.000000 -0.121450 0.000000 ) +( 0.149077 -0.000000 0.177179 -0.000000 -0.042264 -0.000000 ) +( 0.071635 -0.000000 -0.046653 0.000000 0.078864 0.000000 ) +( 0.149077 -0.000000 0.177179 -0.000000 -0.042264 -0.000000 ) +( 0.071635 -0.000000 -0.046653 0.000000 0.078864 0.000000 ) +( 0.165361 -0.000000 -0.063205 0.000000 0.216217 0.000000 ) +( 0.034508 -0.000000 -0.157275 0.000000 0.119860 0.000000 ) +( 0.165361 -0.000000 -0.063205 0.000000 0.216217 0.000000 ) +( 0.034508 -0.000000 -0.157275 0.000000 0.119860 0.000000 ) +( -0.078068 0.000000 -0.115488 0.000000 -0.140806 0.000000 ) +( -0.121945 0.000000 -0.192276 0.000000 0.030768 0.000000 ) +( -0.078068 0.000000 -0.115488 0.000000 -0.140806 0.000000 ) +( -0.121945 0.000000 -0.192276 0.000000 0.030768 0.000000 ) +( 0.077678 -0.000000 0.209927 -0.000000 -0.186798 -0.000000 ) +( 0.093083 -0.000000 0.100070 -0.000000 0.060076 -0.000000 ) +( 0.077678 -0.000000 0.209927 -0.000000 -0.186798 -0.000000 ) +( 0.093083 -0.000000 0.100070 -0.000000 0.060076 -0.000000 ) + freq ( 33) = 39.28216123 [THz] = 1310.31185577 [cm-1] +( -0.100309 0.000000 0.069079 -0.000000 0.227205 -0.000000 ) +( 0.108540 -0.000000 -0.009357 0.000000 -0.053544 0.000000 ) +( -0.100309 0.000000 0.069079 -0.000000 0.227205 -0.000000 ) +( 0.108540 -0.000000 -0.009357 0.000000 -0.053544 0.000000 ) +( 0.110498 -0.000000 -0.137726 0.000000 0.056047 0.000000 ) +( 0.067439 -0.000000 -0.014857 0.000000 -0.100478 0.000000 ) +( 0.110498 -0.000000 -0.137726 0.000000 0.056047 0.000000 ) +( 0.067439 -0.000000 -0.014857 0.000000 -0.100478 0.000000 ) +( -0.015110 0.000000 0.311756 0.000000 0.156386 0.000000 ) +( -0.154152 0.000000 -0.031302 0.000000 -0.018774 0.000000 ) +( -0.015110 0.000000 0.311756 -0.000000 0.156386 -0.000000 ) +( -0.154152 0.000000 -0.031302 0.000000 -0.018774 0.000000 ) +( -0.150261 0.000000 0.108295 -0.000000 -0.224281 -0.000000 ) +( 0.004741 -0.000000 -0.012415 0.000000 -0.097487 0.000000 ) +( -0.150261 0.000000 0.108295 -0.000000 -0.224281 -0.000000 ) +( 0.004741 -0.000000 -0.012415 0.000000 -0.097487 0.000000 ) +( -0.134183 0.000000 0.120248 -0.000000 -0.040453 -0.000000 ) +( 0.034723 -0.000000 -0.026406 0.000000 0.092938 0.000000 ) +( -0.134183 0.000000 0.120248 -0.000000 -0.040453 -0.000000 ) +( 0.034723 -0.000000 -0.026406 0.000000 0.092938 0.000000 ) +( 0.110026 -0.000000 0.034350 -0.000000 -0.078321 -0.000000 ) +( -0.071694 0.000000 0.229959 -0.000000 0.079259 -0.000000 ) +( 0.110026 -0.000000 0.034350 -0.000000 -0.078321 -0.000000 ) +( -0.071694 0.000000 0.229959 -0.000000 0.079259 -0.000000 ) + freq ( 34) = 40.47964591 [THz] = 1350.25564497 [cm-1] +( 0.209323 0.000000 -0.083768 0.000000 -0.092589 0.000000 ) +( -0.125777 0.000000 -0.059166 0.000000 -0.033347 0.000000 ) +( -0.209323 0.000000 0.083768 0.000000 0.092589 0.000000 ) +( 0.125777 0.000000 0.059166 0.000000 0.033347 0.000000 ) +( 0.142118 0.000000 -0.182694 0.000000 -0.025070 0.000000 ) +( 0.121646 0.000000 -0.153810 0.000000 0.151996 0.000000 ) +( -0.142118 0.000000 0.182694 0.000000 0.025070 0.000000 ) +( -0.121646 0.000000 0.153810 0.000000 -0.151996 0.000000 ) +( 0.172874 0.000000 0.097325 0.000000 -0.012035 0.000000 ) +( 0.034799 0.000000 -0.009935 0.000000 0.067655 0.000000 ) +( -0.172874 0.000000 -0.097325 0.000000 0.012035 0.000000 ) +( -0.034799 0.000000 0.009935 0.000000 -0.067655 0.000000 ) +( 0.062395 0.000000 0.239456 0.000000 0.094881 0.000000 ) +( 0.001392 0.000000 0.311293 0.000000 0.052478 0.000000 ) +( -0.062395 0.000000 -0.239456 0.000000 -0.094881 0.000000 ) +( -0.001392 0.000000 -0.311293 0.000000 -0.052478 0.000000 ) +( -0.052535 0.000000 -0.068248 0.000000 -0.092024 0.000000 ) +( 0.014592 0.000000 -0.043536 0.000000 0.059518 0.000000 ) +( 0.052535 0.000000 0.068248 0.000000 0.092024 0.000000 ) +( -0.014592 0.000000 0.043536 0.000000 -0.059518 0.000000 ) +( 0.093517 0.000000 0.013443 0.000000 0.097211 0.000000 ) +( 0.006101 0.000000 -0.082275 0.000000 -0.205907 0.000000 ) +( -0.093517 0.000000 -0.013443 0.000000 -0.097211 0.000000 ) +( -0.006101 0.000000 0.082275 0.000000 0.205907 0.000000 ) + freq ( 35) = 40.88835256 [THz] = 1363.88863122 [cm-1] +( -0.204281 0.000000 -0.167658 0.000000 0.080231 0.000000 ) +( -0.182482 0.000000 0.092199 0.000000 -0.048983 0.000000 ) +( -0.204281 0.000000 -0.167658 0.000000 0.080231 0.000000 ) +( -0.182482 0.000000 0.092199 0.000000 -0.048983 0.000000 ) +( -0.163246 0.000000 -0.224239 0.000000 0.047192 0.000000 ) +( 0.097347 0.000000 0.235371 0.000000 0.176768 0.000000 ) +( -0.163246 0.000000 -0.224239 0.000000 0.047192 0.000000 ) +( 0.097347 0.000000 0.235371 0.000000 0.176768 0.000000 ) +( -0.201554 0.000000 -0.050491 0.000000 -0.042952 0.000000 ) +( -0.065349 0.000000 -0.072311 0.000000 0.060351 0.000000 ) +( -0.201554 0.000000 -0.050491 0.000000 -0.042952 0.000000 ) +( -0.065349 0.000000 -0.072311 0.000000 0.060351 0.000000 ) +( 0.072617 0.000000 -0.012413 0.000000 0.002076 0.000000 ) +( -0.015335 0.000000 -0.180025 0.000000 -0.038467 0.000000 ) +( 0.072617 0.000000 -0.012413 0.000000 0.002076 0.000000 ) +( -0.015335 0.000000 -0.180025 0.000000 -0.038467 0.000000 ) +( 0.014451 0.000000 -0.101472 0.000000 0.006463 0.000000 ) +( -0.033025 0.000000 -0.031059 0.000000 0.055128 0.000000 ) +( 0.014451 0.000000 -0.101472 0.000000 0.006463 0.000000 ) +( -0.033025 0.000000 -0.031059 0.000000 0.055128 0.000000 ) +( -0.054798 0.000000 0.041514 0.000000 -0.163464 0.000000 ) +( 0.087191 0.000000 0.121880 0.000000 -0.192302 0.000000 ) +( -0.054798 0.000000 0.041514 0.000000 -0.163464 0.000000 ) +( 0.087191 0.000000 0.121880 0.000000 -0.192302 0.000000 ) + freq ( 36) = 41.86432297 [THz] = 1396.44350007 [cm-1] +( -0.163726 0.000000 -0.158291 0.000000 0.105816 0.000000 ) +( -0.083375 0.000000 0.062912 -0.000000 0.093409 -0.000000 ) +( 0.163726 -0.000000 0.158291 -0.000000 -0.105816 -0.000000 ) +( 0.083375 -0.000000 -0.062912 0.000000 -0.093409 0.000000 ) +( 0.078335 -0.000000 0.007600 -0.000000 -0.143262 -0.000000 ) +( -0.106002 0.000000 0.089712 -0.000000 0.104341 -0.000000 ) +( -0.078335 0.000000 -0.007600 0.000000 0.143262 0.000000 ) +( 0.106002 -0.000000 -0.089712 0.000000 -0.104341 0.000000 ) +( -0.210593 0.000000 0.039412 -0.000000 0.001193 -0.000000 ) +( 0.167608 -0.000000 0.073191 -0.000000 0.059036 -0.000000 ) +( 0.210593 -0.000000 -0.039412 0.000000 -0.001193 0.000000 ) +( -0.167608 0.000000 -0.073191 0.000000 -0.059036 0.000000 ) +( -0.093939 0.000000 -0.064798 0.000000 -0.177814 0.000000 ) +( -0.016505 0.000000 0.160843 -0.000000 0.165508 -0.000000 ) +( 0.093939 -0.000000 0.064798 -0.000000 0.177814 -0.000000 ) +( 0.016505 -0.000000 -0.160843 0.000000 -0.165508 0.000000 ) +( -0.011620 0.000000 -0.122328 0.000000 0.035041 0.000000 ) +( -0.097341 0.000000 0.041080 -0.000000 0.080632 -0.000000 ) +( 0.011620 -0.000000 0.122328 -0.000000 -0.035041 -0.000000 ) +( 0.097341 -0.000000 -0.041080 0.000000 -0.080632 0.000000 ) +( -0.016429 0.000000 0.291468 0.000000 0.177300 0.000000 ) +( 0.081461 -0.000000 -0.138462 0.000000 0.054251 0.000000 ) +( 0.016429 -0.000000 -0.291468 0.000000 -0.177300 0.000000 ) +( -0.081461 0.000000 0.138462 -0.000000 -0.054251 -0.000000 ) + freq ( 37) = 43.30992274 [THz] = 1444.66351778 [cm-1] +( 0.061973 0.000000 -0.054065 0.000000 0.039642 0.000000 ) +( -0.071567 0.000000 -0.113488 0.000000 0.070561 0.000000 ) +( 0.061973 0.000000 -0.054065 0.000000 0.039642 0.000000 ) +( -0.071567 0.000000 -0.113488 0.000000 0.070561 0.000000 ) +( 0.091210 0.000000 0.012529 0.000000 0.004824 0.000000 ) +( -0.178566 0.000000 -0.006710 0.000000 0.036475 0.000000 ) +( 0.091210 0.000000 0.012529 0.000000 0.004824 0.000000 ) +( -0.178566 0.000000 -0.006710 0.000000 0.036475 0.000000 ) +( -0.059246 0.000000 -0.010175 0.000000 -0.083300 0.000000 ) +( 0.184979 0.000000 0.021090 0.000000 -0.098872 0.000000 ) +( -0.059246 0.000000 -0.010175 0.000000 -0.083300 0.000000 ) +( 0.184979 0.000000 0.021090 0.000000 -0.098872 0.000000 ) +( -0.130926 0.000000 -0.140375 0.000000 -0.014943 0.000000 ) +( -0.262220 0.000000 -0.042795 0.000000 0.128157 0.000000 ) +( -0.130926 0.000000 -0.140375 0.000000 -0.014943 0.000000 ) +( -0.262220 0.000000 -0.042795 0.000000 0.128157 0.000000 ) +( -0.016166 0.000000 0.151739 0.000000 0.094658 0.000000 ) +( -0.009791 0.000000 -0.018875 0.000000 0.095607 0.000000 ) +( -0.016166 0.000000 0.151739 0.000000 0.094658 0.000000 ) +( -0.009791 0.000000 -0.018875 0.000000 0.095607 0.000000 ) +( 0.039107 0.000000 0.022400 0.000000 0.229926 0.000000 ) +( 0.019530 0.000000 0.316979 0.000000 -0.224176 0.000000 ) +( 0.039107 0.000000 0.022400 0.000000 0.229926 0.000000 ) +( 0.019530 0.000000 0.316979 0.000000 -0.224176 0.000000 ) + freq ( 38) = 43.55059253 [THz] = 1452.69139812 [cm-1] +( 0.010961 -0.000000 -0.169237 0.000000 -0.017210 0.000000 ) +( -0.102057 0.000000 -0.061526 0.000000 0.156463 0.000000 ) +( -0.010961 0.000000 0.169237 -0.000000 0.017210 -0.000000 ) +( 0.102057 -0.000000 0.061526 -0.000000 -0.156463 -0.000000 ) +( -0.031218 0.000000 0.019100 -0.000000 0.051727 -0.000000 ) +( -0.145372 0.000000 -0.026309 0.000000 0.122565 0.000000 ) +( 0.031218 -0.000000 -0.019100 0.000000 -0.051727 0.000000 ) +( 0.145372 -0.000000 0.026309 -0.000000 -0.122565 -0.000000 ) +( 0.087915 -0.000000 0.073855 -0.000000 0.165016 -0.000000 ) +( 0.150725 -0.000000 -0.083439 0.000000 -0.124297 0.000000 ) +( -0.087915 0.000000 -0.073855 0.000000 -0.165016 0.000000 ) +( -0.150725 0.000000 0.083439 -0.000000 0.124297 -0.000000 ) +( 0.059286 -0.000000 -0.145954 0.000000 -0.058093 0.000000 ) +( -0.262765 0.000000 -0.166929 0.000000 0.062790 0.000000 ) +( -0.059286 0.000000 0.145954 -0.000000 0.058093 -0.000000 ) +( 0.262765 0.000000 0.166929 -0.000000 -0.062790 -0.000000 ) +( -0.013599 0.000000 0.035682 -0.000000 -0.239953 -0.000000 ) +( 0.052608 -0.000000 -0.010069 0.000000 0.021580 0.000000 ) +( 0.013599 -0.000000 -0.035682 0.000000 0.239953 0.000000 ) +( -0.052608 0.000000 0.010069 -0.000000 -0.021580 -0.000000 ) +( 0.007328 -0.000000 -0.001649 0.000000 -0.253725 0.000000 ) +( -0.071809 0.000000 -0.140104 0.000000 -0.158811 0.000000 ) +( -0.007328 0.000000 0.001649 -0.000000 0.253725 -0.000000 ) +( 0.071809 -0.000000 0.140104 -0.000000 0.158811 -0.000000 ) + freq ( 39) = 43.96554036 [THz] = 1466.53256760 [cm-1] +( 0.094502 -0.000000 -0.042915 0.000000 -0.065127 0.000000 ) +( 0.016212 -0.000000 0.149811 -0.000000 -0.120133 -0.000000 ) +( 0.094502 -0.000000 -0.042915 0.000000 -0.065127 0.000000 ) +( 0.016212 -0.000000 0.149811 -0.000000 -0.120133 -0.000000 ) +( 0.010349 -0.000000 -0.078011 0.000000 0.005507 0.000000 ) +( 0.097452 -0.000000 0.004821 -0.000000 -0.169036 -0.000000 ) +( 0.010349 -0.000000 -0.078011 0.000000 0.005507 0.000000 ) +( 0.097452 -0.000000 0.004821 -0.000000 -0.169036 -0.000000 ) +( 0.028369 -0.000000 -0.017101 0.000000 -0.142407 0.000000 ) +( -0.210325 0.000000 -0.147724 0.000000 0.047838 0.000000 ) +( 0.028369 -0.000000 -0.017101 0.000000 -0.142407 0.000000 ) +( -0.210325 0.000000 -0.147724 0.000000 0.047838 0.000000 ) +( -0.063607 0.000000 -0.244780 0.000000 0.084766 0.000000 ) +( 0.098583 -0.000000 0.033243 -0.000000 -0.094293 -0.000000 ) +( -0.063607 0.000000 -0.244780 0.000000 0.084766 0.000000 ) +( 0.098583 -0.000000 0.033243 -0.000000 -0.094293 -0.000000 ) +( 0.094223 -0.000000 -0.112519 0.000000 0.258090 0.000000 ) +( 0.085772 -0.000000 -0.191938 0.000000 0.061168 0.000000 ) +( 0.094223 -0.000000 -0.112519 0.000000 0.258090 0.000000 ) +( 0.085772 -0.000000 -0.191938 0.000000 0.061168 0.000000 ) +( -0.064060 0.000000 0.001206 -0.000000 0.201299 -0.000000 ) +( -0.099090 0.000000 0.145967 -0.000000 0.105378 -0.000000 ) +( -0.064060 0.000000 0.001206 -0.000000 0.201299 -0.000000 ) +( -0.099090 0.000000 0.145967 -0.000000 0.105378 -0.000000 ) + freq ( 40) = 44.08610505 [THz] = 1470.55417284 [cm-1] +( 0.104911 0.000000 0.033106 0.000000 -0.089662 0.000000 ) +( 0.024756 0.000000 0.137183 0.000000 0.109237 0.000000 ) +( -0.104911 0.000000 -0.033106 0.000000 0.089662 0.000000 ) +( -0.024756 0.000000 -0.137183 0.000000 -0.109237 0.000000 ) +( -0.114212 0.000000 0.167517 0.000000 0.066658 0.000000 ) +( -0.143286 0.000000 0.021606 0.000000 0.038802 0.000000 ) +( 0.114212 0.000000 -0.167517 0.000000 -0.066658 0.000000 ) +( 0.143286 0.000000 -0.021606 0.000000 -0.038802 0.000000 ) +( 0.033159 0.000000 -0.057685 0.000000 -0.138055 0.000000 ) +( 0.293538 0.000000 -0.211048 0.000000 -0.044555 0.000000 ) +( -0.033159 0.000000 0.057685 0.000000 0.138055 0.000000 ) +( -0.293538 0.000000 0.211048 0.000000 0.044555 0.000000 ) +( -0.091306 0.000000 0.131240 0.000000 0.049996 0.000000 ) +( -0.020935 0.000000 -0.022529 0.000000 0.145954 0.000000 ) +( 0.091306 0.000000 -0.131240 0.000000 -0.049996 0.000000 ) +( 0.020935 0.000000 0.022529 0.000000 -0.145954 0.000000 ) +( 0.099359 0.000000 0.102940 0.000000 0.250014 0.000000 ) +( 0.021412 0.000000 -0.150162 0.000000 -0.049591 0.000000 ) +( -0.099359 0.000000 -0.102940 0.000000 -0.250014 0.000000 ) +( -0.021412 0.000000 0.150162 0.000000 0.049591 0.000000 ) +( -0.072745 0.000000 -0.069628 0.000000 0.162005 0.000000 ) +( -0.029891 0.000000 0.025431 0.000000 -0.166092 0.000000 ) +( 0.072745 0.000000 0.069628 0.000000 -0.162005 0.000000 ) +( 0.029891 0.000000 -0.025431 0.000000 0.166092 0.000000 ) + freq ( 41) = 46.11092394 [THz] = 1538.09486104 [cm-1] +( 0.009751 0.000000 -0.039507 0.000000 0.011647 0.000000 ) +( 0.020720 0.000000 0.129640 0.000000 -0.022559 0.000000 ) +( -0.009751 0.000000 0.039507 0.000000 -0.011647 0.000000 ) +( -0.020720 0.000000 -0.129640 0.000000 0.022559 0.000000 ) +( -0.060664 0.000000 -0.296829 0.000000 0.049758 0.000000 ) +( -0.063509 0.000000 0.150129 0.000000 -0.068933 0.000000 ) +( 0.060664 0.000000 0.296829 0.000000 -0.049758 0.000000 ) +( 0.063509 0.000000 -0.150129 0.000000 0.068933 0.000000 ) +( 0.012933 0.000000 0.108468 0.000000 -0.057543 0.000000 ) +( -0.137337 0.000000 -0.289207 0.000000 0.042108 0.000000 ) +( -0.012933 0.000000 -0.108468 0.000000 0.057543 0.000000 ) +( 0.137337 0.000000 0.289207 0.000000 -0.042108 0.000000 ) +( -0.095399 0.000000 -0.120659 0.000000 0.034714 0.000000 ) +( -0.052574 0.000000 -0.048098 0.000000 0.003455 0.000000 ) +( 0.095399 0.000000 0.120659 0.000000 -0.034714 0.000000 ) +( 0.052574 0.000000 0.048098 0.000000 -0.003455 0.000000 ) +( -0.039969 0.000000 -0.291116 0.000000 -0.072402 0.000000 ) +( -0.004943 0.000000 -0.320026 0.000000 -0.013093 0.000000 ) +( 0.039969 0.000000 0.291116 0.000000 0.072402 0.000000 ) +( 0.004943 0.000000 0.320026 0.000000 0.013093 0.000000 ) +( 0.018581 0.000000 0.028173 0.000000 0.048665 0.000000 ) +( -0.009165 0.000000 0.078412 0.000000 0.038257 0.000000 ) +( -0.018581 0.000000 -0.028173 0.000000 -0.048665 0.000000 ) +( 0.009165 0.000000 -0.078412 0.000000 -0.038257 0.000000 ) + freq ( 42) = 47.59931728 [THz] = 1587.74231866 [cm-1] +( -0.020222 0.000000 -0.304769 0.000000 -0.034756 0.000000 ) +( -0.019382 0.000000 0.187220 -0.000000 0.055022 -0.000000 ) +( -0.020222 0.000000 -0.304769 0.000000 -0.034756 0.000000 ) +( -0.019382 0.000000 0.187220 -0.000000 0.055022 -0.000000 ) +( -0.128406 0.000000 -0.023295 0.000000 0.029997 0.000000 ) +( -0.024844 0.000000 -0.243624 0.000000 0.057925 0.000000 ) +( -0.128406 0.000000 -0.023295 0.000000 0.029997 0.000000 ) +( -0.024844 0.000000 -0.243624 0.000000 0.057925 0.000000 ) +( 0.033990 -0.000000 0.241525 -0.000000 -0.041733 -0.000000 ) +( -0.074517 0.000000 0.019825 -0.000000 0.005006 -0.000000 ) +( 0.033990 -0.000000 0.241525 -0.000000 -0.041733 -0.000000 ) +( -0.074517 0.000000 0.019825 -0.000000 0.005006 -0.000000 ) +( -0.049343 0.000000 0.134731 -0.000000 0.007458 -0.000000 ) +( -0.145373 0.000000 0.206419 -0.000000 0.049877 -0.000000 ) +( -0.049343 0.000000 0.134731 -0.000000 0.007458 -0.000000 ) +( -0.145373 0.000000 0.206419 -0.000000 0.049877 -0.000000 ) +( 0.018459 -0.000000 -0.051580 0.000000 0.028509 0.000000 ) +( 0.014711 -0.000000 -0.009874 0.000000 -0.041173 0.000000 ) +( 0.018459 -0.000000 -0.051580 0.000000 0.028509 0.000000 ) +( 0.014711 -0.000000 -0.009874 0.000000 -0.041173 0.000000 ) +( -0.003993 0.000000 0.307458 -0.000000 0.075310 -0.000000 ) +( -0.012072 0.000000 -0.124376 0.000000 -0.100289 0.000000 ) +( -0.003993 0.000000 0.307458 0.000000 0.075310 0.000000 ) +( -0.012072 0.000000 -0.124376 0.000000 -0.100289 0.000000 ) + freq ( 43) = 50.78717029 [THz] = 1694.07764919 [cm-1] +( 0.161703 -0.000000 -0.011518 0.000000 0.018681 0.000000 ) +( 0.076520 -0.000000 0.026926 -0.000000 0.169132 -0.000000 ) +( 0.161703 -0.000000 -0.011518 0.000000 0.018681 0.000000 ) +( 0.076520 -0.000000 0.026926 -0.000000 0.169132 -0.000000 ) +( 0.165644 -0.000000 -0.031410 0.000000 0.050465 0.000000 ) +( 0.131714 -0.000000 0.019350 -0.000000 0.198804 -0.000000 ) +( 0.165644 -0.000000 -0.031410 0.000000 0.050465 0.000000 ) +( 0.131714 -0.000000 0.019350 -0.000000 0.198804 -0.000000 ) +( 0.376890 0.000000 -0.074755 0.000000 0.178433 0.000000 ) +( -0.094154 0.000000 -0.030081 0.000000 0.039788 0.000000 ) +( 0.376890 -0.000000 -0.074755 0.000000 0.178433 0.000000 ) +( -0.094154 0.000000 -0.030081 0.000000 0.039788 0.000000 ) +( -0.065846 0.000000 -0.008556 0.000000 0.031152 0.000000 ) +( -0.052898 0.000000 -0.082031 0.000000 0.002017 0.000000 ) +( -0.065846 0.000000 -0.008556 0.000000 0.031152 0.000000 ) +( -0.052898 0.000000 -0.082031 0.000000 0.002017 0.000000 ) +( 0.055232 -0.000000 -0.045639 0.000000 0.175407 0.000000 ) +( 0.055624 -0.000000 0.052391 -0.000000 -0.109482 -0.000000 ) +( 0.055232 -0.000000 -0.045639 0.000000 0.175407 0.000000 ) +( 0.055624 -0.000000 0.052391 -0.000000 -0.109482 -0.000000 ) +( -0.046933 0.000000 0.009303 -0.000000 -0.187619 -0.000000 ) +( -0.070470 0.000000 0.064591 -0.000000 -0.209466 -0.000000 ) +( -0.046933 0.000000 0.009303 -0.000000 -0.187619 -0.000000 ) +( -0.070470 0.000000 0.064591 -0.000000 -0.209466 -0.000000 ) + freq ( 44) = 51.37142342 [THz] = 1713.56623575 [cm-1] +( 0.026038 0.000000 -0.096638 0.000000 0.102749 0.000000 ) +( 0.147264 0.000000 0.094870 0.000000 0.083764 0.000000 ) +( 0.026038 0.000000 -0.096638 0.000000 0.102749 0.000000 ) +( 0.147264 0.000000 0.094870 0.000000 0.083764 0.000000 ) +( 0.337312 0.000000 -0.004740 0.000000 -0.100710 0.000000 ) +( 0.009817 0.000000 -0.039783 0.000000 0.046098 0.000000 ) +( 0.337312 0.000000 -0.004740 0.000000 -0.100710 0.000000 ) +( 0.009817 0.000000 -0.039783 0.000000 0.046098 0.000000 ) +( -0.239932 0.000000 0.026104 0.000000 -0.044915 0.000000 ) +( -0.059987 0.000000 0.112111 0.000000 0.139320 0.000000 ) +( -0.239932 0.000000 0.026104 0.000000 -0.044915 0.000000 ) +( -0.059987 0.000000 0.112111 0.000000 0.139320 0.000000 ) +( 0.237995 0.000000 0.131365 0.000000 0.051721 0.000000 ) +( 0.029533 0.000000 -0.016887 0.000000 0.111325 0.000000 ) +( 0.237995 0.000000 0.131365 0.000000 0.051721 0.000000 ) +( 0.029533 0.000000 -0.016887 0.000000 0.111325 0.000000 ) +( -0.027939 0.000000 -0.095043 0.000000 0.177840 0.000000 ) +( -0.120777 0.000000 0.003809 0.000000 -0.163989 0.000000 ) +( -0.027939 0.000000 -0.095043 0.000000 0.177840 0.000000 ) +( -0.120777 0.000000 0.003809 0.000000 -0.163989 0.000000 ) +( 0.095870 0.000000 -0.079549 0.000000 0.070609 0.000000 ) +( 0.121926 0.000000 0.081028 0.000000 0.055994 0.000000 ) +( 0.095870 0.000000 -0.079549 0.000000 0.070609 0.000000 ) +( 0.121926 0.000000 0.081028 0.000000 0.055994 0.000000 ) + freq ( 45) = 52.96963021 [THz] = 1766.87667567 [cm-1] +( 0.022072 -0.000000 -0.092799 0.000000 0.109213 0.000000 ) +( -0.192378 0.000000 0.036038 -0.000000 -0.191459 -0.000000 ) +( 0.022072 -0.000000 -0.092799 0.000000 0.109213 0.000000 ) +( -0.192378 0.000000 0.036038 -0.000000 -0.191459 -0.000000 ) +( 0.211026 -0.000000 -0.010003 0.000000 -0.026608 0.000000 ) +( 0.027262 -0.000000 -0.043898 0.000000 -0.043554 0.000000 ) +( 0.211026 -0.000000 -0.010003 0.000000 -0.026608 0.000000 ) +( 0.027262 -0.000000 -0.043898 0.000000 -0.043554 0.000000 ) +( 0.028546 -0.000000 0.020283 -0.000000 0.084120 -0.000000 ) +( 0.283554 -0.000000 0.048589 -0.000000 -0.098821 -0.000000 ) +( 0.028546 -0.000000 0.020283 -0.000000 0.084120 -0.000000 ) +( 0.283554 -0.000000 0.048589 -0.000000 -0.098821 -0.000000 ) +( 0.124563 -0.000000 0.058872 -0.000000 0.037632 -0.000000 ) +( 0.064609 -0.000000 0.097095 -0.000000 -0.029456 -0.000000 ) +( 0.124563 -0.000000 0.058872 -0.000000 0.037632 -0.000000 ) +( 0.064609 -0.000000 0.097095 -0.000000 -0.029456 -0.000000 ) +( 0.053009 -0.000000 -0.018989 0.000000 0.229790 0.000000 ) +( 0.073960 -0.000000 0.033246 -0.000000 0.339280 -0.000000 ) +( 0.053009 -0.000000 -0.018989 0.000000 0.229790 0.000000 ) +( 0.073960 -0.000000 0.033246 -0.000000 0.339280 -0.000000 ) +( -0.046674 0.000000 0.032532 -0.000000 -0.158921 -0.000000 ) +( -0.057199 0.000000 -0.091737 0.000000 0.023716 0.000000 ) +( -0.046674 0.000000 0.032532 -0.000000 -0.158921 -0.000000 ) +( -0.057199 0.000000 -0.091737 0.000000 0.023716 0.000000 ) + freq ( 46) = 53.14190137 [THz] = 1772.62302322 [cm-1] +( 0.075723 -0.000000 -0.001188 0.000000 0.083417 0.000000 ) +( -0.199748 0.000000 -0.032667 0.000000 -0.347371 0.000000 ) +( -0.075723 0.000000 0.001188 -0.000000 -0.083417 -0.000000 ) +( 0.199748 -0.000000 0.032667 -0.000000 0.347371 -0.000000 ) +( 0.057815 -0.000000 0.001218 -0.000000 0.036191 -0.000000 ) +( -0.118237 0.000000 -0.022698 0.000000 -0.221914 0.000000 ) +( -0.057815 0.000000 -0.001218 0.000000 -0.036191 0.000000 ) +( 0.118237 -0.000000 0.022698 -0.000000 0.221914 -0.000000 ) +( 0.141191 -0.000000 0.002437 -0.000000 0.041071 -0.000000 ) +( 0.208089 -0.000000 -0.016802 0.000000 -0.026061 0.000000 ) +( -0.141191 0.000000 -0.002437 0.000000 -0.041071 0.000000 ) +( -0.208089 0.000000 0.016802 -0.000000 0.026061 -0.000000 ) +( -0.138914 0.000000 -0.047120 0.000000 0.006610 0.000000 ) +( -0.004550 0.000000 -0.060925 0.000000 0.034890 0.000000 ) +( 0.138914 -0.000000 0.047120 -0.000000 -0.006610 -0.000000 ) +( 0.004550 -0.000000 0.060925 -0.000000 -0.034890 -0.000000 ) +( -0.064974 0.000000 0.036273 -0.000000 0.014807 -0.000000 ) +( -0.024780 0.000000 0.032965 -0.000000 0.373870 -0.000000 ) +( 0.064974 -0.000000 -0.036273 0.000000 -0.014807 0.000000 ) +( 0.024780 -0.000000 -0.032965 0.000000 -0.373870 0.000000 ) +( 0.024143 -0.000000 -0.044230 0.000000 0.023557 0.000000 ) +( 0.005484 -0.000000 0.050427 -0.000000 0.109426 -0.000000 ) +( -0.024143 0.000000 0.044230 -0.000000 -0.023557 -0.000000 ) +( -0.005484 0.000000 -0.050427 0.000000 -0.109426 0.000000 ) + freq ( 47) = 54.31746074 [THz] = 1811.83546280 [cm-1] +( -0.114997 0.000000 -0.089507 0.000000 -0.004881 0.000000 ) +( -0.016101 0.000000 0.092301 -0.000000 -0.035099 -0.000000 ) +( 0.114997 -0.000000 0.089507 -0.000000 0.004881 -0.000000 ) +( 0.016101 -0.000000 -0.092301 0.000000 0.035099 0.000000 ) +( 0.036662 -0.000000 -0.157625 0.000000 -0.037490 0.000000 ) +( 0.278682 0.000000 -0.034350 0.000000 0.100996 0.000000 ) +( -0.036662 0.000000 0.157625 -0.000000 0.037490 -0.000000 ) +( -0.278682 0.000000 0.034350 -0.000000 -0.100996 -0.000000 ) +( -0.164338 0.000000 -0.071435 0.000000 0.022385 0.000000 ) +( 0.224728 -0.000000 -0.005672 0.000000 -0.099298 0.000000 ) +( 0.164338 -0.000000 0.071435 -0.000000 -0.022385 -0.000000 ) +( -0.224728 0.000000 0.005672 -0.000000 0.099298 -0.000000 ) +( 0.214109 -0.000000 -0.046218 0.000000 0.037114 0.000000 ) +( 0.140729 -0.000000 -0.055779 0.000000 -0.069110 0.000000 ) +( -0.214109 0.000000 0.046218 -0.000000 -0.037114 -0.000000 ) +( -0.140729 0.000000 0.055779 -0.000000 0.069110 -0.000000 ) +( 0.097096 -0.000000 -0.053887 0.000000 0.146173 0.000000 ) +( 0.131745 -0.000000 -0.110177 0.000000 0.192944 0.000000 ) +( -0.097096 0.000000 0.053887 -0.000000 -0.146173 -0.000000 ) +( -0.131745 0.000000 0.110177 -0.000000 -0.192944 -0.000000 ) +( -0.096849 0.000000 0.053218 -0.000000 -0.168416 -0.000000 ) +( -0.117648 0.000000 0.152361 -0.000000 -0.063122 -0.000000 ) +( 0.096849 -0.000000 -0.053218 0.000000 0.168416 0.000000 ) +( 0.117648 -0.000000 -0.152361 0.000000 0.063122 0.000000 ) + freq ( 48) = 55.68417106 [THz] = 1857.42401186 [cm-1] +( 0.172606 0.000000 0.064119 0.000000 0.079057 0.000000 ) +( -0.025367 0.000000 0.079007 0.000000 0.037293 0.000000 ) +( -0.172606 0.000000 -0.064119 0.000000 -0.079057 0.000000 ) +( 0.025367 0.000000 -0.079007 0.000000 -0.037293 0.000000 ) +( 0.424680 0.000000 0.020907 0.000000 -0.079721 0.000000 ) +( -0.195117 0.000000 0.029511 0.000000 -0.087297 0.000000 ) +( -0.424680 0.000000 -0.020907 0.000000 0.079721 0.000000 ) +( 0.195117 0.000000 -0.029511 0.000000 0.087297 0.000000 ) +( -0.039087 0.000000 0.075866 0.000000 0.029612 0.000000 ) +( -0.088577 0.000000 -0.035493 0.000000 -0.034550 0.000000 ) +( 0.039087 0.000000 -0.075866 0.000000 -0.029612 0.000000 ) +( 0.088577 0.000000 0.035493 0.000000 0.034550 0.000000 ) +( 0.289075 0.000000 -0.032616 0.000000 0.101331 0.000000 ) +( -0.145958 0.000000 -0.072535 0.000000 0.003805 0.000000 ) +( -0.289075 0.000000 0.032616 0.000000 -0.101331 0.000000 ) +( 0.145958 0.000000 0.072535 0.000000 -0.003805 0.000000 ) +( 0.015855 0.000000 -0.021632 0.000000 0.249443 0.000000 ) +( 0.012650 0.000000 0.021255 0.000000 -0.059837 0.000000 ) +( -0.015855 0.000000 0.021632 0.000000 -0.249443 0.000000 ) +( -0.012650 0.000000 -0.021255 0.000000 0.059837 0.000000 ) +( 0.055591 0.000000 0.075323 0.000000 -0.024675 0.000000 ) +( -0.017691 0.000000 0.017703 0.000000 0.028158 0.000000 ) +( -0.055591 0.000000 -0.075323 0.000000 0.024675 0.000000 ) +( 0.017691 0.000000 -0.017703 0.000000 -0.028158 0.000000 ) + freq ( 49) = 57.73867920 [THz] = 1925.95502674 [cm-1] +( 0.236462 -0.000000 -0.115417 0.000000 -0.013520 0.000000 ) +( 0.056896 -0.000000 0.117797 -0.000000 -0.032702 -0.000000 ) +( 0.236462 0.000000 -0.115417 0.000000 -0.013520 0.000000 ) +( 0.056896 -0.000000 0.117797 -0.000000 -0.032702 -0.000000 ) +( 0.058897 -0.000000 -0.180404 0.000000 0.074696 0.000000 ) +( 0.230715 -0.000000 0.153939 -0.000000 0.117514 -0.000000 ) +( 0.058897 -0.000000 -0.180404 0.000000 0.074696 0.000000 ) +( 0.230715 -0.000000 0.153939 -0.000000 0.117514 -0.000000 ) +( 0.052894 -0.000000 -0.052802 0.000000 -0.044057 0.000000 ) +( 0.172515 -0.000000 0.014533 -0.000000 0.057590 -0.000000 ) +( 0.052894 -0.000000 -0.052802 0.000000 -0.044057 0.000000 ) +( 0.172515 -0.000000 0.014533 -0.000000 0.057590 -0.000000 ) +( -0.150465 0.000000 0.033261 -0.000000 -0.010339 -0.000000 ) +( 0.189603 -0.000000 0.041500 -0.000000 0.060496 -0.000000 ) +( -0.150465 0.000000 0.033261 -0.000000 -0.010339 -0.000000 ) +( 0.189603 -0.000000 0.041500 -0.000000 0.060496 -0.000000 ) +( -0.147412 0.000000 -0.005049 0.000000 -0.212511 0.000000 ) +( -0.056549 0.000000 0.097156 -0.000000 0.117539 -0.000000 ) +( -0.147412 0.000000 -0.005049 0.000000 -0.212511 0.000000 ) +( -0.056549 0.000000 0.097156 -0.000000 0.117539 -0.000000 ) +( 0.148331 -0.000000 0.023391 -0.000000 0.232375 -0.000000 ) +( 0.043237 -0.000000 -0.046440 0.000000 0.011223 0.000000 ) +( 0.148331 -0.000000 0.023391 -0.000000 0.232375 -0.000000 ) +( 0.043237 -0.000000 -0.046440 0.000000 0.011223 0.000000 ) + freq ( 50) = 57.98123636 [THz] = 1934.04586283 [cm-1] +( -0.044776 0.000000 -0.155537 0.000000 0.021670 0.000000 ) +( -0.003512 0.000000 -0.047661 0.000000 -0.002257 0.000000 ) +( 0.044776 0.000000 0.155537 0.000000 -0.021670 0.000000 ) +( 0.003512 0.000000 0.047661 0.000000 0.002257 0.000000 ) +( 0.088547 0.000000 -0.148294 0.000000 -0.069655 0.000000 ) +( -0.025463 0.000000 -0.102678 0.000000 0.053355 0.000000 ) +( -0.088547 0.000000 0.148294 0.000000 0.069655 0.000000 ) +( 0.025463 0.000000 0.102678 0.000000 -0.053355 0.000000 ) +( 0.210213 0.000000 0.017397 0.000000 0.177528 0.000000 ) +( 0.091801 0.000000 -0.117053 0.000000 0.153244 0.000000 ) +( -0.210213 0.000000 -0.017397 0.000000 -0.177528 0.000000 ) +( -0.091801 0.000000 0.117053 0.000000 -0.153244 0.000000 ) +( -0.042732 0.000000 -0.040558 0.000000 -0.053605 0.000000 ) +( 0.250826 0.000000 -0.065135 0.000000 0.085307 0.000000 ) +( 0.042732 0.000000 0.040558 0.000000 0.053605 0.000000 ) +( -0.250826 0.000000 0.065135 0.000000 -0.085307 0.000000 ) +( 0.069142 0.000000 0.071465 0.000000 0.161557 0.000000 ) +( -0.178146 0.000000 -0.018072 0.000000 -0.217954 0.000000 ) +( -0.069142 0.000000 -0.071465 0.000000 -0.161557 0.000000 ) +( 0.178146 0.000000 0.018072 0.000000 0.217954 0.000000 ) +( -0.081441 0.000000 -0.101104 0.000000 -0.160733 0.000000 ) +( 0.214891 0.000000 -0.021593 0.000000 0.122621 0.000000 ) +( 0.081441 0.000000 0.101104 0.000000 0.160733 0.000000 ) +( -0.214891 0.000000 0.021593 0.000000 -0.122621 0.000000 ) + freq ( 51) = 59.03551408 [THz] = 1969.21278217 [cm-1] +( -0.037140 0.000000 -0.085872 0.000000 0.025437 0.000000 ) +( 0.001684 0.000000 0.120440 0.000000 -0.131659 0.000000 ) +( -0.037140 0.000000 -0.085872 0.000000 0.025437 0.000000 ) +( 0.001684 0.000000 0.120440 0.000000 -0.131659 0.000000 ) +( -0.133682 0.000000 -0.126748 0.000000 0.011587 0.000000 ) +( -0.146828 0.000000 0.016844 0.000000 -0.095635 0.000000 ) +( -0.133682 0.000000 -0.126748 0.000000 0.011587 0.000000 ) +( -0.146828 0.000000 0.016844 0.000000 -0.095635 0.000000 ) +( 0.173538 0.000000 -0.101548 0.000000 0.055407 0.000000 ) +( 0.012416 0.000000 0.242809 0.000000 0.124204 0.000000 ) +( 0.173538 0.000000 -0.101548 0.000000 0.055407 0.000000 ) +( 0.012416 0.000000 0.242809 0.000000 0.124204 0.000000 ) +( -0.169428 0.000000 0.040646 0.000000 -0.009129 0.000000 ) +( 0.037207 0.000000 0.208922 0.000000 0.106678 0.000000 ) +( -0.169428 0.000000 0.040646 0.000000 -0.009129 0.000000 ) +( 0.037207 0.000000 0.208922 0.000000 0.106678 0.000000 ) +( 0.027287 0.000000 0.113509 0.000000 0.079481 0.000000 ) +( -0.170595 0.000000 -0.060389 0.000000 -0.056083 0.000000 ) +( 0.027287 0.000000 0.113509 0.000000 0.079481 0.000000 ) +( -0.170595 0.000000 -0.060389 0.000000 -0.056083 0.000000 ) +( -0.105765 0.000000 -0.197149 0.000000 -0.114375 0.000000 ) +( 0.223338 0.000000 0.127407 0.000000 0.061001 0.000000 ) +( -0.105765 0.000000 -0.197149 0.000000 -0.114375 0.000000 ) +( 0.223338 0.000000 0.127407 0.000000 0.061001 0.000000 ) + freq ( 52) = 59.09104431 [THz] = 1971.06507120 [cm-1] +( 0.112284 -0.000000 -0.063719 0.000000 -0.199580 0.000000 ) +( -0.119951 0.000000 -0.029999 0.000000 0.068590 0.000000 ) +( -0.112284 0.000000 0.063719 -0.000000 0.199580 -0.000000 ) +( 0.119951 -0.000000 0.029999 -0.000000 -0.068590 -0.000000 ) +( 0.079296 -0.000000 -0.099427 0.000000 -0.157397 0.000000 ) +( -0.055330 0.000000 0.007725 -0.000000 -0.064314 -0.000000 ) +( -0.079296 0.000000 0.099427 -0.000000 0.157397 -0.000000 ) +( 0.055330 -0.000000 -0.007725 0.000000 0.064314 0.000000 ) +( -0.073463 0.000000 0.010746 -0.000000 -0.061394 -0.000000 ) +( 0.127956 -0.000000 -0.069238 0.000000 -0.174290 0.000000 ) +( 0.073463 -0.000000 -0.010746 0.000000 0.061394 0.000000 ) +( -0.127956 0.000000 0.069238 -0.000000 0.174290 -0.000000 ) +( 0.090702 -0.000000 -0.047608 0.000000 -0.140625 0.000000 ) +( 0.144116 -0.000000 -0.025840 0.000000 -0.125999 0.000000 ) +( -0.090702 0.000000 0.047608 -0.000000 0.140625 -0.000000 ) +( -0.144116 0.000000 0.025840 -0.000000 0.125999 -0.000000 ) +( 0.087017 -0.000000 0.097663 -0.000000 -0.228380 -0.000000 ) +( 0.114467 -0.000000 0.025719 -0.000000 -0.126787 -0.000000 ) +( -0.087017 0.000000 -0.097663 0.000000 0.228380 0.000000 ) +( -0.114467 0.000000 -0.025719 0.000000 0.126787 0.000000 ) +( -0.013849 0.000000 -0.127913 0.000000 0.254727 0.000000 ) +( -0.082302 0.000000 0.003051 -0.000000 0.244062 -0.000000 ) +( 0.013849 -0.000000 0.127913 -0.000000 -0.254727 -0.000000 ) +( 0.082302 -0.000000 -0.003051 0.000000 -0.244062 0.000000 ) + freq ( 53) = 60.45268080 [THz] = 2016.48437557 [cm-1] +( 0.032351 -0.000000 0.199061 -0.000000 0.035131 -0.000000 ) +( -0.075349 0.000000 -0.024908 0.000000 0.123298 0.000000 ) +( -0.032351 0.000000 -0.199061 0.000000 -0.035131 0.000000 ) +( 0.075349 -0.000000 0.024908 -0.000000 -0.123298 -0.000000 ) +( 0.008761 -0.000000 0.112517 -0.000000 0.041963 -0.000000 ) +( 0.049979 -0.000000 -0.122358 0.000000 0.010283 0.000000 ) +( -0.008761 0.000000 -0.112517 0.000000 -0.041963 0.000000 ) +( -0.049979 0.000000 0.122358 -0.000000 -0.010283 -0.000000 ) +( 0.254223 -0.000000 0.042753 -0.000000 0.117012 -0.000000 ) +( 0.050965 -0.000000 -0.047869 0.000000 -0.173956 0.000000 ) +( -0.254223 0.000000 -0.042753 0.000000 -0.117012 0.000000 ) +( -0.050965 0.000000 0.047869 -0.000000 0.173956 -0.000000 ) +( -0.181482 0.000000 -0.003517 0.000000 -0.047028 0.000000 ) +( 0.107978 -0.000000 0.037941 -0.000000 -0.170962 -0.000000 ) +( 0.181482 -0.000000 0.003517 -0.000000 0.047028 -0.000000 ) +( -0.107978 0.000000 -0.037941 0.000000 0.170962 0.000000 ) +( 0.027876 -0.000000 -0.232587 0.000000 0.092468 0.000000 ) +( 0.124728 -0.000000 0.029224 -0.000000 -0.086403 -0.000000 ) +( -0.027876 0.000000 0.232587 -0.000000 -0.092468 -0.000000 ) +( -0.124728 0.000000 -0.029224 0.000000 0.086403 0.000000 ) +( -0.035624 0.000000 0.293518 0.000000 -0.036357 0.000000 ) +( -0.147184 0.000000 -0.032249 0.000000 0.113965 0.000000 ) +( 0.035624 -0.000000 -0.293518 0.000000 0.036357 0.000000 ) +( 0.147184 -0.000000 0.032249 -0.000000 -0.113965 -0.000000 ) + freq ( 54) = 61.98201711 [THz] = 2067.49754376 [cm-1] +( -0.164188 0.000000 -0.034943 0.000000 -0.048497 0.000000 ) +( -0.181691 0.000000 -0.131534 0.000000 -0.020725 0.000000 ) +( 0.164188 -0.000000 0.034943 -0.000000 0.048497 -0.000000 ) +( 0.181691 -0.000000 0.131534 -0.000000 0.020725 -0.000000 ) +( -0.096756 0.000000 -0.128748 0.000000 -0.070564 0.000000 ) +( -0.260147 0.000000 -0.090746 0.000000 -0.121619 0.000000 ) +( 0.096756 -0.000000 0.128748 -0.000000 0.070564 -0.000000 ) +( 0.260147 0.000000 0.090746 -0.000000 0.121619 -0.000000 ) +( -0.028300 0.000000 -0.206484 0.000000 0.035636 0.000000 ) +( -0.082532 0.000000 0.114977 -0.000000 -0.063267 -0.000000 ) +( 0.028300 -0.000000 0.206484 -0.000000 -0.035636 -0.000000 ) +( 0.082532 -0.000000 -0.114977 0.000000 0.063267 0.000000 ) +( 0.016516 -0.000000 0.215892 -0.000000 -0.047516 -0.000000 ) +( -0.191539 0.000000 0.180998 -0.000000 -0.057755 -0.000000 ) +( -0.016516 0.000000 -0.215892 0.000000 0.047516 0.000000 ) +( 0.191539 -0.000000 -0.180998 0.000000 0.057755 0.000000 ) +( 0.133515 -0.000000 -0.083691 0.000000 0.095356 0.000000 ) +( 0.054803 -0.000000 -0.115372 0.000000 -0.064461 0.000000 ) +( -0.133515 0.000000 0.083691 -0.000000 -0.095356 -0.000000 ) +( -0.054803 0.000000 0.115372 -0.000000 0.064461 -0.000000 ) +( -0.175360 0.000000 -0.052245 0.000000 -0.108329 0.000000 ) +( -0.005947 0.000000 0.078724 -0.000000 0.024556 -0.000000 ) +( 0.175360 -0.000000 0.052245 -0.000000 0.108329 -0.000000 ) +( 0.005947 -0.000000 -0.078724 0.000000 -0.024556 0.000000 ) + freq ( 55) = 62.07322959 [THz] = 2070.54006442 [cm-1] +( 0.084880 -0.000000 0.120438 -0.000000 0.018331 -0.000000 ) +( -0.033326 0.000000 -0.051345 0.000000 -0.136846 0.000000 ) +( 0.084880 -0.000000 0.120438 -0.000000 0.018331 -0.000000 ) +( -0.033326 0.000000 -0.051345 0.000000 -0.136846 0.000000 ) +( 0.065909 -0.000000 -0.132397 0.000000 0.015460 0.000000 ) +( -0.101148 0.000000 -0.086154 0.000000 -0.144326 0.000000 ) +( 0.065909 -0.000000 -0.132397 0.000000 0.015460 0.000000 ) +( -0.101148 0.000000 -0.086154 0.000000 -0.144326 0.000000 ) +( -0.003793 0.000000 -0.291590 0.000000 -0.008380 0.000000 ) +( -0.227695 0.000000 -0.031757 0.000000 0.060564 0.000000 ) +( -0.003793 0.000000 -0.291590 0.000000 -0.008380 0.000000 ) +( -0.227695 0.000000 -0.031757 0.000000 0.060564 0.000000 ) +( -0.022166 0.000000 0.293193 0.000000 0.022549 0.000000 ) +( -0.220992 0.000000 0.039007 -0.000000 -0.000745 -0.000000 ) +( -0.022166 0.000000 0.293193 -0.000000 0.022549 -0.000000 ) +( -0.220992 0.000000 0.039007 -0.000000 -0.000745 -0.000000 ) +( -0.064125 0.000000 -0.210949 0.000000 -0.090179 0.000000 ) +( 0.029333 -0.000000 0.021727 -0.000000 0.167996 -0.000000 ) +( -0.064125 0.000000 -0.210949 0.000000 -0.090179 0.000000 ) +( 0.029333 -0.000000 0.021727 -0.000000 0.167996 -0.000000 ) +( 0.055226 -0.000000 -0.019412 0.000000 0.057848 0.000000 ) +( -0.018304 0.000000 -0.036843 0.000000 -0.145491 0.000000 ) +( 0.055226 -0.000000 -0.019412 0.000000 0.057848 0.000000 ) +( -0.018304 0.000000 -0.036843 0.000000 -0.145491 0.000000 ) + freq ( 56) = 63.12831005 [THz] = 2105.73376039 [cm-1] +( 0.093169 0.000000 -0.055691 0.000000 0.025644 0.000000 ) +( -0.047940 0.000000 0.228957 0.000000 -0.111052 0.000000 ) +( 0.093169 0.000000 -0.055691 0.000000 0.025644 0.000000 ) +( -0.047940 0.000000 0.228957 0.000000 -0.111052 0.000000 ) +( 0.056729 0.000000 0.077963 0.000000 -0.006954 0.000000 ) +( -0.175531 0.000000 0.175722 0.000000 -0.149587 0.000000 ) +( 0.056729 0.000000 0.077963 0.000000 -0.006954 0.000000 ) +( -0.175531 0.000000 0.175722 0.000000 -0.149587 0.000000 ) +( 0.049301 0.000000 0.149360 0.000000 0.019833 0.000000 ) +( -0.150485 0.000000 -0.027574 0.000000 0.067541 0.000000 ) +( 0.049301 0.000000 0.149360 0.000000 0.019833 0.000000 ) +( -0.150485 0.000000 -0.027574 0.000000 0.067541 0.000000 ) +( -0.008055 0.000000 -0.127034 0.000000 -0.013283 0.000000 ) +( -0.139025 0.000000 -0.245170 0.000000 -0.002157 0.000000 ) +( -0.008055 0.000000 -0.127034 0.000000 -0.013283 0.000000 ) +( -0.139025 0.000000 -0.245170 0.000000 -0.002157 0.000000 ) +( -0.004115 0.000000 0.123065 0.000000 0.031109 0.000000 ) +( -0.064276 0.000000 0.318033 0.000000 0.041626 0.000000 ) +( -0.004115 0.000000 0.123065 0.000000 0.031109 0.000000 ) +( -0.064276 0.000000 0.318033 0.000000 0.041626 0.000000 ) +( 0.011587 0.000000 -0.049663 0.000000 0.036283 0.000000 ) +( 0.066322 0.000000 -0.215348 0.000000 -0.018669 0.000000 ) +( 0.011587 0.000000 -0.049663 0.000000 0.036283 0.000000 ) +( 0.066322 0.000000 -0.215348 0.000000 -0.018669 0.000000 ) + freq ( 57) = 63.22698620 [THz] = 2109.02524243 [cm-1] +( -0.088679 0.000000 0.032001 -0.000000 0.091604 -0.000000 ) +( -0.050940 0.000000 -0.283947 0.000000 -0.022058 0.000000 ) +( 0.088679 -0.000000 -0.032001 0.000000 -0.091604 0.000000 ) +( 0.050940 -0.000000 0.283947 -0.000000 0.022058 -0.000000 ) +( -0.095014 0.000000 0.004408 -0.000000 0.109210 -0.000000 ) +( -0.041468 0.000000 -0.293362 0.000000 -0.044590 0.000000 ) +( 0.095014 -0.000000 -0.004408 0.000000 -0.109210 0.000000 ) +( 0.041468 -0.000000 0.293362 0.000000 0.044590 0.000000 ) +( -0.242837 0.000000 0.041129 -0.000000 -0.175853 -0.000000 ) +( 0.054916 -0.000000 -0.215268 0.000000 -0.025833 0.000000 ) +( 0.242837 -0.000000 -0.041129 0.000000 0.175853 0.000000 ) +( -0.054916 0.000000 0.215268 -0.000000 0.025833 -0.000000 ) +( 0.112411 -0.000000 0.028337 -0.000000 0.175867 -0.000000 ) +( 0.070051 -0.000000 -0.050862 0.000000 -0.002021 0.000000 ) +( -0.112411 0.000000 -0.028337 0.000000 -0.175867 0.000000 ) +( -0.070051 0.000000 0.050862 -0.000000 0.002021 -0.000000 ) +( -0.106607 0.000000 -0.011635 0.000000 0.034165 0.000000 ) +( -0.040862 0.000000 -0.045560 0.000000 -0.042423 0.000000 ) +( 0.106607 -0.000000 0.011635 -0.000000 -0.034165 -0.000000 ) +( 0.040862 -0.000000 0.045560 -0.000000 0.042423 -0.000000 ) +( 0.121692 -0.000000 0.072929 -0.000000 -0.020229 -0.000000 ) +( 0.023459 -0.000000 -0.211005 0.000000 0.104745 0.000000 ) +( -0.121692 0.000000 -0.072929 0.000000 0.020229 0.000000 ) +( -0.023459 0.000000 0.211005 -0.000000 -0.104745 -0.000000 ) + freq ( 58) = 65.00757504 [THz] = 2168.41929285 [cm-1] +( -0.066412 0.000000 0.093525 0.000000 -0.025737 0.000000 ) +( 0.250801 0.000000 -0.065484 0.000000 -0.131348 0.000000 ) +( -0.066412 0.000000 0.093525 0.000000 -0.025737 0.000000 ) +( 0.250801 0.000000 -0.065484 0.000000 -0.131348 0.000000 ) +( -0.054335 0.000000 0.180368 0.000000 -0.032072 0.000000 ) +( 0.214098 0.000000 -0.131163 0.000000 0.053106 0.000000 ) +( -0.054335 0.000000 0.180368 0.000000 -0.032072 0.000000 ) +( 0.214098 0.000000 -0.131163 0.000000 0.053106 0.000000 ) +( -0.050898 0.000000 0.058587 0.000000 0.009772 0.000000 ) +( -0.069644 0.000000 -0.023999 0.000000 0.231604 0.000000 ) +( -0.050898 0.000000 0.058587 0.000000 0.009772 0.000000 ) +( -0.069644 0.000000 -0.023999 0.000000 0.231604 0.000000 ) +( 0.029627 0.000000 -0.166565 0.000000 0.001214 0.000000 ) +( -0.015195 0.000000 0.052133 0.000000 0.196610 0.000000 ) +( 0.029627 0.000000 -0.166565 0.000000 0.001214 0.000000 ) +( -0.015195 0.000000 0.052133 0.000000 0.196610 0.000000 ) +( 0.023839 0.000000 0.060290 0.000000 -0.008183 0.000000 ) +( -0.115395 0.000000 -0.020241 0.000000 0.290906 0.000000 ) +( 0.023839 0.000000 0.060290 0.000000 -0.008183 0.000000 ) +( -0.115395 0.000000 -0.020241 0.000000 0.290906 0.000000 ) +( -0.027275 0.000000 -0.011814 0.000000 -0.060191 0.000000 ) +( 0.088249 0.000000 -0.049688 0.000000 -0.215790 0.000000 ) +( -0.027275 0.000000 -0.011814 0.000000 -0.060191 0.000000 ) +( 0.088249 0.000000 -0.049688 0.000000 -0.215790 0.000000 ) + freq ( 59) = 66.11238882 [THz] = 2205.27191376 [cm-1] +( -0.025488 0.000000 -0.245192 0.000000 0.169357 0.000000 ) +( -0.091948 0.000000 0.195499 0.000000 0.101961 0.000000 ) +( 0.025488 0.000000 0.245192 0.000000 -0.169357 0.000000 ) +( 0.091948 0.000000 -0.195499 0.000000 -0.101961 0.000000 ) +( -0.057407 0.000000 -0.155386 0.000000 0.213176 0.000000 ) +( -0.065234 0.000000 0.073568 0.000000 -0.000877 0.000000 ) +( 0.057407 0.000000 0.155386 0.000000 -0.213176 0.000000 ) +( 0.065234 0.000000 -0.073568 0.000000 0.000877 0.000000 ) +( 0.008317 0.000000 0.096525 0.000000 -0.080904 0.000000 ) +( 0.054174 0.000000 0.180997 0.000000 -0.149392 0.000000 ) +( -0.008317 0.000000 -0.096525 0.000000 0.080904 0.000000 ) +( -0.054174 0.000000 -0.180997 0.000000 0.149392 0.000000 ) +( -0.106685 0.000000 0.024956 0.000000 0.163685 0.000000 ) +( 0.034034 0.000000 0.102475 0.000000 -0.108523 0.000000 ) +( 0.106685 0.000000 -0.024956 0.000000 -0.163685 0.000000 ) +( -0.034034 0.000000 -0.102475 0.000000 0.108523 0.000000 ) +( -0.166196 0.000000 0.101658 0.000000 0.125553 0.000000 ) +( 0.060094 0.000000 0.111224 0.000000 -0.132938 0.000000 ) +( 0.166196 0.000000 -0.101658 0.000000 -0.125553 0.000000 ) +( -0.060094 0.000000 -0.111224 0.000000 0.132938 0.000000 ) +( 0.147136 0.000000 -0.093621 0.000000 -0.049022 0.000000 ) +( -0.077521 0.000000 0.017557 0.000000 0.090769 0.000000 ) +( -0.147136 0.000000 0.093621 0.000000 0.049022 0.000000 ) +( 0.077521 0.000000 -0.017557 0.000000 -0.090769 0.000000 ) + freq ( 60) = 68.21046570 [THz] = 2275.25622537 [cm-1] +( -0.055606 0.000000 0.083885 0.000000 0.218940 0.000000 ) +( 0.028196 0.000000 0.004991 0.000000 0.019578 0.000000 ) +( -0.055606 0.000000 0.083885 0.000000 0.218940 0.000000 ) +( 0.028196 0.000000 0.004991 0.000000 0.019578 0.000000 ) +( -0.120941 0.000000 0.071541 0.000000 0.325320 0.000000 ) +( 0.014751 0.000000 -0.060482 0.000000 0.032341 0.000000 ) +( -0.120941 0.000000 0.071541 0.000000 0.325320 0.000000 ) +( 0.014751 0.000000 -0.060482 0.000000 0.032341 0.000000 ) +( -0.057457 0.000000 -0.050187 0.000000 -0.164471 0.000000 ) +( -0.002417 0.000000 0.018425 0.000000 -0.051654 0.000000 ) +( -0.057457 0.000000 -0.050187 0.000000 -0.164471 0.000000 ) +( -0.002417 0.000000 0.018425 0.000000 -0.051654 0.000000 ) +( -0.122782 0.000000 -0.025361 0.000000 0.280762 0.000000 ) +( 0.010029 0.000000 0.028571 0.000000 -0.014738 0.000000 ) +( -0.122782 0.000000 -0.025361 0.000000 0.280762 0.000000 ) +( 0.010029 0.000000 0.028571 0.000000 -0.014738 0.000000 ) +( -0.237176 0.000000 0.031335 0.000000 0.223186 0.000000 ) +( -0.006696 0.000000 0.070718 0.000000 -0.039730 0.000000 ) +( -0.237176 0.000000 0.031335 0.000000 0.223186 0.000000 ) +( -0.006696 0.000000 0.070718 0.000000 -0.039730 0.000000 ) +( 0.205720 0.000000 -0.055127 0.000000 -0.088285 0.000000 ) +( -0.044223 0.000000 -0.099332 0.000000 0.004696 0.000000 ) +( 0.205720 0.000000 -0.055127 0.000000 -0.088285 0.000000 ) +( -0.044223 0.000000 -0.099332 0.000000 0.004696 0.000000 ) + freq ( 61) = 101.14264239 [THz] = 3373.75539661 [cm-1] +( 0.167868 -0.000000 0.014514 -0.000000 0.183450 -0.000000 ) +( 0.133333 -0.000000 -0.001983 0.000000 -0.049455 0.000000 ) +( 0.167868 -0.000000 0.014514 -0.000000 0.183450 -0.000000 ) +( 0.133333 -0.000000 -0.001983 0.000000 -0.049455 0.000000 ) +( -0.142862 0.000000 0.013122 -0.000000 -0.196450 -0.000000 ) +( -0.064288 0.000000 -0.016671 0.000000 0.125919 0.000000 ) +( -0.142862 0.000000 0.013122 -0.000000 -0.196450 -0.000000 ) +( -0.064288 0.000000 -0.016671 0.000000 0.125919 0.000000 ) +( -0.059908 0.000000 0.027822 -0.000000 0.098398 -0.000000 ) +( 0.109559 -0.000000 -0.038970 0.000000 0.162401 0.000000 ) +( -0.059908 0.000000 0.027822 -0.000000 0.098398 -0.000000 ) +( 0.109559 -0.000000 -0.038970 0.000000 0.162401 0.000000 ) +( -0.050626 0.000000 -0.009436 0.000000 0.133944 0.000000 ) +( -0.113017 0.000000 -0.016307 0.000000 -0.209917 0.000000 ) +( -0.050626 0.000000 -0.009436 0.000000 0.133944 0.000000 ) +( -0.113017 0.000000 -0.016307 0.000000 -0.209917 0.000000 ) +( -0.017108 0.000000 -0.017710 0.000000 -0.001627 0.000000 ) +( 0.353795 0.000000 -0.039212 0.000000 0.002005 0.000000 ) +( -0.017108 0.000000 -0.017710 0.000000 -0.001627 0.000000 ) +( 0.353795 -0.000000 -0.039212 0.000000 0.002005 0.000000 ) +( -0.002429 0.000000 0.004952 -0.000000 0.008734 -0.000000 ) +( 0.271523 -0.000000 0.000303 -0.000000 0.074139 -0.000000 ) +( -0.002429 0.000000 0.004952 -0.000000 0.008734 -0.000000 ) +( 0.271523 -0.000000 0.000303 -0.000000 0.074139 -0.000000 ) + freq ( 62) = 101.79237425 [THz] = 3395.42811851 [cm-1] +( -0.177042 0.000000 -0.011180 0.000000 -0.155024 0.000000 ) +( -0.011012 0.000000 0.000044 -0.000000 -0.086667 -0.000000 ) +( 0.177042 -0.000000 0.011180 -0.000000 0.155024 -0.000000 ) +( 0.011012 -0.000000 -0.000044 0.000000 0.086667 0.000000 ) +( 0.132013 -0.000000 0.000063 -0.000000 0.218131 -0.000000 ) +( -0.041894 0.000000 -0.000104 0.000000 0.033783 0.000000 ) +( -0.132013 0.000000 -0.000063 0.000000 -0.218131 0.000000 ) +( 0.041894 -0.000000 0.000104 -0.000000 -0.033783 -0.000000 ) +( 0.041971 -0.000000 -0.016057 0.000000 -0.062740 0.000000 ) +( -0.137420 0.000000 0.032207 -0.000000 -0.225768 -0.000000 ) +( -0.041971 0.000000 0.016057 -0.000000 0.062740 -0.000000 ) +( 0.137420 -0.000000 -0.032207 0.000000 0.225768 0.000000 ) +( -0.015363 0.000000 0.002839 -0.000000 -0.097030 -0.000000 ) +( 0.124967 -0.000000 -0.005412 0.000000 0.220783 0.000000 ) +( 0.015363 -0.000000 -0.002839 0.000000 0.097030 0.000000 ) +( -0.124967 0.000000 0.005412 -0.000000 -0.220783 -0.000000 ) +( 0.301399 0.000000 -0.029072 0.000000 -0.002271 0.000000 ) +( -0.155613 0.000000 -0.006561 0.000000 0.019628 0.000000 ) +( -0.301399 0.000000 0.029072 -0.000000 0.002271 -0.000000 ) +( 0.155613 -0.000000 0.006561 -0.000000 -0.019628 -0.000000 ) +( 0.293414 -0.000000 0.004504 -0.000000 -0.022022 -0.000000 ) +( -0.117505 0.000000 0.001995 -0.000000 -0.036319 -0.000000 ) +( -0.293414 0.000000 -0.004504 0.000000 0.022022 0.000000 ) +( 0.117505 -0.000000 -0.001995 0.000000 0.036319 0.000000 ) + freq ( 63) = 105.02606942 [THz] = 3503.29257883 [cm-1] +( -0.117815 0.000000 -0.015900 0.000000 -0.107562 0.000000 ) +( 0.167545 -0.000000 0.008384 -0.000000 -0.258128 -0.000000 ) +( -0.117815 0.000000 -0.015900 0.000000 -0.107562 0.000000 ) +( 0.167545 -0.000000 0.008384 -0.000000 -0.258128 -0.000000 ) +( 0.083588 -0.000000 -0.008353 0.000000 0.167355 0.000000 ) +( -0.200297 0.000000 0.017509 -0.000000 0.260572 -0.000000 ) +( 0.083588 -0.000000 -0.008353 0.000000 0.167355 0.000000 ) +( -0.200297 0.000000 0.017509 -0.000000 0.260572 -0.000000 ) +( 0.078292 -0.000000 -0.008710 0.000000 -0.113871 0.000000 ) +( 0.005907 -0.000000 -0.000403 0.000000 -0.022874 0.000000 ) +( 0.078292 -0.000000 -0.008710 0.000000 -0.113871 0.000000 ) +( 0.005907 -0.000000 -0.000403 0.000000 -0.022874 0.000000 ) +( 0.018007 -0.000000 -0.008264 0.000000 -0.113422 0.000000 ) +( 0.003186 -0.000000 0.005320 -0.000000 -0.056824 -0.000000 ) +( 0.018007 -0.000000 -0.008264 0.000000 -0.113422 0.000000 ) +( 0.003186 -0.000000 0.005320 -0.000000 -0.056824 -0.000000 ) +( 0.306073 -0.000000 -0.026459 0.000000 -0.019528 0.000000 ) +( 0.084174 -0.000000 -0.008633 0.000000 -0.008053 0.000000 ) +( 0.306073 -0.000000 -0.026459 0.000000 -0.019528 0.000000 ) +( 0.084174 -0.000000 -0.008633 0.000000 -0.008053 0.000000 ) +( 0.309402 -0.000000 -0.021562 0.000000 -0.016204 0.000000 ) +( 0.002764 -0.000000 0.002245 -0.000000 0.037764 -0.000000 ) +( 0.309402 0.000000 -0.021562 0.000000 -0.016204 0.000000 ) +( 0.002764 -0.000000 0.002245 -0.000000 0.037764 -0.000000 ) + freq ( 64) = 105.10816984 [THz] = 3506.03115403 [cm-1] +( -0.020916 0.000000 0.007152 0.000000 0.027741 0.000000 ) +( 0.164238 0.000000 0.008520 0.000000 -0.181857 0.000000 ) +( 0.020916 0.000000 -0.007152 0.000000 -0.027741 0.000000 ) +( -0.164238 0.000000 -0.008520 0.000000 0.181857 0.000000 ) +( -0.015731 0.000000 0.010881 0.000000 0.021284 0.000000 ) +( -0.138686 0.000000 0.011258 0.000000 0.221003 0.000000 ) +( 0.015731 0.000000 -0.010881 0.000000 -0.021284 0.000000 ) +( 0.138686 0.000000 -0.011258 0.000000 -0.221003 0.000000 ) +( 0.020230 0.000000 0.015915 0.000000 -0.043362 0.000000 ) +( 0.136840 0.000000 0.008736 0.000000 0.175075 0.000000 ) +( -0.020230 0.000000 -0.015915 0.000000 0.043362 0.000000 ) +( -0.136840 0.000000 -0.008736 0.000000 -0.175075 0.000000 ) +( -0.008856 0.000000 -0.007636 0.000000 -0.023627 0.000000 ) +( -0.103703 0.000000 0.023752 0.000000 -0.242483 0.000000 ) +( 0.008856 0.000000 0.007636 0.000000 0.023627 0.000000 ) +( 0.103703 0.000000 -0.023752 0.000000 0.242483 0.000000 ) +( 0.254985 0.000000 -0.038096 0.000000 -0.000581 0.000000 ) +( 0.266975 0.000000 0.000947 0.000000 -0.012705 0.000000 ) +( -0.254985 0.000000 0.038096 0.000000 0.000581 0.000000 ) +( -0.266975 0.000000 -0.000947 0.000000 0.012705 0.000000 ) +( 0.262604 0.000000 0.000019 0.000000 -0.024140 0.000000 ) +( 0.176507 0.000000 -0.029270 0.000000 0.085629 0.000000 ) +( -0.262604 0.000000 -0.000019 0.000000 0.024140 0.000000 ) +( -0.176507 0.000000 0.029270 0.000000 -0.085629 0.000000 ) + freq ( 65) = 107.32504048 [THz] = 3579.97799876 [cm-1] +( -0.169996 0.000000 -0.015578 0.000000 -0.292066 0.000000 ) +( -0.057609 0.000000 0.005567 0.000000 0.073986 0.000000 ) +( -0.169996 0.000000 -0.015578 0.000000 -0.292066 0.000000 ) +( -0.057609 0.000000 0.005567 0.000000 0.073986 0.000000 ) +( 0.173111 0.000000 0.000153 0.000000 0.219238 0.000000 ) +( 0.051599 0.000000 0.011932 0.000000 -0.093693 0.000000 ) +( 0.173111 0.000000 0.000153 0.000000 0.219238 0.000000 ) +( 0.051599 0.000000 0.011932 0.000000 -0.093693 0.000000 ) +( -0.159184 0.000000 0.034432 0.000000 0.335381 0.000000 ) +( 0.001086 0.000000 0.005155 0.000000 0.033194 0.000000 ) +( -0.159184 0.000000 0.034432 0.000000 0.335381 0.000000 ) +( 0.001086 0.000000 0.005155 0.000000 0.033194 0.000000 ) +( -0.175791 0.000000 0.005359 0.000000 0.254085 0.000000 ) +( -0.017421 0.000000 -0.007740 0.000000 0.006686 0.000000 ) +( -0.175791 0.000000 0.005359 0.000000 0.254085 0.000000 ) +( -0.017421 0.000000 -0.007740 0.000000 0.006686 0.000000 ) +( 0.084387 0.000000 -0.000063 0.000000 -0.033988 0.000000 ) +( 0.114879 0.000000 -0.009535 0.000000 0.019643 0.000000 ) +( 0.084387 0.000000 -0.000063 0.000000 -0.033988 0.000000 ) +( 0.114879 0.000000 -0.009535 0.000000 0.019643 0.000000 ) +( 0.026185 0.000000 -0.012324 0.000000 0.049820 0.000000 ) +( 0.159852 0.000000 -0.007801 0.000000 0.014126 0.000000 ) +( 0.026185 0.000000 -0.012324 0.000000 0.049820 0.000000 ) +( 0.159852 0.000000 -0.007801 0.000000 0.014126 0.000000 ) + freq ( 66) = 109.83029818 [THz] = 3663.54440059 [cm-1] +( -0.089259 0.000000 0.007217 0.000000 -0.026233 0.000000 ) +( -0.114523 0.000000 -0.010236 0.000000 0.224167 0.000000 ) +( -0.089259 0.000000 0.007217 0.000000 -0.026233 0.000000 ) +( -0.114523 0.000000 -0.010236 0.000000 0.224167 0.000000 ) +( 0.053774 0.000000 0.022035 0.000000 0.156647 0.000000 ) +( 0.164931 0.000000 -0.006186 0.000000 -0.223080 0.000000 ) +( 0.053774 0.000000 0.022035 0.000000 0.156647 0.000000 ) +( 0.164931 0.000000 -0.006186 0.000000 -0.223080 0.000000 ) +( 0.138014 0.000000 -0.018617 0.000000 -0.243326 0.000000 ) +( 0.127298 0.000000 0.009520 0.000000 0.264923 0.000000 ) +( 0.138014 0.000000 -0.018617 0.000000 -0.243326 0.000000 ) +( 0.127298 0.000000 0.009520 0.000000 0.264923 0.000000 ) +( 0.095345 0.000000 -0.004895 0.000000 -0.219130 0.000000 ) +( -0.131597 0.000000 0.028186 0.000000 -0.142261 0.000000 ) +( 0.095345 0.000000 -0.004895 0.000000 -0.219130 0.000000 ) +( -0.131597 0.000000 0.028186 0.000000 -0.142261 0.000000 ) +( 0.045040 0.000000 0.019163 0.000000 0.010405 0.000000 ) +( 0.112984 0.000000 -0.000587 0.000000 0.018990 0.000000 ) +( 0.045040 0.000000 0.019163 0.000000 0.010405 0.000000 ) +( 0.112984 0.000000 -0.000587 0.000000 0.018990 0.000000 ) +( 0.105895 0.000000 -0.016694 0.000000 -0.033421 0.000000 ) +( 0.183864 0.000000 -0.015172 0.000000 0.007749 0.000000 ) +( 0.105895 0.000000 -0.016694 0.000000 -0.033421 0.000000 ) +( 0.183864 0.000000 -0.015172 0.000000 0.007749 0.000000 ) + freq ( 67) = 110.53973944 [THz] = 3687.20881354 [cm-1] +( -0.155835 0.000000 0.007682 0.000000 -0.319197 0.000000 ) +( -0.019011 0.000000 0.007188 0.000000 0.017567 0.000000 ) +( 0.155835 0.000000 -0.007682 0.000000 0.319197 0.000000 ) +( 0.019011 0.000000 -0.007188 0.000000 -0.017567 0.000000 ) +( 0.199374 0.000000 0.030869 0.000000 0.231787 0.000000 ) +( 0.009660 0.000000 0.013788 0.000000 -0.026606 0.000000 ) +( -0.199374 0.000000 -0.030869 0.000000 -0.231787 0.000000 ) +( -0.009660 0.000000 -0.013788 0.000000 0.026606 0.000000 ) +( -0.174097 0.000000 0.016097 0.000000 0.295613 0.000000 ) +( 0.080642 0.000000 -0.020559 0.000000 0.153379 0.000000 ) +( 0.174097 0.000000 -0.016097 0.000000 -0.295613 0.000000 ) +( -0.080642 0.000000 0.020559 0.000000 -0.153379 0.000000 ) +( -0.152062 0.000000 0.013404 0.000000 0.243088 0.000000 ) +( -0.069510 0.000000 0.002610 0.000000 -0.149238 0.000000 ) +( 0.152062 0.000000 -0.013404 0.000000 -0.243088 0.000000 ) +( 0.069510 0.000000 -0.002610 0.000000 0.149238 0.000000 ) +( -0.019892 0.000000 0.015737 0.000000 -0.031092 0.000000 ) +( -0.060177 0.000000 -0.000147 0.000000 -0.017731 0.000000 ) +( 0.019892 0.000000 -0.015737 0.000000 0.031092 0.000000 ) +( 0.060177 0.000000 0.000147 0.000000 0.017731 0.000000 ) +( -0.064750 0.000000 0.006452 0.000000 0.093432 0.000000 ) +( -0.027662 0.000000 0.000683 0.000000 0.021025 0.000000 ) +( 0.064750 0.000000 -0.006452 0.000000 -0.093432 0.000000 ) +( 0.027662 0.000000 -0.000683 0.000000 -0.021025 0.000000 ) + freq ( 68) = 112.34413482 [THz] = 3747.39696492 [cm-1] +( -0.119653 0.000000 0.001121 -0.000000 -0.084410 -0.000000 ) +( -0.011692 0.000000 -0.003716 0.000000 0.021695 0.000000 ) +( 0.119653 -0.000000 -0.001121 0.000000 0.084410 0.000000 ) +( 0.011692 -0.000000 0.003716 -0.000000 -0.021695 -0.000000 ) +( 0.085124 -0.000000 -0.013622 0.000000 0.169751 0.000000 ) +( 0.024329 -0.000000 0.003404 -0.000000 -0.038152 -0.000000 ) +( -0.085124 0.000000 0.013622 -0.000000 -0.169751 -0.000000 ) +( -0.024329 0.000000 -0.003404 0.000000 0.038152 0.000000 ) +( 0.167796 -0.000000 -0.011087 0.000000 -0.300145 0.000000 ) +( 0.121121 -0.000000 -0.017038 0.000000 0.235232 0.000000 ) +( -0.167796 0.000000 0.011087 -0.000000 0.300145 -0.000000 ) +( -0.121121 0.000000 0.017038 -0.000000 -0.235232 -0.000000 ) +( 0.147841 -0.000000 -0.036233 0.000000 -0.275718 0.000000 ) +( -0.112083 0.000000 0.021531 -0.000000 -0.213246 -0.000000 ) +( -0.147841 0.000000 0.036233 -0.000000 0.275718 -0.000000 ) +( 0.112083 -0.000000 -0.021531 0.000000 0.213246 0.000000 ) +( -0.114012 0.000000 -0.004767 0.000000 0.042217 0.000000 ) +( -0.203086 0.000000 0.032632 -0.000000 -0.020234 -0.000000 ) +( 0.114012 -0.000000 0.004767 -0.000000 -0.042217 -0.000000 ) +( 0.203086 -0.000000 -0.032632 0.000000 0.020234 0.000000 ) +( -0.053818 0.000000 0.011602 -0.000000 -0.032515 -0.000000 ) +( -0.177935 0.000000 0.002516 -0.000000 -0.001434 -0.000000 ) +( 0.053818 -0.000000 -0.011602 0.000000 0.032515 0.000000 ) +( 0.177935 -0.000000 -0.002516 0.000000 0.001434 0.000000 ) + freq ( 69) = 114.50771801 [THz] = 3819.56633168 [cm-1] +( 0.062366 0.000000 0.004958 0.000000 0.141327 0.000000 ) +( -0.083008 0.000000 -0.010970 0.000000 0.114707 0.000000 ) +( 0.062366 0.000000 0.004958 0.000000 0.141327 0.000000 ) +( -0.083008 0.000000 -0.010970 0.000000 0.114707 0.000000 ) +( -0.086503 0.000000 0.005173 0.000000 -0.090987 0.000000 ) +( 0.087285 0.000000 0.017651 0.000000 -0.127380 0.000000 ) +( -0.086503 0.000000 0.005173 0.000000 -0.090987 0.000000 ) +( 0.087285 0.000000 0.017651 0.000000 -0.127380 0.000000 ) +( 0.021037 0.000000 -0.002626 0.000000 -0.022515 0.000000 ) +( -0.170937 0.000000 0.029843 0.000000 -0.274498 0.000000 ) +( 0.021037 0.000000 -0.002626 0.000000 -0.022515 0.000000 ) +( -0.170937 0.000000 0.029843 0.000000 -0.274498 0.000000 ) +( -0.005586 0.000000 0.000828 0.000000 -0.018095 0.000000 ) +( 0.143384 0.000000 -0.017744 0.000000 0.323653 0.000000 ) +( -0.005586 0.000000 0.000828 0.000000 -0.018095 0.000000 ) +( 0.143384 0.000000 -0.017744 0.000000 0.323653 0.000000 ) +( 0.205780 0.000000 -0.010004 0.000000 -0.007916 0.000000 ) +( 0.203471 0.000000 0.004422 0.000000 0.043480 0.000000 ) +( 0.205780 0.000000 -0.010004 0.000000 -0.007916 0.000000 ) +( 0.203471 0.000000 0.004422 0.000000 0.043480 0.000000 ) +( 0.211659 0.000000 -0.006438 0.000000 -0.038142 0.000000 ) +( 0.223629 0.000000 -0.018718 0.000000 -0.033546 0.000000 ) +( 0.211659 0.000000 -0.006438 0.000000 -0.038142 0.000000 ) +( 0.223629 0.000000 -0.018718 0.000000 -0.033546 0.000000 ) + freq ( 70) = 114.74830815 [THz] = 3827.59155480 [cm-1] +( -0.077188 0.000000 0.014451 -0.000000 -0.032999 -0.000000 ) +( -0.183083 0.000000 0.004623 -0.000000 0.280797 -0.000000 ) +( 0.077188 -0.000000 -0.014451 0.000000 0.032999 0.000000 ) +( 0.183083 -0.000000 -0.004623 0.000000 -0.280797 0.000000 ) +( 0.050972 -0.000000 0.018848 -0.000000 0.118245 -0.000000 ) +( 0.205919 -0.000000 0.025992 -0.000000 -0.319916 -0.000000 ) +( -0.050972 0.000000 -0.018848 0.000000 -0.118245 0.000000 ) +( -0.205919 0.000000 -0.025992 0.000000 0.319916 0.000000 ) +( 0.047049 -0.000000 0.009615 -0.000000 -0.072224 -0.000000 ) +( 0.005424 -0.000000 -0.012282 0.000000 0.082791 0.000000 ) +( -0.047049 0.000000 -0.009615 0.000000 0.072224 0.000000 ) +( -0.005424 0.000000 0.012282 -0.000000 -0.082791 -0.000000 ) +( 0.013195 -0.000000 -0.010438 0.000000 -0.072173 0.000000 ) +( -0.036883 0.000000 -0.003783 0.000000 0.070249 0.000000 ) +( -0.013195 0.000000 0.010438 -0.000000 0.072173 -0.000000 ) +( 0.036883 -0.000000 0.003783 -0.000000 -0.070249 -0.000000 ) +( 0.086584 -0.000000 0.009303 -0.000000 0.008932 -0.000000 ) +( 0.230244 -0.000000 -0.006910 0.000000 0.061075 0.000000 ) +( -0.086584 0.000000 -0.009303 0.000000 -0.008932 0.000000 ) +( -0.230244 0.000000 0.006910 -0.000000 -0.061075 -0.000000 ) +( 0.112669 -0.000000 -0.009788 0.000000 -0.026210 0.000000 ) +( 0.335835 0.000000 -0.007579 0.000000 -0.029413 0.000000 ) +( -0.112669 0.000000 0.009788 -0.000000 0.026210 -0.000000 ) +( -0.335835 0.000000 0.007579 -0.000000 0.029413 -0.000000 ) + freq ( 71) = 119.91915161 [THz] = 4000.07232690 [cm-1] +( 0.071340 0.000000 0.000039 0.000000 0.129747 0.000000 ) +( -0.073879 0.000000 -0.006879 0.000000 0.090389 0.000000 ) +( 0.071340 0.000000 0.000039 0.000000 0.129747 0.000000 ) +( -0.073879 0.000000 -0.006879 0.000000 0.090389 0.000000 ) +( -0.122457 0.000000 -0.017654 0.000000 -0.154217 0.000000 ) +( 0.065567 0.000000 0.005284 0.000000 -0.111522 0.000000 ) +( -0.122457 0.000000 -0.017654 0.000000 -0.154217 0.000000 ) +( 0.065567 0.000000 0.005284 0.000000 -0.111522 0.000000 ) +( -0.068126 0.000000 0.003346 0.000000 0.132912 0.000000 ) +( 0.089186 0.000000 0.010164 0.000000 0.157699 0.000000 ) +( -0.068126 0.000000 0.003346 0.000000 0.132912 0.000000 ) +( 0.089186 0.000000 0.010164 0.000000 0.157699 0.000000 ) +( -0.082680 0.000000 -0.004665 0.000000 0.136190 0.000000 ) +( -0.064871 0.000000 0.020618 0.000000 -0.120134 0.000000 ) +( -0.082680 0.000000 -0.004665 0.000000 0.136190 0.000000 ) +( -0.064871 0.000000 0.020618 0.000000 -0.120134 0.000000 ) +( 0.324764 0.000000 -0.002783 0.000000 -0.026654 0.000000 ) +( -0.252347 0.000000 -0.006444 0.000000 -0.016177 0.000000 ) +( 0.324764 0.000000 -0.002783 0.000000 -0.026654 0.000000 ) +( -0.252347 0.000000 -0.006444 0.000000 -0.016177 0.000000 ) +( 0.296365 0.000000 -0.014901 0.000000 -0.019770 0.000000 ) +( -0.223015 0.000000 0.005575 0.000000 -0.021136 0.000000 ) +( 0.296365 0.000000 -0.014901 0.000000 -0.019770 0.000000 ) +( -0.223015 0.000000 0.005575 0.000000 -0.021136 0.000000 ) + freq ( 72) = 120.80094369 [THz] = 4029.48574463 [cm-1] +( 0.093432 -0.000000 0.005411 -0.000000 0.158420 -0.000000 ) +( -0.102024 0.000000 -0.006744 0.000000 0.141669 0.000000 ) +( -0.093432 0.000000 -0.005411 0.000000 -0.158420 0.000000 ) +( 0.102024 -0.000000 0.006744 -0.000000 -0.141669 -0.000000 ) +( -0.126696 0.000000 -0.011397 0.000000 -0.198009 0.000000 ) +( 0.106601 -0.000000 0.023454 -0.000000 -0.163536 -0.000000 ) +( 0.126696 -0.000000 0.011397 -0.000000 0.198009 -0.000000 ) +( -0.106601 0.000000 -0.023454 0.000000 0.163536 0.000000 ) +( -0.056703 0.000000 -0.010387 0.000000 0.100312 0.000000 ) +( 0.084357 -0.000000 -0.015656 0.000000 0.167949 0.000000 ) +( 0.056703 -0.000000 0.010387 -0.000000 -0.100312 -0.000000 ) +( -0.084357 0.000000 0.015656 -0.000000 -0.167949 -0.000000 ) +( -0.053651 0.000000 0.020550 -0.000000 0.098353 -0.000000 ) +( -0.068116 0.000000 0.001720 -0.000000 -0.121115 -0.000000 ) +( 0.053651 -0.000000 -0.020550 0.000000 -0.098353 0.000000 ) +( 0.068116 -0.000000 -0.001720 0.000000 0.121115 0.000000 ) +( 0.278516 0.000000 0.014536 -0.000000 -0.018566 -0.000000 ) +( -0.266831 0.000000 0.001309 -0.000000 -0.012783 -0.000000 ) +( -0.278516 0.000000 -0.014536 0.000000 0.018566 0.000000 ) +( 0.266831 -0.000000 -0.001309 0.000000 0.012783 0.000000 ) +( 0.248620 -0.000000 -0.020244 0.000000 -0.016462 0.000000 ) +( -0.216297 0.000000 0.023333 -0.000000 -0.031947 -0.000000 ) +( -0.248620 0.000000 0.020244 -0.000000 0.016462 -0.000000 ) +( 0.216297 -0.000000 -0.023333 0.000000 0.031947 0.000000 ) +*************************************************************************** diff --git a/tests/aiida_ensemble/dyn3 b/tests/aiida_ensemble/dyn3 new file mode 100644 index 00000000..07ab051c --- /dev/null +++ b/tests/aiida_ensemble/dyn3 @@ -0,0 +1,4148 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 24 0 5.36307068 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 +Basis vectors + 0.49334568 0.01129550 -0.85311514 + -0.03458521 1.75181777 0.00000000 + 0.49334568 0.01129550 0.85311514 + 1 'H ' 918.73579607 + 1 1 0.5519365595 0.2313707631 -0.1692669144 + 2 1 0.4174621950 0.6671291184 -0.1692669144 + 3 1 0.4001695915 1.5430380039 0.1692669144 + 4 1 0.5346439560 1.1072796486 0.1692669144 + 5 1 0.6981106437 0.2360660957 0.0464225528 + 6 1 0.2712881108 0.6624337858 0.0464225528 + 7 1 0.2539955073 1.5383426713 -0.0464225528 + 8 1 0.6808180402 1.1119749812 -0.0464225528 + 9 1 0.6732076478 0.2102400630 0.5104913056 + 10 1 0.2961911067 0.6882598185 0.5104913056 + 11 1 0.2788985032 1.5641687040 -0.5104913056 + 12 1 0.6559150443 1.0861489485 -0.5104913056 + 13 1 0.0576044735 0.2147663837 -0.1115184507 + 14 1 0.9117942810 0.6837334978 -0.1115184507 + 15 1 0.8945016775 1.5596423833 0.1115184507 + 16 1 0.0403118700 1.0906752692 0.1115184507 + 17 1 1.0881087549 0.2679292681 0.2995449619 + 18 1 -0.1187100004 0.6305706134 0.2995449619 + 19 1 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0.00000000 + 0.02612168 0.00000000 -0.00549414 0.00000000 0.17228904 0.00000000 + + Diagonalizing the dynamical matrix + + q = ( -1.013030243 -0.019999718 0.000000000 ) + +*************************************************************************** + freq ( 1) = 6.62261700 [THz] = 220.90672462 [cm-1] +( 0.176273 -0.000000 0.057314 -0.000000 0.162610 -0.000000 ) +( 0.176273 -0.000000 0.057314 -0.000000 -0.162610 -0.000000 ) +( -0.176273 0.000000 -0.057314 0.000000 -0.162610 0.000000 ) +( -0.176273 0.000000 -0.057314 0.000000 0.162610 0.000000 ) +( 0.217585 -0.000000 -0.045624 0.000000 0.101449 0.000000 ) +( 0.217585 0.000000 -0.045624 0.000000 -0.101449 0.000000 ) +( -0.217585 0.000000 0.045624 -0.000000 -0.101449 -0.000000 ) +( -0.217585 0.000000 0.045624 -0.000000 0.101449 -0.000000 ) +( -0.073145 0.000000 -0.019477 0.000000 0.160097 0.000000 ) +( -0.073145 0.000000 -0.019477 0.000000 -0.160097 0.000000 ) +( 0.073145 -0.000000 0.019477 -0.000000 -0.160097 -0.000000 ) +( 0.073145 -0.000000 0.019477 -0.000000 0.160097 -0.000000 ) +( 0.190834 -0.000000 0.038248 -0.000000 -0.113954 -0.000000 ) +( 0.190834 -0.000000 0.038248 -0.000000 0.113954 -0.000000 ) +( -0.190834 0.000000 -0.038248 0.000000 0.113954 0.000000 ) +( -0.190834 0.000000 -0.038248 0.000000 -0.113954 0.000000 ) +( 0.117316 -0.000000 -0.080888 0.000000 -0.005310 0.000000 ) +( 0.117316 -0.000000 -0.080888 0.000000 0.005310 0.000000 ) +( -0.117316 0.000000 0.080888 -0.000000 0.005310 -0.000000 ) +( -0.117316 0.000000 0.080888 -0.000000 -0.005310 -0.000000 ) +( 0.128460 -0.000000 -0.091822 0.000000 -0.044615 0.000000 ) +( 0.128460 -0.000000 -0.091822 0.000000 0.044615 0.000000 ) +( -0.128460 0.000000 0.091822 -0.000000 0.044615 -0.000000 ) +( -0.128460 0.000000 0.091822 -0.000000 -0.044615 -0.000000 ) + freq ( 2) = 7.27905192 [THz] = 242.80303653 [cm-1] +( 0.098061 0.000000 0.039345 0.000000 0.189198 0.000000 ) +( -0.098061 0.000000 -0.039345 0.000000 0.189198 0.000000 ) +( -0.098061 0.000000 -0.039345 0.000000 -0.189198 0.000000 ) +( 0.098061 0.000000 0.039345 0.000000 -0.189198 0.000000 ) +( 0.214917 0.000000 0.025705 0.000000 0.122183 0.000000 ) +( -0.214917 0.000000 -0.025705 0.000000 0.122183 0.000000 ) +( -0.214917 0.000000 -0.025705 0.000000 -0.122183 0.000000 ) +( 0.214917 0.000000 0.025705 0.000000 -0.122183 0.000000 ) +( -0.052552 0.000000 0.011273 0.000000 0.205116 0.000000 ) +( 0.052552 0.000000 -0.011273 0.000000 0.205116 0.000000 ) +( 0.052552 0.000000 -0.011273 0.000000 -0.205116 0.000000 ) +( -0.052552 0.000000 0.011273 0.000000 -0.205116 0.000000 ) +( 0.164909 0.000000 -0.027989 0.000000 -0.163059 0.000000 ) +( -0.164909 0.000000 0.027989 0.000000 -0.163059 0.000000 ) +( -0.164909 0.000000 0.027989 0.000000 0.163059 0.000000 ) +( 0.164909 0.000000 -0.027989 0.000000 0.163059 0.000000 ) +( 0.106301 0.000000 0.008010 0.000000 -0.088530 0.000000 ) +( -0.106301 0.000000 -0.008010 0.000000 -0.088530 0.000000 ) +( -0.106301 0.000000 -0.008010 0.000000 0.088530 0.000000 ) +( 0.106301 0.000000 0.008010 0.000000 0.088530 0.000000 ) +( 0.142533 0.000000 -0.046343 0.000000 -0.008262 0.000000 ) +( -0.142533 0.000000 0.046343 0.000000 -0.008262 0.000000 ) +( -0.142533 0.000000 0.046343 0.000000 0.008262 0.000000 ) +( 0.142533 0.000000 -0.046343 0.000000 0.008262 0.000000 ) + freq ( 3) = 8.38592618 [THz] = 279.72438754 [cm-1] +( -0.105014 0.000000 -0.002005 0.000000 -0.191983 0.000000 ) +( 0.105014 -0.000000 0.002005 -0.000000 -0.191983 -0.000000 ) +( -0.105014 0.000000 -0.002005 0.000000 -0.191983 0.000000 ) +( 0.105014 -0.000000 0.002005 -0.000000 -0.191983 -0.000000 ) +( -0.234807 0.000000 -0.084330 0.000000 -0.093692 0.000000 ) +( 0.234807 -0.000000 0.084330 -0.000000 -0.093692 -0.000000 ) +( -0.234807 0.000000 -0.084330 0.000000 -0.093692 0.000000 ) +( 0.234807 0.000000 0.084330 -0.000000 -0.093692 -0.000000 ) +( 0.049683 -0.000000 0.055077 -0.000000 -0.215503 -0.000000 ) +( -0.049683 0.000000 -0.055077 0.000000 -0.215503 0.000000 ) +( 0.049683 -0.000000 0.055077 -0.000000 -0.215503 -0.000000 ) +( -0.049683 0.000000 -0.055077 0.000000 -0.215503 0.000000 ) +( -0.151720 0.000000 0.029214 -0.000000 0.183242 -0.000000 ) +( 0.151720 -0.000000 -0.029214 0.000000 0.183242 0.000000 ) +( -0.151720 0.000000 0.029214 -0.000000 0.183242 -0.000000 ) +( 0.151720 -0.000000 -0.029214 0.000000 0.183242 0.000000 ) +( -0.063292 0.000000 0.028234 -0.000000 0.062638 -0.000000 ) +( 0.063292 -0.000000 -0.028234 0.000000 0.062638 0.000000 ) +( -0.063292 0.000000 0.028234 -0.000000 0.062638 -0.000000 ) +( 0.063292 -0.000000 -0.028234 0.000000 0.062638 0.000000 ) +( -0.099017 0.000000 -0.030069 0.000000 -0.047516 0.000000 ) +( 0.099017 -0.000000 0.030069 -0.000000 -0.047516 -0.000000 ) +( -0.099017 0.000000 -0.030069 0.000000 -0.047516 0.000000 ) +( 0.099017 -0.000000 0.030069 -0.000000 -0.047516 -0.000000 ) + freq ( 4) = 18.05374151 [THz] = 602.20799455 [cm-1] +( -0.102950 0.000000 0.119931 0.000000 0.078220 0.000000 ) +( -0.102950 0.000000 0.119931 0.000000 -0.078220 0.000000 ) +( -0.102950 0.000000 0.119931 0.000000 0.078220 0.000000 ) +( -0.102950 0.000000 0.119931 0.000000 -0.078220 0.000000 ) +( 0.005715 0.000000 0.264741 0.000000 -0.010554 0.000000 ) +( 0.005715 0.000000 0.264741 0.000000 0.010554 0.000000 ) +( 0.005715 0.000000 0.264741 0.000000 -0.010554 0.000000 ) +( 0.005715 0.000000 0.264741 0.000000 0.010554 0.000000 ) +( 0.127932 0.000000 -0.049861 0.000000 -0.024966 0.000000 ) +( 0.127932 0.000000 -0.049861 0.000000 0.024966 0.000000 ) +( 0.127932 0.000000 -0.049861 0.000000 -0.024966 0.000000 ) +( 0.127932 0.000000 -0.049861 0.000000 0.024966 0.000000 ) +( -0.061774 0.000000 0.257756 0.000000 0.068460 0.000000 ) +( -0.061774 0.000000 0.257756 0.000000 -0.068460 0.000000 ) +( -0.061774 0.000000 0.257756 0.000000 0.068460 0.000000 ) +( -0.061774 0.000000 0.257756 0.000000 -0.068460 0.000000 ) +( 0.102254 0.000000 0.133749 0.000000 -0.039906 0.000000 ) +( 0.102254 0.000000 0.133749 0.000000 0.039906 0.000000 ) +( 0.102254 0.000000 0.133749 0.000000 -0.039906 0.000000 ) +( 0.102254 0.000000 0.133749 0.000000 0.039906 0.000000 ) +( 0.099493 0.000000 0.118140 0.000000 0.021387 0.000000 ) +( 0.099493 0.000000 0.118140 0.000000 -0.021387 0.000000 ) +( 0.099493 0.000000 0.118140 0.000000 0.021387 0.000000 ) +( 0.099493 0.000000 0.118140 0.000000 -0.021387 0.000000 ) + freq ( 5) = 19.84593642 [THz] = 661.98918196 [cm-1] +( -0.017873 0.000000 0.112567 0.000000 -0.046614 0.000000 ) +( -0.017873 0.000000 0.112567 0.000000 0.046614 0.000000 ) +( 0.017873 0.000000 -0.112567 0.000000 0.046614 0.000000 ) +( 0.017873 0.000000 -0.112567 0.000000 -0.046614 0.000000 ) +( 0.000517 0.000000 -0.136232 0.000000 -0.021848 0.000000 ) +( 0.000517 0.000000 -0.136232 0.000000 0.021848 0.000000 ) +( -0.000517 0.000000 0.136232 0.000000 0.021848 0.000000 ) +( -0.000517 0.000000 0.136232 0.000000 -0.021848 0.000000 ) +( -0.257390 0.000000 0.044453 0.000000 0.045647 0.000000 ) +( -0.257390 0.000000 0.044453 0.000000 -0.045647 0.000000 ) +( 0.257390 0.000000 -0.044453 0.000000 -0.045647 0.000000 ) +( 0.257390 0.000000 -0.044453 0.000000 0.045647 0.000000 ) +( -0.012086 0.000000 -0.063513 0.000000 -0.202763 0.000000 ) +( -0.012086 0.000000 -0.063513 0.000000 0.202763 0.000000 ) +( 0.012086 0.000000 0.063513 0.000000 0.202763 0.000000 ) +( 0.012086 0.000000 0.063513 0.000000 -0.202763 0.000000 ) +( -0.215088 0.000000 -0.010967 0.000000 0.105390 0.000000 ) +( -0.215088 0.000000 -0.010967 0.000000 -0.105390 0.000000 ) +( 0.215088 0.000000 0.010967 0.000000 -0.105390 0.000000 ) +( 0.215088 0.000000 0.010967 0.000000 0.105390 0.000000 ) +( -0.194488 0.000000 -0.043229 0.000000 -0.054887 0.000000 ) +( -0.194488 0.000000 -0.043229 0.000000 0.054887 0.000000 ) +( 0.194488 0.000000 0.043229 0.000000 0.054887 0.000000 ) +( 0.194488 0.000000 0.043229 0.000000 -0.054887 0.000000 ) + freq ( 6) = 21.45403656 [THz] = 715.62962857 [cm-1] +( 0.059736 0.000000 -0.203860 0.000000 0.051981 0.000000 ) +( 0.059736 0.000000 -0.203860 0.000000 -0.051981 0.000000 ) +( -0.059736 0.000000 0.203860 0.000000 -0.051981 0.000000 ) +( -0.059736 0.000000 0.203860 0.000000 0.051981 0.000000 ) +( 0.052749 0.000000 0.083570 0.000000 0.052352 0.000000 ) +( 0.052749 0.000000 0.083570 0.000000 -0.052352 0.000000 ) +( -0.052749 0.000000 -0.083570 0.000000 -0.052352 0.000000 ) +( -0.052749 0.000000 -0.083570 0.000000 0.052352 0.000000 ) +( -0.071419 0.000000 0.211811 0.000000 0.033527 0.000000 ) +( -0.071419 0.000000 0.211811 0.000000 -0.033527 0.000000 ) +( 0.071419 0.000000 -0.211811 0.000000 -0.033527 0.000000 ) +( 0.071419 0.000000 -0.211811 0.000000 0.033527 0.000000 ) +( 0.050290 0.000000 -0.170299 0.000000 -0.062246 0.000000 ) +( 0.050290 0.000000 -0.170299 0.000000 0.062246 0.000000 ) +( -0.050290 0.000000 0.170299 0.000000 0.062246 0.000000 ) +( -0.050290 0.000000 0.170299 0.000000 -0.062246 0.000000 ) +( 0.001005 0.000000 0.205160 0.000000 -0.006144 0.000000 ) +( 0.001005 0.000000 0.205160 0.000000 0.006144 0.000000 ) +( -0.001005 0.000000 -0.205160 0.000000 0.006144 0.000000 ) +( -0.001005 0.000000 -0.205160 0.000000 -0.006144 0.000000 ) +( 0.005731 0.000000 0.245244 0.000000 -0.029368 0.000000 ) +( 0.005731 0.000000 0.245244 0.000000 0.029368 0.000000 ) +( -0.005731 0.000000 -0.245244 0.000000 0.029368 0.000000 ) +( -0.005731 0.000000 -0.245244 0.000000 -0.029368 0.000000 ) + freq ( 7) = 21.73476692 [THz] = 724.99378562 [cm-1] +( -0.201309 0.000000 0.138079 -0.000000 -0.011418 -0.000000 ) +( 0.201309 -0.000000 -0.138079 0.000000 -0.011418 0.000000 ) +( 0.201309 0.000000 -0.138079 0.000000 0.011418 0.000000 ) +( -0.201309 0.000000 0.138079 -0.000000 0.011418 -0.000000 ) +( 0.041919 -0.000000 -0.047339 0.000000 -0.134121 0.000000 ) +( -0.041919 0.000000 0.047339 -0.000000 -0.134121 -0.000000 ) +( -0.041919 0.000000 0.047339 -0.000000 0.134121 -0.000000 ) +( 0.041919 -0.000000 -0.047339 0.000000 0.134121 0.000000 ) +( 0.190242 -0.000000 0.186648 -0.000000 0.021076 -0.000000 ) +( -0.190242 0.000000 -0.186648 0.000000 0.021076 0.000000 ) +( -0.190242 0.000000 -0.186648 0.000000 -0.021076 0.000000 ) +( 0.190242 -0.000000 0.186648 -0.000000 -0.021076 -0.000000 ) +( -0.099144 0.000000 -0.007152 0.000000 0.020344 0.000000 ) +( 0.099144 -0.000000 0.007152 -0.000000 0.020344 -0.000000 ) +( 0.099144 -0.000000 0.007152 -0.000000 -0.020344 -0.000000 ) +( -0.099144 0.000000 -0.007152 0.000000 -0.020344 0.000000 ) +( 0.171838 -0.000000 0.140180 -0.000000 -0.013452 -0.000000 ) +( -0.171838 0.000000 -0.140180 0.000000 -0.013452 0.000000 ) +( -0.171838 0.000000 -0.140180 0.000000 0.013452 0.000000 ) +( 0.171838 -0.000000 0.140180 -0.000000 0.013452 -0.000000 ) +( 0.155959 -0.000000 -0.113182 0.000000 -0.005522 0.000000 ) +( -0.155959 0.000000 0.113182 -0.000000 -0.005522 -0.000000 ) +( -0.155959 0.000000 0.113182 -0.000000 0.005522 -0.000000 ) +( 0.155959 -0.000000 -0.113182 0.000000 0.005522 0.000000 ) + freq ( 8) = 22.50403553 [THz] = 750.65382435 [cm-1] +( 0.206846 0.000000 -0.074312 0.000000 0.167577 0.000000 ) +( 0.206846 0.000000 -0.074312 0.000000 -0.167577 0.000000 ) +( 0.206846 0.000000 -0.074312 0.000000 0.167577 0.000000 ) +( 0.206846 0.000000 -0.074312 0.000000 -0.167577 0.000000 ) +( 0.211327 0.000000 0.008115 0.000000 0.114984 0.000000 ) +( 0.211327 0.000000 0.008115 0.000000 -0.114984 0.000000 ) +( 0.211327 0.000000 0.008115 0.000000 0.114984 0.000000 ) +( 0.211327 0.000000 0.008115 0.000000 -0.114984 0.000000 ) +( -0.059336 0.000000 -0.025025 0.000000 0.145801 0.000000 ) +( -0.059336 0.000000 -0.025025 0.000000 -0.145801 0.000000 ) +( -0.059336 0.000000 -0.025025 0.000000 0.145801 0.000000 ) +( -0.059336 0.000000 -0.025025 0.000000 -0.145801 0.000000 ) +( 0.185245 0.000000 0.025439 0.000000 -0.079373 0.000000 ) +( 0.185245 0.000000 0.025439 0.000000 0.079373 0.000000 ) +( 0.185245 0.000000 0.025439 0.000000 -0.079373 0.000000 ) +( 0.185245 0.000000 0.025439 0.000000 0.079373 0.000000 ) +( 0.151476 0.000000 0.009354 0.000000 -0.024691 0.000000 ) +( 0.151476 0.000000 0.009354 0.000000 0.024691 0.000000 ) +( 0.151476 0.000000 0.009354 0.000000 -0.024691 0.000000 ) +( 0.151476 0.000000 0.009354 0.000000 0.024691 0.000000 ) +( 0.153920 0.000000 0.024677 0.000000 -0.032460 0.000000 ) +( 0.153920 0.000000 0.024677 0.000000 0.032460 0.000000 ) +( 0.153920 0.000000 0.024677 0.000000 -0.032460 0.000000 ) +( 0.153920 0.000000 0.024677 0.000000 0.032460 0.000000 ) + freq ( 9) = 23.69499562 [THz] = 790.37997674 [cm-1] +( 0.150571 -0.000000 0.291777 0.000000 -0.094801 0.000000 ) +( 0.150571 -0.000000 0.291777 -0.000000 0.094801 -0.000000 ) +( 0.150571 -0.000000 0.291777 -0.000000 -0.094801 -0.000000 ) +( 0.150571 -0.000000 0.291777 -0.000000 0.094801 -0.000000 ) +( 0.021288 -0.000000 0.027728 -0.000000 0.013003 -0.000000 ) +( 0.021288 -0.000000 0.027728 -0.000000 -0.013003 -0.000000 ) +( 0.021288 -0.000000 0.027728 -0.000000 0.013003 -0.000000 ) +( 0.021288 -0.000000 0.027728 -0.000000 -0.013003 -0.000000 ) +( -0.168216 0.000000 -0.023737 0.000000 0.012882 0.000000 ) +( -0.168216 0.000000 -0.023737 0.000000 -0.012882 0.000000 ) +( -0.168216 0.000000 -0.023737 0.000000 0.012882 0.000000 ) +( -0.168216 0.000000 -0.023737 0.000000 -0.012882 0.000000 ) +( 0.123417 -0.000000 0.104591 -0.000000 -0.060342 -0.000000 ) +( 0.123417 -0.000000 0.104591 -0.000000 0.060342 -0.000000 ) +( 0.123417 -0.000000 0.104591 -0.000000 -0.060342 -0.000000 ) +( 0.123417 -0.000000 0.104591 -0.000000 0.060342 -0.000000 ) +( -0.135802 0.000000 0.120567 -0.000000 0.125054 -0.000000 ) +( -0.135802 0.000000 0.120567 -0.000000 -0.125054 -0.000000 ) +( -0.135802 0.000000 0.120567 -0.000000 0.125054 -0.000000 ) +( -0.135802 0.000000 0.120567 -0.000000 -0.125054 -0.000000 ) +( -0.145258 0.000000 0.035636 -0.000000 -0.044620 -0.000000 ) +( -0.145258 0.000000 0.035636 -0.000000 0.044620 -0.000000 ) +( -0.145258 0.000000 0.035636 -0.000000 -0.044620 -0.000000 ) +( -0.145258 0.000000 0.035636 -0.000000 0.044620 -0.000000 ) + freq ( 10) = 23.81451092 [THz] = 794.36657817 [cm-1] +( 0.286709 0.000000 0.080986 -0.000000 -0.111844 -0.000000 ) +( -0.286709 0.000000 -0.080986 0.000000 -0.111844 0.000000 ) +( 0.286709 -0.000000 0.080986 -0.000000 -0.111844 -0.000000 ) +( -0.286709 0.000000 -0.080986 0.000000 -0.111844 0.000000 ) +( 0.003836 -0.000000 -0.002411 0.000000 0.061764 0.000000 ) +( -0.003836 0.000000 0.002411 -0.000000 0.061764 -0.000000 ) +( 0.003836 -0.000000 -0.002411 0.000000 0.061764 0.000000 ) +( -0.003836 0.000000 0.002411 -0.000000 0.061764 -0.000000 ) +( -0.139582 0.000000 0.090335 -0.000000 -0.022240 -0.000000 ) +( 0.139582 -0.000000 -0.090335 0.000000 -0.022240 0.000000 ) +( -0.139582 0.000000 0.090335 -0.000000 -0.022240 -0.000000 ) +( 0.139582 -0.000000 -0.090335 0.000000 -0.022240 0.000000 ) +( 0.187789 -0.000000 0.056683 -0.000000 0.028614 -0.000000 ) +( -0.187789 0.000000 -0.056683 0.000000 0.028614 0.000000 ) +( 0.187789 -0.000000 0.056683 -0.000000 0.028614 -0.000000 ) +( -0.187789 0.000000 -0.056683 0.000000 0.028614 0.000000 ) +( -0.112094 0.000000 -0.073440 0.000000 0.162953 0.000000 ) +( 0.112094 -0.000000 0.073440 -0.000000 0.162953 -0.000000 ) +( -0.112094 0.000000 -0.073440 0.000000 0.162953 0.000000 ) +( 0.112094 -0.000000 0.073440 -0.000000 0.162953 -0.000000 ) +( -0.133696 0.000000 0.008156 -0.000000 -0.122502 -0.000000 ) +( 0.133696 -0.000000 -0.008156 0.000000 -0.122502 0.000000 ) +( -0.133696 0.000000 0.008156 -0.000000 -0.122502 -0.000000 ) +( 0.133696 -0.000000 -0.008156 0.000000 -0.122502 0.000000 ) + freq ( 11) = 23.87522068 [THz] = 796.39163782 [cm-1] +( 0.257925 -0.000000 -0.029101 0.000000 -0.173737 0.000000 ) +( 0.257925 0.000000 -0.029101 0.000000 0.173737 0.000000 ) +( -0.257925 0.000000 0.029101 -0.000000 0.173737 -0.000000 ) +( -0.257925 0.000000 0.029101 -0.000000 -0.173737 -0.000000 ) +( -0.073914 0.000000 -0.049486 0.000000 0.048672 0.000000 ) +( -0.073914 0.000000 -0.049486 0.000000 -0.048672 0.000000 ) +( 0.073914 -0.000000 0.049486 -0.000000 -0.048672 -0.000000 ) +( 0.073914 -0.000000 0.049486 -0.000000 0.048672 -0.000000 ) +( -0.053026 0.000000 -0.108924 0.000000 -0.111508 0.000000 ) +( -0.053026 0.000000 -0.108924 0.000000 0.111508 0.000000 ) +( 0.053026 -0.000000 0.108924 -0.000000 0.111508 -0.000000 ) +( 0.053026 -0.000000 0.108924 -0.000000 -0.111508 -0.000000 ) +( 0.023571 -0.000000 0.028458 -0.000000 0.095160 -0.000000 ) +( 0.023571 -0.000000 0.028458 -0.000000 -0.095160 -0.000000 ) +( -0.023571 0.000000 -0.028458 0.000000 -0.095160 0.000000 ) +( -0.023571 0.000000 -0.028458 0.000000 0.095160 0.000000 ) +( 0.062063 -0.000000 -0.029199 0.000000 0.210335 0.000000 ) +( 0.062063 -0.000000 -0.029199 0.000000 -0.210335 0.000000 ) +( -0.062063 0.000000 0.029199 -0.000000 -0.210335 -0.000000 ) +( -0.062063 0.000000 0.029199 -0.000000 0.210335 -0.000000 ) +( 0.020708 -0.000000 0.109165 -0.000000 -0.208183 -0.000000 ) +( 0.020708 -0.000000 0.109165 -0.000000 0.208183 -0.000000 ) +( -0.020708 0.000000 -0.109165 0.000000 0.208183 0.000000 ) +( -0.020708 0.000000 -0.109165 0.000000 -0.208183 0.000000 ) + freq ( 12) = 26.60307574 [THz] = 887.38308800 [cm-1] +( -0.133533 0.000000 0.117359 -0.000000 0.136601 -0.000000 ) +( -0.133533 0.000000 0.117359 -0.000000 -0.136601 -0.000000 ) +( -0.133533 0.000000 0.117359 -0.000000 0.136601 -0.000000 ) +( -0.133533 0.000000 0.117359 -0.000000 -0.136601 -0.000000 ) +( 0.112793 -0.000000 -0.089374 0.000000 -0.034921 0.000000 ) +( 0.112793 -0.000000 -0.089374 0.000000 0.034921 0.000000 ) +( 0.112793 -0.000000 -0.089374 0.000000 -0.034921 0.000000 ) +( 0.112793 -0.000000 -0.089374 0.000000 0.034921 0.000000 ) +( 0.008052 -0.000000 0.011367 -0.000000 0.030997 -0.000000 ) +( 0.008052 -0.000000 0.011367 -0.000000 -0.030997 -0.000000 ) +( 0.008052 -0.000000 0.011367 -0.000000 0.030997 -0.000000 ) +( 0.008052 -0.000000 0.011367 -0.000000 -0.030997 -0.000000 ) +( 0.011639 -0.000000 -0.118821 0.000000 0.013702 0.000000 ) +( 0.011639 -0.000000 -0.118821 0.000000 -0.013702 0.000000 ) +( 0.011639 -0.000000 -0.118821 0.000000 0.013702 0.000000 ) +( 0.011639 -0.000000 -0.118821 0.000000 -0.013702 0.000000 ) +( -0.027202 0.000000 0.292481 -0.000000 -0.134941 -0.000000 ) +( -0.027202 0.000000 0.292481 -0.000000 0.134941 -0.000000 ) +( -0.027202 0.000000 0.292481 0.000000 -0.134941 0.000000 ) +( -0.027202 0.000000 0.292481 -0.000000 0.134941 -0.000000 ) +( -0.010131 0.000000 -0.230793 0.000000 0.065935 0.000000 ) +( -0.010131 0.000000 -0.230793 0.000000 -0.065935 0.000000 ) +( -0.010131 0.000000 -0.230793 0.000000 0.065935 0.000000 ) +( -0.010131 0.000000 -0.230793 0.000000 -0.065935 0.000000 ) + freq ( 13) = 27.63231216 [THz] = 921.71471942 [cm-1] +( -0.074575 0.000000 -0.124798 0.000000 0.030147 0.000000 ) +( 0.074575 0.000000 0.124798 0.000000 0.030147 0.000000 ) +( 0.074575 0.000000 0.124798 0.000000 -0.030147 0.000000 ) +( -0.074575 0.000000 -0.124798 0.000000 -0.030147 0.000000 ) +( -0.023074 0.000000 0.212800 0.000000 -0.033001 0.000000 ) +( 0.023074 0.000000 -0.212800 0.000000 -0.033001 0.000000 ) +( 0.023074 0.000000 -0.212800 0.000000 0.033001 0.000000 ) +( -0.023074 0.000000 0.212800 0.000000 0.033001 0.000000 ) +( 0.088458 0.000000 0.201456 0.000000 0.023510 0.000000 ) +( -0.088458 0.000000 -0.201456 0.000000 0.023510 0.000000 ) +( -0.088458 0.000000 -0.201456 0.000000 -0.023510 0.000000 ) +( 0.088458 0.000000 0.201456 0.000000 -0.023510 0.000000 ) +( 0.109391 0.000000 0.130610 0.000000 0.048361 0.000000 ) +( -0.109391 0.000000 -0.130610 0.000000 0.048361 0.000000 ) +( -0.109391 0.000000 -0.130610 0.000000 -0.048361 0.000000 ) +( 0.109391 0.000000 0.130610 0.000000 -0.048361 0.000000 ) +( -0.058022 0.000000 -0.256765 0.000000 -0.078470 0.000000 ) +( 0.058022 0.000000 0.256765 0.000000 -0.078470 0.000000 ) +( 0.058022 0.000000 0.256765 0.000000 0.078470 0.000000 ) +( -0.058022 0.000000 -0.256765 0.000000 0.078470 0.000000 ) +( -0.013035 0.000000 -0.111429 0.000000 0.112629 0.000000 ) +( 0.013035 0.000000 0.111429 0.000000 0.112629 0.000000 ) +( 0.013035 0.000000 0.111429 0.000000 -0.112629 0.000000 ) +( -0.013035 0.000000 -0.111429 0.000000 -0.112629 0.000000 ) + freq ( 14) = 29.26791697 [THz] = 976.27262346 [cm-1] +( 0.020080 -0.000000 -0.175001 0.000000 0.036392 0.000000 ) +( -0.020080 0.000000 0.175001 -0.000000 0.036392 -0.000000 ) +( 0.020080 -0.000000 -0.175001 0.000000 0.036392 0.000000 ) +( -0.020080 0.000000 0.175001 -0.000000 0.036392 -0.000000 ) +( -0.079377 0.000000 0.169486 -0.000000 0.110682 -0.000000 ) +( 0.079377 -0.000000 -0.169486 0.000000 0.110682 0.000000 ) +( -0.079377 0.000000 0.169486 -0.000000 0.110682 -0.000000 ) +( 0.079377 -0.000000 -0.169486 0.000000 0.110682 0.000000 ) +( -0.154622 0.000000 -0.067177 0.000000 -0.050498 0.000000 ) +( 0.154622 -0.000000 0.067177 -0.000000 -0.050498 -0.000000 ) +( -0.154622 0.000000 -0.067177 0.000000 -0.050498 0.000000 ) +( 0.154622 -0.000000 0.067177 -0.000000 -0.050498 -0.000000 ) +( -0.211890 0.000000 -0.024342 0.000000 -0.125461 0.000000 ) +( 0.211890 -0.000000 0.024342 -0.000000 -0.125461 -0.000000 ) +( -0.211890 0.000000 -0.024342 0.000000 -0.125461 0.000000 ) +( 0.211890 0.000000 0.024342 -0.000000 -0.125461 -0.000000 ) +( -0.114685 0.000000 -0.198067 0.000000 -0.057277 0.000000 ) +( 0.114685 -0.000000 0.198067 -0.000000 -0.057277 -0.000000 ) +( -0.114685 0.000000 -0.198067 0.000000 -0.057277 0.000000 ) +( 0.114685 -0.000000 0.198067 -0.000000 -0.057277 -0.000000 ) +( -0.116741 0.000000 0.094219 -0.000000 -0.000340 -0.000000 ) +( 0.116741 -0.000000 -0.094219 0.000000 -0.000340 0.000000 ) +( -0.116741 0.000000 0.094219 -0.000000 -0.000340 -0.000000 ) +( 0.116741 -0.000000 -0.094219 0.000000 -0.000340 0.000000 ) + freq ( 15) = 29.40183417 [THz] = 980.73962020 [cm-1] +( -0.024071 0.000000 -0.178404 0.000000 -0.005001 0.000000 ) +( -0.024071 0.000000 -0.178404 0.000000 0.005001 0.000000 ) +( 0.024071 0.000000 0.178404 0.000000 0.005001 0.000000 ) +( 0.024071 0.000000 0.178404 0.000000 -0.005001 0.000000 ) +( 0.090656 0.000000 0.035764 0.000000 -0.063285 0.000000 ) +( 0.090656 0.000000 0.035764 0.000000 0.063285 0.000000 ) +( -0.090656 0.000000 -0.035764 0.000000 0.063285 0.000000 ) +( -0.090656 0.000000 -0.035764 0.000000 -0.063285 0.000000 ) +( -0.077247 0.000000 0.143131 0.000000 -0.042871 0.000000 ) +( -0.077247 0.000000 0.143131 0.000000 0.042871 0.000000 ) +( 0.077247 0.000000 -0.143131 0.000000 0.042871 0.000000 ) +( 0.077247 0.000000 -0.143131 0.000000 -0.042871 0.000000 ) +( -0.098424 0.000000 0.275097 0.000000 -0.060407 0.000000 ) +( -0.098424 0.000000 0.275097 0.000000 0.060407 0.000000 ) +( 0.098424 0.000000 -0.275097 0.000000 0.060407 0.000000 ) +( 0.098424 0.000000 -0.275097 0.000000 -0.060407 0.000000 ) +( -0.015625 0.000000 -0.265793 0.000000 -0.037100 0.000000 ) +( -0.015625 0.000000 -0.265793 0.000000 0.037100 0.000000 ) +( 0.015625 0.000000 0.265793 0.000000 0.037100 0.000000 ) +( 0.015625 0.000000 0.265793 0.000000 -0.037100 0.000000 ) +( -0.016180 0.000000 0.113566 0.000000 -0.036515 0.000000 ) +( -0.016180 0.000000 0.113566 0.000000 0.036515 0.000000 ) +( 0.016180 0.000000 -0.113566 0.000000 0.036515 0.000000 ) +( 0.016180 0.000000 -0.113566 0.000000 -0.036515 0.000000 ) + freq ( 16) = 29.49441314 [THz] = 983.82772246 [cm-1] +( 0.136016 -0.000000 -0.188644 0.000000 -0.119322 0.000000 ) +( 0.136016 -0.000000 -0.188644 0.000000 0.119322 0.000000 ) +( 0.136016 -0.000000 -0.188644 0.000000 -0.119322 0.000000 ) +( 0.136016 -0.000000 -0.188644 0.000000 0.119322 0.000000 ) +( -0.099915 0.000000 -0.053933 0.000000 0.022310 0.000000 ) +( -0.099915 0.000000 -0.053933 0.000000 -0.022310 0.000000 ) +( -0.099915 0.000000 -0.053933 0.000000 0.022310 0.000000 ) +( -0.099915 0.000000 -0.053933 0.000000 -0.022310 0.000000 ) +( 0.090682 -0.000000 0.017185 -0.000000 -0.086614 -0.000000 ) +( 0.090682 -0.000000 0.017185 -0.000000 0.086614 -0.000000 ) +( 0.090682 -0.000000 0.017185 -0.000000 -0.086614 -0.000000 ) +( 0.090682 -0.000000 0.017185 -0.000000 0.086614 -0.000000 ) +( 0.099393 -0.000000 0.091897 -0.000000 0.182540 -0.000000 ) +( 0.099393 -0.000000 0.091897 -0.000000 -0.182540 -0.000000 ) +( 0.099393 -0.000000 0.091897 -0.000000 0.182540 -0.000000 ) +( 0.099393 -0.000000 0.091897 -0.000000 -0.182540 -0.000000 ) +( 0.060324 -0.000000 0.233406 0.000000 0.158327 0.000000 ) +( 0.060324 -0.000000 0.233406 -0.000000 -0.158327 -0.000000 ) +( 0.060324 -0.000000 0.233406 -0.000000 0.158327 -0.000000 ) +( 0.060324 -0.000000 0.233406 -0.000000 -0.158327 -0.000000 ) +( 0.025858 -0.000000 -0.127357 0.000000 -0.023381 0.000000 ) +( 0.025858 -0.000000 -0.127357 0.000000 0.023381 0.000000 ) +( 0.025858 -0.000000 -0.127357 0.000000 -0.023381 0.000000 ) +( 0.025858 -0.000000 -0.127357 0.000000 0.023381 0.000000 ) + freq ( 17) = 30.14378346 [THz] = 1005.48838466 [cm-1] +( 0.159603 -0.000000 -0.032647 0.000000 -0.140820 0.000000 ) +( -0.159603 0.000000 0.032647 -0.000000 -0.140820 -0.000000 ) +( -0.159603 0.000000 0.032647 -0.000000 0.140820 -0.000000 ) +( 0.159603 -0.000000 -0.032647 0.000000 0.140820 0.000000 ) +( 0.003801 -0.000000 0.128145 -0.000000 -0.073318 -0.000000 ) +( -0.003801 0.000000 -0.128145 0.000000 -0.073318 0.000000 ) +( -0.003801 0.000000 -0.128145 0.000000 0.073318 0.000000 ) +( 0.003801 -0.000000 0.128145 -0.000000 0.073318 -0.000000 ) +( 0.158567 -0.000000 -0.099474 0.000000 0.004215 0.000000 ) +( -0.158567 0.000000 0.099474 -0.000000 0.004215 -0.000000 ) +( -0.158567 0.000000 0.099474 -0.000000 -0.004215 -0.000000 ) +( 0.158567 -0.000000 -0.099474 0.000000 -0.004215 0.000000 ) +( 0.236065 0.000000 -0.140616 0.000000 0.183647 0.000000 ) +( -0.236065 0.000000 0.140616 -0.000000 0.183647 -0.000000 ) +( -0.236065 0.000000 0.140616 -0.000000 -0.183647 -0.000000 ) +( 0.236065 -0.000000 -0.140616 0.000000 -0.183647 0.000000 ) +( 0.094560 -0.000000 0.044634 -0.000000 0.131343 -0.000000 ) +( -0.094560 0.000000 -0.044634 0.000000 0.131343 0.000000 ) +( -0.094560 0.000000 -0.044634 0.000000 -0.131343 0.000000 ) +( 0.094560 -0.000000 0.044634 -0.000000 -0.131343 -0.000000 ) +( 0.085604 -0.000000 -0.033778 0.000000 -0.029719 0.000000 ) +( -0.085604 0.000000 0.033778 -0.000000 -0.029719 -0.000000 ) +( -0.085604 0.000000 0.033778 -0.000000 0.029719 -0.000000 ) +( 0.085604 -0.000000 -0.033778 0.000000 0.029719 0.000000 ) + freq ( 18) = 30.85248325 [THz] = 1029.12806499 [cm-1] +( 0.009926 -0.000000 0.089095 -0.000000 0.116557 -0.000000 ) +( 0.009926 -0.000000 0.089095 -0.000000 -0.116557 -0.000000 ) +( -0.009926 0.000000 -0.089095 0.000000 -0.116557 0.000000 ) +( -0.009926 0.000000 -0.089095 0.000000 0.116557 0.000000 ) +( -0.054436 0.000000 -0.028723 0.000000 0.162148 0.000000 ) +( -0.054436 0.000000 -0.028723 0.000000 -0.162148 0.000000 ) +( 0.054436 -0.000000 0.028723 -0.000000 -0.162148 -0.000000 ) +( 0.054436 -0.000000 0.028723 -0.000000 0.162148 -0.000000 ) +( -0.092093 0.000000 -0.203071 0.000000 -0.044047 0.000000 ) +( -0.092093 0.000000 -0.203071 0.000000 0.044047 0.000000 ) +( 0.092093 -0.000000 0.203071 -0.000000 0.044047 -0.000000 ) +( 0.092093 -0.000000 0.203071 -0.000000 -0.044047 -0.000000 ) +( -0.237394 0.000000 -0.015357 0.000000 -0.115719 0.000000 ) +( -0.237394 0.000000 -0.015357 0.000000 0.115719 0.000000 ) +( 0.237394 0.000000 0.015357 -0.000000 0.115719 -0.000000 ) +( 0.237394 -0.000000 0.015357 -0.000000 -0.115719 -0.000000 ) +( 0.043502 -0.000000 0.004158 -0.000000 -0.192923 -0.000000 ) +( 0.043502 -0.000000 0.004158 -0.000000 0.192923 -0.000000 ) +( -0.043502 0.000000 -0.004158 0.000000 0.192923 0.000000 ) +( -0.043502 0.000000 -0.004158 0.000000 -0.192923 0.000000 ) +( 0.049083 -0.000000 0.182140 -0.000000 -0.044078 -0.000000 ) +( 0.049083 -0.000000 0.182140 -0.000000 0.044078 -0.000000 ) +( -0.049083 0.000000 -0.182140 0.000000 0.044078 0.000000 ) +( -0.049083 0.000000 -0.182140 0.000000 -0.044078 0.000000 ) + freq ( 19) = 31.12874338 [THz] = 1038.34311094 [cm-1] +( -0.153164 0.000000 0.059547 -0.000000 0.124450 -0.000000 ) +( 0.153164 -0.000000 -0.059547 0.000000 0.124450 0.000000 ) +( -0.153164 0.000000 0.059547 -0.000000 0.124450 -0.000000 ) +( 0.153164 -0.000000 -0.059547 0.000000 0.124450 0.000000 ) +( 0.041746 -0.000000 -0.205461 0.000000 -0.003150 0.000000 ) +( -0.041746 0.000000 0.205461 -0.000000 -0.003150 -0.000000 ) +( 0.041746 -0.000000 -0.205461 0.000000 -0.003150 0.000000 ) +( -0.041746 0.000000 0.205461 -0.000000 -0.003150 -0.000000 ) +( 0.048134 -0.000000 0.189372 -0.000000 0.031466 -0.000000 ) +( -0.048134 0.000000 -0.189372 0.000000 0.031466 0.000000 ) +( 0.048134 -0.000000 0.189372 -0.000000 0.031466 -0.000000 ) +( -0.048134 0.000000 -0.189372 0.000000 0.031466 0.000000 ) +( 0.033987 -0.000000 0.178751 -0.000000 -0.015642 -0.000000 ) +( -0.033987 0.000000 -0.178751 0.000000 -0.015642 0.000000 ) +( 0.033987 -0.000000 0.178751 -0.000000 -0.015642 -0.000000 ) +( -0.033987 0.000000 -0.178751 0.000000 -0.015642 0.000000 ) +( -0.100165 0.000000 -0.212385 0.000000 -0.049879 0.000000 ) +( 0.100165 -0.000000 0.212385 0.000000 -0.049879 0.000000 ) +( -0.100165 0.000000 -0.212385 0.000000 -0.049879 0.000000 ) +( 0.100165 -0.000000 0.212385 -0.000000 -0.049879 -0.000000 ) +( -0.049863 0.000000 0.175800 -0.000000 0.000034 -0.000000 ) +( 0.049863 -0.000000 -0.175800 0.000000 0.000034 0.000000 ) +( -0.049863 0.000000 0.175800 -0.000000 0.000034 -0.000000 ) +( 0.049863 -0.000000 -0.175800 0.000000 0.000034 0.000000 ) + freq ( 20) = 31.51126588 [THz] = 1051.10268834 [cm-1] +( 0.162501 0.000000 0.173746 0.000000 -0.072643 0.000000 ) +( -0.162501 0.000000 -0.173746 0.000000 -0.072643 0.000000 ) +( -0.162501 0.000000 -0.173746 0.000000 0.072643 0.000000 ) +( 0.162501 0.000000 0.173746 0.000000 0.072643 0.000000 ) +( 0.000903 0.000000 -0.237290 0.000000 0.030277 0.000000 ) +( -0.000903 0.000000 0.237290 0.000000 0.030277 0.000000 ) +( -0.000903 0.000000 0.237290 0.000000 -0.030277 0.000000 ) +( 0.000903 0.000000 -0.237290 0.000000 -0.030277 0.000000 ) +( -0.020380 0.000000 0.201085 0.000000 -0.015042 0.000000 ) +( 0.020380 0.000000 -0.201085 0.000000 -0.015042 0.000000 ) +( 0.020380 0.000000 -0.201085 0.000000 0.015042 0.000000 ) +( -0.020380 0.000000 0.201085 0.000000 0.015042 0.000000 ) +( 0.150986 0.000000 0.205869 0.000000 0.060670 0.000000 ) +( -0.150986 0.000000 -0.205869 0.000000 0.060670 0.000000 ) +( -0.150986 0.000000 -0.205869 0.000000 -0.060670 0.000000 ) +( 0.150986 0.000000 0.205869 0.000000 -0.060670 0.000000 ) +( -0.022355 0.000000 -0.057719 0.000000 0.100408 0.000000 ) +( 0.022355 0.000000 0.057719 0.000000 0.100408 0.000000 ) +( 0.022355 0.000000 0.057719 0.000000 -0.100408 0.000000 ) +( -0.022355 0.000000 -0.057719 0.000000 -0.100408 0.000000 ) +( -0.042043 0.000000 -0.017697 0.000000 -0.070533 0.000000 ) +( 0.042043 0.000000 0.017697 0.000000 -0.070533 0.000000 ) +( 0.042043 0.000000 0.017697 0.000000 0.070533 0.000000 ) +( -0.042043 0.000000 -0.017697 0.000000 0.070533 0.000000 ) + freq ( 21) = 31.77510494 [THz] = 1059.90341185 [cm-1] +( -0.001730 0.000000 -0.154482 0.000000 0.037524 0.000000 ) +( -0.001730 0.000000 -0.154482 0.000000 -0.037524 0.000000 ) +( -0.001730 0.000000 -0.154482 0.000000 0.037524 0.000000 ) +( -0.001730 0.000000 -0.154482 0.000000 -0.037524 0.000000 ) +( -0.018972 0.000000 -0.051658 0.000000 0.057703 0.000000 ) +( -0.018972 0.000000 -0.051658 0.000000 -0.057703 0.000000 ) +( -0.018972 0.000000 -0.051658 0.000000 0.057703 0.000000 ) +( -0.018972 0.000000 -0.051658 0.000000 -0.057703 0.000000 ) +( -0.146118 0.000000 0.088324 0.000000 -0.004372 0.000000 ) +( -0.146118 0.000000 0.088324 0.000000 0.004372 0.000000 ) +( -0.146118 0.000000 0.088324 0.000000 -0.004372 0.000000 ) +( -0.146118 0.000000 0.088324 0.000000 0.004372 0.000000 ) +( -0.135395 0.000000 0.313321 0.000000 -0.179642 0.000000 ) +( -0.135395 0.000000 0.313321 0.000000 0.179642 0.000000 ) +( -0.135395 0.000000 0.313321 0.000000 -0.179642 0.000000 ) +( -0.135395 0.000000 0.313321 0.000000 0.179642 0.000000 ) +( -0.059293 0.000000 0.009552 0.000000 -0.097651 0.000000 ) +( -0.059293 0.000000 0.009552 0.000000 0.097651 0.000000 ) +( -0.059293 0.000000 0.009552 0.000000 -0.097651 0.000000 ) +( -0.059293 0.000000 0.009552 0.000000 0.097651 0.000000 ) +( -0.072980 0.000000 -0.142052 0.000000 0.042127 0.000000 ) +( -0.072980 0.000000 -0.142052 0.000000 -0.042127 0.000000 ) +( -0.072980 0.000000 -0.142052 0.000000 0.042127 0.000000 ) +( -0.072980 0.000000 -0.142052 0.000000 -0.042127 0.000000 ) + freq ( 22) = 32.63374921 [THz] = 1088.54470181 [cm-1] +( 0.115630 0.000000 0.115095 0.000000 -0.006780 0.000000 ) +( -0.115630 0.000000 -0.115095 0.000000 -0.006780 0.000000 ) +( -0.115630 0.000000 -0.115095 0.000000 0.006780 0.000000 ) +( 0.115630 0.000000 0.115095 0.000000 0.006780 0.000000 ) +( -0.089625 0.000000 0.164580 0.000000 0.123447 0.000000 ) +( 0.089625 0.000000 -0.164580 0.000000 0.123447 0.000000 ) +( 0.089625 0.000000 -0.164580 0.000000 -0.123447 0.000000 ) +( -0.089625 0.000000 0.164580 0.000000 -0.123447 0.000000 ) +( -0.120081 0.000000 0.104714 0.000000 -0.085116 0.000000 ) +( 0.120081 0.000000 -0.104714 0.000000 -0.085116 0.000000 ) +( 0.120081 0.000000 -0.104714 0.000000 0.085116 0.000000 ) +( -0.120081 0.000000 0.104714 0.000000 0.085116 0.000000 ) +( -0.091548 0.000000 -0.122437 0.000000 -0.050808 0.000000 ) +( 0.091548 0.000000 0.122437 0.000000 -0.050808 0.000000 ) +( 0.091548 0.000000 0.122437 0.000000 0.050808 0.000000 ) +( -0.091548 0.000000 -0.122437 0.000000 0.050808 0.000000 ) +( -0.029413 0.000000 0.071870 0.000000 0.066630 0.000000 ) +( 0.029413 0.000000 -0.071870 0.000000 0.066630 0.000000 ) +( 0.029413 0.000000 -0.071870 0.000000 -0.066630 0.000000 ) +( -0.029413 0.000000 0.071870 0.000000 -0.066630 0.000000 ) +( -0.054401 0.000000 -0.315978 0.000000 -0.033533 0.000000 ) +( 0.054401 0.000000 0.315978 0.000000 -0.033533 0.000000 ) +( 0.054401 0.000000 0.315978 0.000000 0.033533 0.000000 ) +( -0.054401 0.000000 -0.315978 0.000000 0.033533 0.000000 ) + freq ( 23) = 32.73128252 [THz] = 1091.79806292 [cm-1] +( 0.065423 0.000000 0.058563 0.000000 -0.037769 0.000000 ) +( 0.065423 0.000000 0.058563 0.000000 0.037769 0.000000 ) +( -0.065423 0.000000 -0.058563 0.000000 0.037769 0.000000 ) +( -0.065423 0.000000 -0.058563 0.000000 -0.037769 0.000000 ) +( 0.018969 0.000000 -0.346311 0.000000 0.016895 0.000000 ) +( 0.018969 0.000000 -0.346311 0.000000 -0.016895 0.000000 ) +( -0.018969 0.000000 0.346311 0.000000 -0.016895 0.000000 ) +( -0.018969 0.000000 0.346311 0.000000 0.016895 0.000000 ) +( 0.092714 0.000000 0.173027 0.000000 -0.007210 0.000000 ) +( 0.092714 0.000000 0.173027 0.000000 0.007210 0.000000 ) +( -0.092714 0.000000 -0.173027 0.000000 0.007210 0.000000 ) +( -0.092714 0.000000 -0.173027 0.000000 -0.007210 0.000000 ) +( -0.120360 0.000000 0.133147 0.000000 -0.021919 0.000000 ) +( -0.120360 0.000000 0.133147 0.000000 0.021919 0.000000 ) +( 0.120360 0.000000 -0.133147 0.000000 0.021919 0.000000 ) +( 0.120360 0.000000 -0.133147 0.000000 -0.021919 0.000000 ) +( 0.080717 0.000000 0.149577 0.000000 0.029942 0.000000 ) +( 0.080717 0.000000 0.149577 0.000000 -0.029942 0.000000 ) +( -0.080717 0.000000 -0.149577 0.000000 -0.029942 0.000000 ) +( -0.080717 0.000000 -0.149577 0.000000 0.029942 0.000000 ) +( 0.056888 0.000000 0.029868 0.000000 0.122851 0.000000 ) +( 0.056888 0.000000 0.029868 0.000000 -0.122851 0.000000 ) +( -0.056888 0.000000 -0.029868 0.000000 -0.122851 0.000000 ) +( -0.056888 0.000000 -0.029868 0.000000 0.122851 0.000000 ) + freq ( 24) = 32.76808309 [THz] = 1093.02559787 [cm-1] +( 0.042852 -0.000000 -0.163012 0.000000 0.007513 0.000000 ) +( 0.042852 -0.000000 -0.163012 0.000000 -0.007513 0.000000 ) +( 0.042852 -0.000000 -0.163012 0.000000 0.007513 0.000000 ) +( 0.042852 -0.000000 -0.163012 0.000000 -0.007513 0.000000 ) +( -0.061306 0.000000 0.266655 -0.000000 0.095132 -0.000000 ) +( -0.061306 0.000000 0.266655 0.000000 -0.095132 0.000000 ) +( -0.061306 0.000000 0.266655 -0.000000 0.095132 -0.000000 ) +( -0.061306 0.000000 0.266655 -0.000000 -0.095132 -0.000000 ) +( -0.110957 0.000000 -0.245575 0.000000 0.006148 0.000000 ) +( -0.110957 0.000000 -0.245575 0.000000 -0.006148 0.000000 ) +( -0.110957 0.000000 -0.245575 0.000000 0.006148 0.000000 ) +( -0.110957 0.000000 -0.245575 0.000000 -0.006148 0.000000 ) +( -0.079246 0.000000 -0.164044 0.000000 -0.063934 0.000000 ) +( -0.079246 0.000000 -0.164044 0.000000 0.063934 0.000000 ) +( -0.079246 0.000000 -0.164044 0.000000 -0.063934 0.000000 ) +( -0.079246 0.000000 -0.164044 0.000000 0.063934 0.000000 ) +( -0.061582 0.000000 0.116124 -0.000000 -0.025542 -0.000000 ) +( -0.061582 0.000000 0.116124 -0.000000 0.025542 -0.000000 ) +( -0.061582 0.000000 0.116124 -0.000000 -0.025542 -0.000000 ) +( -0.061582 0.000000 0.116124 -0.000000 0.025542 -0.000000 ) +( -0.095185 0.000000 -0.020537 0.000000 -0.016589 0.000000 ) +( -0.095185 0.000000 -0.020537 0.000000 0.016589 0.000000 ) +( -0.095185 0.000000 -0.020537 0.000000 -0.016589 0.000000 ) +( -0.095185 0.000000 -0.020537 0.000000 0.016589 0.000000 ) + freq ( 25) = 33.29375128 [THz] = 1110.56000111 [cm-1] +( 0.014749 -0.000000 -0.113158 0.000000 -0.121567 0.000000 ) +( -0.014749 0.000000 0.113158 -0.000000 -0.121567 -0.000000 ) +( -0.014749 0.000000 0.113158 -0.000000 0.121567 -0.000000 ) +( 0.014749 -0.000000 -0.113158 0.000000 0.121567 0.000000 ) +( 0.131564 -0.000000 0.114728 -0.000000 -0.170221 -0.000000 ) +( -0.131564 0.000000 -0.114728 0.000000 -0.170221 0.000000 ) +( -0.131564 0.000000 -0.114728 0.000000 0.170221 0.000000 ) +( 0.131564 -0.000000 0.114728 -0.000000 0.170221 -0.000000 ) +( -0.131688 0.000000 0.191076 -0.000000 0.040874 -0.000000 ) +( 0.131688 -0.000000 -0.191076 0.000000 0.040874 0.000000 ) +( 0.131688 -0.000000 -0.191076 0.000000 -0.040874 0.000000 ) +( -0.131688 0.000000 0.191076 -0.000000 -0.040874 -0.000000 ) +( -0.048272 0.000000 -0.058705 0.000000 -0.131283 0.000000 ) +( 0.048272 -0.000000 0.058705 -0.000000 -0.131283 -0.000000 ) +( 0.048272 -0.000000 0.058705 -0.000000 0.131283 -0.000000 ) +( -0.048272 0.000000 -0.058705 0.000000 0.131283 0.000000 ) +( 0.007291 -0.000000 -0.019168 0.000000 0.119082 0.000000 ) +( -0.007291 0.000000 0.019168 -0.000000 0.119082 -0.000000 ) +( -0.007291 0.000000 0.019168 -0.000000 -0.119082 -0.000000 ) +( 0.007291 -0.000000 -0.019168 0.000000 -0.119082 0.000000 ) +( -0.020182 0.000000 0.130704 -0.000000 -0.228312 -0.000000 ) +( 0.020182 -0.000000 -0.130704 0.000000 -0.228312 0.000000 ) +( 0.020182 -0.000000 -0.130704 0.000000 0.228312 0.000000 ) +( -0.020182 0.000000 0.130704 -0.000000 0.228312 -0.000000 ) + freq ( 26) = 33.93510948 [THz] = 1131.95340796 [cm-1] +( 0.003084 -0.000000 -0.120952 0.000000 0.047759 0.000000 ) +( -0.003084 0.000000 0.120952 -0.000000 0.047759 -0.000000 ) +( 0.003084 -0.000000 -0.120952 0.000000 0.047759 0.000000 ) +( -0.003084 0.000000 0.120952 -0.000000 0.047759 -0.000000 ) +( 0.037142 -0.000000 0.043059 -0.000000 0.043085 -0.000000 ) +( -0.037142 0.000000 -0.043059 0.000000 0.043085 0.000000 ) +( 0.037142 -0.000000 0.043059 -0.000000 0.043085 -0.000000 ) +( -0.037142 0.000000 -0.043059 0.000000 0.043085 0.000000 ) +( -0.036172 0.000000 0.238121 -0.000000 -0.031356 -0.000000 ) +( 0.036172 -0.000000 -0.238121 0.000000 -0.031356 0.000000 ) +( -0.036172 0.000000 0.238121 -0.000000 -0.031356 -0.000000 ) +( 0.036172 -0.000000 -0.238121 0.000000 -0.031356 0.000000 ) +( -0.095063 0.000000 0.149083 -0.000000 -0.046755 -0.000000 ) +( 0.095063 -0.000000 -0.149083 0.000000 -0.046755 0.000000 ) +( -0.095063 0.000000 0.149083 -0.000000 -0.046755 -0.000000 ) +( 0.095063 -0.000000 -0.149083 0.000000 -0.046755 0.000000 ) +( 0.120383 -0.000000 -0.029840 0.000000 -0.002420 0.000000 ) +( -0.120383 0.000000 0.029840 -0.000000 -0.002420 -0.000000 ) +( 0.120383 -0.000000 -0.029840 0.000000 -0.002420 0.000000 ) +( -0.120383 0.000000 0.029840 -0.000000 -0.002420 -0.000000 ) +( 0.113562 -0.000000 -0.262128 0.000000 -0.196348 0.000000 ) +( -0.113562 0.000000 0.262128 -0.000000 -0.196348 -0.000000 ) +( 0.113562 -0.000000 -0.262128 0.000000 -0.196348 0.000000 ) +( -0.113562 0.000000 0.262128 0.000000 -0.196348 0.000000 ) + freq ( 27) = 35.21355787 [THz] = 1174.59785582 [cm-1] +( -0.043351 0.000000 0.041257 0.000000 -0.043499 0.000000 ) +( -0.043351 0.000000 0.041257 0.000000 0.043499 0.000000 ) +( 0.043351 0.000000 -0.041257 0.000000 0.043499 0.000000 ) +( 0.043351 0.000000 -0.041257 0.000000 -0.043499 0.000000 ) +( -0.070285 0.000000 -0.124259 0.000000 -0.055572 0.000000 ) +( -0.070285 0.000000 -0.124259 0.000000 0.055572 0.000000 ) +( 0.070285 0.000000 0.124259 0.000000 0.055572 0.000000 ) +( 0.070285 0.000000 0.124259 0.000000 -0.055572 0.000000 ) +( 0.009612 0.000000 -0.039139 0.000000 0.068574 0.000000 ) +( 0.009612 0.000000 -0.039139 0.000000 -0.068574 0.000000 ) +( -0.009612 0.000000 0.039139 0.000000 -0.068574 0.000000 ) +( -0.009612 0.000000 0.039139 0.000000 0.068574 0.000000 ) +( 0.131726 0.000000 -0.164146 0.000000 0.011356 0.000000 ) +( 0.131726 0.000000 -0.164146 0.000000 -0.011356 0.000000 ) +( -0.131726 0.000000 0.164146 0.000000 -0.011356 0.000000 ) +( -0.131726 0.000000 0.164146 0.000000 0.011356 0.000000 ) +( -0.003822 0.000000 -0.243683 0.000000 0.042933 0.000000 ) +( -0.003822 0.000000 -0.243683 0.000000 -0.042933 0.000000 ) +( 0.003822 0.000000 0.243683 0.000000 -0.042933 0.000000 ) +( 0.003822 0.000000 0.243683 0.000000 0.042933 0.000000 ) +( 0.088345 0.000000 0.240366 0.000000 0.208535 0.000000 ) +( 0.088345 0.000000 0.240366 0.000000 -0.208535 0.000000 ) +( -0.088345 0.000000 -0.240366 0.000000 -0.208535 0.000000 ) +( -0.088345 0.000000 -0.240366 0.000000 0.208535 0.000000 ) + freq ( 28) = 35.30673124 [THz] = 1177.70578505 [cm-1] +( -0.028422 0.000000 0.151933 -0.000000 0.109390 -0.000000 ) +( 0.028422 -0.000000 -0.151933 0.000000 0.109390 0.000000 ) +( -0.028422 0.000000 0.151933 -0.000000 0.109390 -0.000000 ) +( 0.028422 -0.000000 -0.151933 0.000000 0.109390 0.000000 ) +( -0.004500 0.000000 -0.203188 0.000000 0.111670 0.000000 ) +( 0.004500 -0.000000 0.203188 -0.000000 0.111670 -0.000000 ) +( -0.004500 0.000000 -0.203188 0.000000 0.111670 0.000000 ) +( 0.004500 -0.000000 0.203188 -0.000000 0.111670 -0.000000 ) +( -0.241713 0.000000 0.010533 -0.000000 -0.057285 -0.000000 ) +( 0.241713 0.000000 -0.010533 0.000000 -0.057285 0.000000 ) +( -0.241713 0.000000 0.010533 -0.000000 -0.057285 -0.000000 ) +( 0.241713 -0.000000 -0.010533 0.000000 -0.057285 0.000000 ) +( -0.085057 0.000000 -0.061273 0.000000 -0.093384 0.000000 ) +( 0.085057 -0.000000 0.061273 -0.000000 -0.093384 -0.000000 ) +( -0.085057 0.000000 -0.061273 0.000000 -0.093384 0.000000 ) +( 0.085057 -0.000000 0.061273 -0.000000 -0.093384 -0.000000 ) +( -0.082672 0.000000 0.210562 -0.000000 -0.106202 -0.000000 ) +( 0.082672 -0.000000 -0.210562 0.000000 -0.106202 0.000000 ) +( -0.082672 0.000000 0.210562 -0.000000 -0.106202 -0.000000 ) +( 0.082672 -0.000000 -0.210562 0.000000 -0.106202 0.000000 ) +( -0.081679 0.000000 -0.098558 0.000000 -0.002034 0.000000 ) +( 0.081679 -0.000000 0.098558 -0.000000 -0.002034 -0.000000 ) +( -0.081679 0.000000 -0.098558 0.000000 -0.002034 0.000000 ) +( 0.081679 -0.000000 0.098558 -0.000000 -0.002034 -0.000000 ) + freq ( 29) = 35.39001739 [THz] = 1180.48391200 [cm-1] +( -0.001181 0.000000 -0.050472 0.000000 -0.088773 0.000000 ) +( -0.001181 0.000000 -0.050472 0.000000 0.088773 0.000000 ) +( -0.001181 0.000000 -0.050472 0.000000 -0.088773 0.000000 ) +( -0.001181 0.000000 -0.050472 0.000000 0.088773 0.000000 ) +( -0.007981 0.000000 0.086844 -0.000000 -0.106596 -0.000000 ) +( -0.007981 0.000000 0.086844 -0.000000 0.106596 -0.000000 ) +( -0.007981 0.000000 0.086844 -0.000000 -0.106596 -0.000000 ) +( -0.007981 0.000000 0.086844 -0.000000 0.106596 -0.000000 ) +( 0.136386 -0.000000 -0.062998 0.000000 0.171953 0.000000 ) +( 0.136386 -0.000000 -0.062998 0.000000 -0.171953 0.000000 ) +( 0.136386 -0.000000 -0.062998 0.000000 0.171953 0.000000 ) +( 0.136386 -0.000000 -0.062998 0.000000 -0.171953 0.000000 ) +( 0.196005 -0.000000 0.052573 -0.000000 -0.044245 -0.000000 ) +( 0.196005 -0.000000 0.052573 -0.000000 0.044245 -0.000000 ) +( 0.196005 -0.000000 0.052573 -0.000000 -0.044245 -0.000000 ) +( 0.196005 -0.000000 0.052573 -0.000000 0.044245 -0.000000 ) +( -0.100711 0.000000 -0.074402 0.000000 -0.020342 0.000000 ) +( -0.100711 0.000000 -0.074402 0.000000 0.020342 0.000000 ) +( -0.100711 0.000000 -0.074402 0.000000 -0.020342 0.000000 ) +( -0.100711 0.000000 -0.074402 0.000000 0.020342 0.000000 ) +( -0.049008 0.000000 -0.071224 0.000000 0.318996 0.000000 ) +( -0.049008 0.000000 -0.071224 0.000000 -0.318996 0.000000 ) +( -0.049008 0.000000 -0.071224 0.000000 0.318996 0.000000 ) +( -0.049008 0.000000 -0.071224 0.000000 -0.318996 0.000000 ) + freq ( 30) = 37.17528481 [THz] = 1240.03402319 [cm-1] +( 0.095936 0.000000 0.124381 0.000000 -0.066713 0.000000 ) +( -0.095936 0.000000 -0.124381 0.000000 -0.066713 0.000000 ) +( 0.095936 0.000000 0.124381 0.000000 -0.066713 0.000000 ) +( -0.095936 0.000000 -0.124381 0.000000 -0.066713 0.000000 ) +( -0.146012 0.000000 0.123436 0.000000 0.082978 0.000000 ) +( 0.146012 0.000000 -0.123436 0.000000 0.082978 0.000000 ) +( -0.146012 0.000000 0.123436 0.000000 0.082978 0.000000 ) +( 0.146012 0.000000 -0.123436 0.000000 0.082978 0.000000 ) +( 0.095208 0.000000 0.166253 0.000000 0.051557 0.000000 ) +( -0.095208 0.000000 -0.166253 0.000000 0.051557 0.000000 ) +( 0.095208 0.000000 0.166253 0.000000 0.051557 0.000000 ) +( -0.095208 0.000000 -0.166253 0.000000 0.051557 0.000000 ) +( -0.014288 0.000000 0.109688 0.000000 -0.068722 0.000000 ) +( 0.014288 0.000000 -0.109688 0.000000 -0.068722 0.000000 ) +( -0.014288 0.000000 0.109688 0.000000 -0.068722 0.000000 ) +( 0.014288 0.000000 -0.109688 0.000000 -0.068722 0.000000 ) +( -0.047574 0.000000 0.016440 0.000000 -0.112148 0.000000 ) +( 0.047574 0.000000 -0.016440 0.000000 -0.112148 0.000000 ) +( -0.047574 0.000000 0.016440 0.000000 -0.112148 0.000000 ) +( 0.047574 0.000000 -0.016440 0.000000 -0.112148 0.000000 ) +( -0.010265 0.000000 -0.102201 0.000000 0.308952 0.000000 ) +( 0.010265 0.000000 0.102201 0.000000 0.308952 0.000000 ) +( -0.010265 0.000000 -0.102201 0.000000 0.308952 0.000000 ) +( 0.010265 0.000000 0.102201 0.000000 0.308952 0.000000 ) + freq ( 31) = 38.36955239 [THz] = 1279.87050144 [cm-1] +( 0.051917 0.000000 0.010361 0.000000 0.095928 0.000000 ) +( 0.051917 0.000000 0.010361 0.000000 -0.095928 0.000000 ) +( 0.051917 0.000000 0.010361 0.000000 0.095928 0.000000 ) +( 0.051917 0.000000 0.010361 0.000000 -0.095928 0.000000 ) +( -0.143817 0.000000 -0.019913 0.000000 0.234013 0.000000 ) +( -0.143817 0.000000 -0.019913 0.000000 -0.234013 0.000000 ) +( -0.143817 0.000000 -0.019913 0.000000 0.234013 0.000000 ) +( -0.143817 0.000000 -0.019913 0.000000 -0.234013 0.000000 ) +( -0.034323 0.000000 0.195035 0.000000 -0.051841 0.000000 ) +( -0.034323 0.000000 0.195035 0.000000 0.051841 0.000000 ) +( -0.034323 0.000000 0.195035 0.000000 -0.051841 0.000000 ) +( -0.034323 0.000000 0.195035 0.000000 0.051841 0.000000 ) +( 0.006775 0.000000 -0.081782 0.000000 0.032154 0.000000 ) +( 0.006775 0.000000 -0.081782 0.000000 -0.032154 0.000000 ) +( 0.006775 0.000000 -0.081782 0.000000 0.032154 0.000000 ) +( 0.006775 0.000000 -0.081782 0.000000 -0.032154 0.000000 ) +( -0.034045 0.000000 0.090339 0.000000 -0.039123 0.000000 ) +( -0.034045 0.000000 0.090339 0.000000 0.039123 0.000000 ) +( -0.034045 0.000000 0.090339 0.000000 -0.039123 0.000000 ) +( -0.034045 0.000000 0.090339 0.000000 0.039123 0.000000 ) +( -0.012042 0.000000 0.193930 0.000000 0.252737 0.000000 ) +( -0.012042 0.000000 0.193930 0.000000 -0.252737 0.000000 ) +( -0.012042 0.000000 0.193930 0.000000 0.252737 0.000000 ) +( -0.012042 0.000000 0.193930 0.000000 -0.252737 0.000000 ) + freq ( 32) = 38.81052503 [THz] = 1294.57976532 [cm-1] +( -0.120232 0.000000 0.209439 0.000000 0.003275 0.000000 ) +( -0.120232 0.000000 0.209439 0.000000 -0.003275 0.000000 ) +( 0.120232 0.000000 -0.209439 0.000000 -0.003275 0.000000 ) +( 0.120232 0.000000 -0.209439 0.000000 0.003275 0.000000 ) +( -0.052042 0.000000 0.069013 0.000000 -0.050561 0.000000 ) +( -0.052042 0.000000 0.069013 0.000000 0.050561 0.000000 ) +( 0.052042 0.000000 -0.069013 0.000000 0.050561 0.000000 ) +( 0.052042 0.000000 -0.069013 0.000000 -0.050561 0.000000 ) +( 0.002849 0.000000 0.226329 0.000000 -0.001333 0.000000 ) +( 0.002849 0.000000 0.226329 0.000000 0.001333 0.000000 ) +( -0.002849 0.000000 -0.226329 0.000000 0.001333 0.000000 ) +( -0.002849 0.000000 -0.226329 0.000000 -0.001333 0.000000 ) +( -0.106399 0.000000 -0.122624 0.000000 -0.031365 0.000000 ) +( -0.106399 0.000000 -0.122624 0.000000 0.031365 0.000000 ) +( 0.106399 0.000000 0.122624 0.000000 0.031365 0.000000 ) +( 0.106399 0.000000 0.122624 0.000000 -0.031365 0.000000 ) +( 0.174238 0.000000 -0.092442 0.000000 0.078810 0.000000 ) +( 0.174238 0.000000 -0.092442 0.000000 -0.078810 0.000000 ) +( -0.174238 0.000000 0.092442 0.000000 -0.078810 0.000000 ) +( -0.174238 0.000000 0.092442 0.000000 0.078810 0.000000 ) +( 0.130767 0.000000 -0.013212 0.000000 -0.201682 0.000000 ) +( 0.130767 0.000000 -0.013212 0.000000 0.201682 0.000000 ) +( -0.130767 0.000000 0.013212 0.000000 0.201682 0.000000 ) +( -0.130767 0.000000 0.013212 0.000000 -0.201682 0.000000 ) + freq ( 33) = 41.05382491 [THz] = 1369.40819498 [cm-1] +( -0.092343 0.000000 0.227936 0.000000 0.058074 0.000000 ) +( -0.092343 0.000000 0.227936 0.000000 -0.058074 0.000000 ) +( 0.092343 0.000000 -0.227936 0.000000 -0.058074 0.000000 ) +( 0.092343 0.000000 -0.227936 0.000000 0.058074 0.000000 ) +( 0.102751 0.000000 -0.010629 0.000000 -0.092524 0.000000 ) +( 0.102751 0.000000 -0.010629 0.000000 0.092524 0.000000 ) +( -0.102751 0.000000 0.010629 0.000000 0.092524 0.000000 ) +( -0.102751 0.000000 0.010629 0.000000 -0.092524 0.000000 ) +( -0.031978 0.000000 0.002659 0.000000 -0.081946 0.000000 ) +( -0.031978 0.000000 0.002659 0.000000 0.081946 0.000000 ) +( 0.031978 0.000000 -0.002659 0.000000 0.081946 0.000000 ) +( 0.031978 0.000000 -0.002659 0.000000 -0.081946 0.000000 ) +( 0.192060 0.000000 0.153599 0.000000 0.147356 0.000000 ) +( 0.192060 0.000000 0.153599 0.000000 -0.147356 0.000000 ) +( -0.192060 0.000000 -0.153599 0.000000 -0.147356 0.000000 ) +( -0.192060 0.000000 -0.153599 0.000000 0.147356 0.000000 ) +( -0.074658 0.000000 0.106947 0.000000 -0.082477 0.000000 ) +( -0.074658 0.000000 0.106947 0.000000 0.082477 0.000000 ) +( 0.074658 0.000000 -0.106947 0.000000 0.082477 0.000000 ) +( 0.074658 0.000000 -0.106947 0.000000 -0.082477 0.000000 ) +( -0.030149 0.000000 0.201824 0.000000 -0.107330 0.000000 ) +( -0.030149 0.000000 0.201824 0.000000 0.107330 0.000000 ) +( 0.030149 0.000000 -0.201824 0.000000 0.107330 0.000000 ) +( 0.030149 0.000000 -0.201824 0.000000 -0.107330 0.000000 ) + freq ( 34) = 41.51123541 [THz] = 1384.66576667 [cm-1] +( -0.154039 0.000000 0.127267 -0.000000 0.161713 -0.000000 ) +( 0.154039 -0.000000 -0.127267 0.000000 0.161713 0.000000 ) +( 0.154039 -0.000000 -0.127267 0.000000 -0.161713 0.000000 ) +( -0.154039 0.000000 0.127267 -0.000000 -0.161713 -0.000000 ) +( 0.099292 -0.000000 0.029900 -0.000000 0.012676 -0.000000 ) +( -0.099292 0.000000 -0.029900 0.000000 0.012676 0.000000 ) +( -0.099292 0.000000 -0.029900 0.000000 -0.012676 0.000000 ) +( 0.099292 -0.000000 0.029900 -0.000000 -0.012676 -0.000000 ) +( -0.053655 0.000000 -0.141779 0.000000 -0.100862 0.000000 ) +( 0.053655 -0.000000 0.141779 -0.000000 -0.100862 -0.000000 ) +( 0.053655 -0.000000 0.141779 -0.000000 0.100862 -0.000000 ) +( -0.053655 0.000000 -0.141779 0.000000 0.100862 0.000000 ) +( -0.023202 0.000000 0.008960 -0.000000 0.109098 -0.000000 ) +( 0.023202 -0.000000 -0.008960 0.000000 0.109098 0.000000 ) +( 0.023202 -0.000000 -0.008960 0.000000 -0.109098 0.000000 ) +( -0.023202 0.000000 0.008960 -0.000000 -0.109098 -0.000000 ) +( 0.049181 -0.000000 -0.235422 0.000000 0.188660 0.000000 ) +( -0.049181 0.000000 0.235422 -0.000000 0.188660 -0.000000 ) +( -0.049181 0.000000 0.235422 0.000000 -0.188660 0.000000 ) +( 0.049181 -0.000000 -0.235422 0.000000 -0.188660 0.000000 ) +( 0.049826 -0.000000 -0.043525 0.000000 -0.171825 0.000000 ) +( -0.049826 0.000000 0.043525 -0.000000 -0.171825 -0.000000 ) +( -0.049826 0.000000 0.043525 -0.000000 0.171825 -0.000000 ) +( 0.049826 -0.000000 -0.043525 0.000000 0.171825 0.000000 ) + freq ( 35) = 42.01666037 [THz] = 1401.52492860 [cm-1] +( -0.073892 0.000000 0.145067 0.000000 -0.077470 0.000000 ) +( 0.073892 0.000000 -0.145067 0.000000 -0.077470 0.000000 ) +( -0.073892 0.000000 0.145067 0.000000 -0.077470 0.000000 ) +( 0.073892 0.000000 -0.145067 0.000000 -0.077470 0.000000 ) +( 0.016384 0.000000 0.084320 0.000000 -0.084968 0.000000 ) +( -0.016384 0.000000 -0.084320 0.000000 -0.084968 0.000000 ) +( 0.016384 0.000000 0.084320 0.000000 -0.084968 0.000000 ) +( -0.016384 0.000000 -0.084320 0.000000 -0.084968 0.000000 ) +( -0.062325 0.000000 -0.029424 0.000000 0.093308 0.000000 ) +( 0.062325 0.000000 0.029424 0.000000 0.093308 0.000000 ) +( -0.062325 0.000000 -0.029424 0.000000 0.093308 0.000000 ) +( 0.062325 0.000000 0.029424 0.000000 0.093308 0.000000 ) +( -0.156719 0.000000 0.196587 0.000000 -0.190608 0.000000 ) +( 0.156719 0.000000 -0.196587 0.000000 -0.190608 0.000000 ) +( -0.156719 0.000000 0.196587 0.000000 -0.190608 0.000000 ) +( 0.156719 0.000000 -0.196587 0.000000 -0.190608 0.000000 ) +( 0.052862 0.000000 0.121053 0.000000 0.235550 0.000000 ) +( -0.052862 0.000000 -0.121053 0.000000 0.235550 0.000000 ) +( 0.052862 0.000000 0.121053 0.000000 0.235550 0.000000 ) +( -0.052862 0.000000 -0.121053 0.000000 0.235550 0.000000 ) +( 0.013513 0.000000 0.127002 0.000000 -0.025619 0.000000 ) +( -0.013513 0.000000 -0.127002 0.000000 -0.025619 0.000000 ) +( 0.013513 0.000000 0.127002 0.000000 -0.025619 0.000000 ) +( -0.013513 0.000000 -0.127002 0.000000 -0.025619 0.000000 ) + freq ( 36) = 42.48662368 [THz] = 1417.20121735 [cm-1] +( -0.021644 0.000000 -0.237452 0.000000 0.016025 0.000000 ) +( 0.021644 0.000000 0.237452 0.000000 0.016025 0.000000 ) +( -0.021644 0.000000 -0.237452 0.000000 0.016025 0.000000 ) +( 0.021644 0.000000 0.237452 0.000000 0.016025 0.000000 ) +( -0.140572 0.000000 -0.096117 0.000000 0.053553 0.000000 ) +( 0.140572 0.000000 0.096117 0.000000 0.053553 0.000000 ) +( -0.140572 0.000000 -0.096117 0.000000 0.053553 0.000000 ) +( 0.140572 0.000000 0.096117 0.000000 0.053553 0.000000 ) +( -0.080475 0.000000 -0.172932 0.000000 0.028479 0.000000 ) +( 0.080475 0.000000 0.172932 0.000000 0.028479 0.000000 ) +( -0.080475 0.000000 -0.172932 0.000000 0.028479 0.000000 ) +( 0.080475 0.000000 0.172932 0.000000 0.028479 0.000000 ) +( 0.162879 0.000000 0.285204 0.000000 0.005570 0.000000 ) +( -0.162879 0.000000 -0.285204 0.000000 0.005570 0.000000 ) +( 0.162879 0.000000 0.285204 0.000000 0.005570 0.000000 ) +( -0.162879 0.000000 -0.285204 0.000000 0.005570 0.000000 ) +( -0.005350 0.000000 0.102041 0.000000 -0.003134 0.000000 ) +( 0.005350 0.000000 -0.102041 0.000000 -0.003134 0.000000 ) +( -0.005350 0.000000 0.102041 0.000000 -0.003134 0.000000 ) +( 0.005350 0.000000 -0.102041 0.000000 -0.003134 0.000000 ) +( 0.011729 0.000000 -0.022879 0.000000 0.069410 0.000000 ) +( -0.011729 0.000000 0.022879 0.000000 0.069410 0.000000 ) +( 0.011729 0.000000 -0.022879 0.000000 0.069410 0.000000 ) +( -0.011729 0.000000 0.022879 0.000000 0.069410 0.000000 ) + freq ( 37) = 43.14433089 [THz] = 1439.13996818 [cm-1] +( -0.167342 0.000000 -0.125502 0.000000 0.002363 0.000000 ) +( -0.167342 0.000000 -0.125502 0.000000 -0.002363 0.000000 ) +( 0.167342 -0.000000 0.125502 -0.000000 -0.002363 -0.000000 ) +( 0.167342 -0.000000 0.125502 -0.000000 0.002363 -0.000000 ) +( 0.183784 -0.000000 -0.107112 0.000000 -0.180828 0.000000 ) +( 0.183784 -0.000000 -0.107112 0.000000 0.180828 0.000000 ) +( -0.183784 0.000000 0.107112 -0.000000 0.180828 -0.000000 ) +( -0.183784 0.000000 0.107112 -0.000000 -0.180828 -0.000000 ) +( 0.110618 -0.000000 -0.197250 0.000000 0.126036 0.000000 ) +( 0.110618 -0.000000 -0.197250 0.000000 -0.126036 0.000000 ) +( -0.110618 0.000000 0.197250 -0.000000 -0.126036 -0.000000 ) +( -0.110618 0.000000 0.197250 0.000000 0.126036 0.000000 ) +( -0.080520 0.000000 -0.039449 0.000000 -0.069199 0.000000 ) +( -0.080520 0.000000 -0.039449 0.000000 0.069199 0.000000 ) +( 0.080520 -0.000000 0.039449 -0.000000 0.069199 -0.000000 ) +( 0.080520 -0.000000 0.039449 -0.000000 -0.069199 -0.000000 ) +( 0.023076 -0.000000 0.062695 -0.000000 0.123711 -0.000000 ) +( 0.023076 -0.000000 0.062695 -0.000000 -0.123711 -0.000000 ) +( -0.023076 0.000000 -0.062695 0.000000 -0.123711 0.000000 ) +( -0.023076 0.000000 -0.062695 0.000000 0.123711 0.000000 ) +( 0.034509 -0.000000 0.059633 -0.000000 -0.154662 -0.000000 ) +( 0.034509 -0.000000 0.059633 -0.000000 0.154662 -0.000000 ) +( -0.034509 0.000000 -0.059633 0.000000 0.154662 0.000000 ) +( -0.034509 0.000000 -0.059633 0.000000 -0.154662 0.000000 ) + freq ( 38) = 43.79960228 [THz] = 1460.99746930 [cm-1] +( -0.159191 0.000000 -0.030758 0.000000 0.054238 0.000000 ) +( 0.159191 0.000000 0.030758 0.000000 0.054238 0.000000 ) +( 0.159191 0.000000 0.030758 0.000000 -0.054238 0.000000 ) +( -0.159191 0.000000 -0.030758 0.000000 -0.054238 0.000000 ) +( 0.153956 0.000000 -0.044736 0.000000 -0.169371 0.000000 ) +( -0.153956 0.000000 0.044736 0.000000 -0.169371 0.000000 ) +( -0.153956 0.000000 0.044736 0.000000 0.169371 0.000000 ) +( 0.153956 0.000000 -0.044736 0.000000 0.169371 0.000000 ) +( -0.118933 0.000000 -0.044191 0.000000 0.005060 0.000000 ) +( 0.118933 0.000000 0.044191 0.000000 0.005060 0.000000 ) +( 0.118933 0.000000 0.044191 0.000000 -0.005060 0.000000 ) +( -0.118933 0.000000 -0.044191 0.000000 -0.005060 0.000000 ) +( 0.186033 0.000000 0.014014 0.000000 0.032470 0.000000 ) +( -0.186033 0.000000 -0.014014 0.000000 0.032470 0.000000 ) +( -0.186033 0.000000 -0.014014 0.000000 -0.032470 0.000000 ) +( 0.186033 0.000000 0.014014 0.000000 -0.032470 0.000000 ) +( -0.158107 0.000000 0.180266 0.000000 0.064770 0.000000 ) +( 0.158107 0.000000 -0.180266 0.000000 0.064770 0.000000 ) +( 0.158107 0.000000 -0.180266 0.000000 -0.064770 0.000000 ) +( -0.158107 0.000000 0.180266 0.000000 -0.064770 0.000000 ) +( -0.152609 0.000000 -0.151920 0.000000 0.079624 0.000000 ) +( 0.152609 0.000000 0.151920 0.000000 0.079624 0.000000 ) +( 0.152609 0.000000 0.151920 0.000000 -0.079624 0.000000 ) +( -0.152609 0.000000 -0.151920 0.000000 -0.079624 0.000000 ) + freq ( 39) = 44.19690814 [THz] = 1474.25016603 [cm-1] +( -0.124280 0.000000 -0.152723 0.000000 0.132772 0.000000 ) +( -0.124280 0.000000 -0.152723 0.000000 -0.132772 0.000000 ) +( -0.124280 0.000000 -0.152723 0.000000 0.132772 0.000000 ) +( -0.124280 0.000000 -0.152723 0.000000 -0.132772 0.000000 ) +( 0.163626 -0.000000 0.154280 -0.000000 -0.076080 -0.000000 ) +( 0.163626 -0.000000 0.154280 -0.000000 0.076080 -0.000000 ) +( 0.163626 -0.000000 0.154280 -0.000000 -0.076080 -0.000000 ) +( 0.163626 -0.000000 0.154280 -0.000000 0.076080 -0.000000 ) +( -0.026338 0.000000 0.223321 0.000000 -0.020523 0.000000 ) +( -0.026338 0.000000 0.223321 -0.000000 0.020523 -0.000000 ) +( -0.026338 0.000000 0.223321 -0.000000 -0.020523 -0.000000 ) +( -0.026338 0.000000 0.223321 -0.000000 0.020523 -0.000000 ) +( 0.113344 -0.000000 -0.010175 0.000000 0.076718 0.000000 ) +( 0.113344 -0.000000 -0.010175 0.000000 -0.076718 0.000000 ) +( 0.113344 -0.000000 -0.010175 0.000000 0.076718 0.000000 ) +( 0.113344 -0.000000 -0.010175 0.000000 -0.076718 0.000000 ) +( -0.144117 0.000000 0.001659 -0.000000 0.124082 -0.000000 ) +( -0.144117 0.000000 0.001659 -0.000000 -0.124082 -0.000000 ) +( -0.144117 0.000000 0.001659 -0.000000 0.124082 -0.000000 ) +( -0.144117 0.000000 0.001659 -0.000000 -0.124082 -0.000000 ) +( -0.142678 0.000000 0.054837 -0.000000 -0.088781 -0.000000 ) +( -0.142678 0.000000 0.054837 -0.000000 0.088781 -0.000000 ) +( -0.142678 0.000000 0.054837 -0.000000 -0.088781 -0.000000 ) +( -0.142678 0.000000 0.054837 -0.000000 0.088781 -0.000000 ) + freq ( 40) = 46.13510735 [THz] = 1538.90153271 [cm-1] +( 0.174463 -0.000000 0.090306 -0.000000 -0.093862 -0.000000 ) +( 0.174463 -0.000000 0.090306 -0.000000 0.093862 -0.000000 ) +( 0.174463 -0.000000 0.090306 -0.000000 -0.093862 -0.000000 ) +( 0.174463 -0.000000 0.090306 -0.000000 0.093862 -0.000000 ) +( -0.000024 0.000000 0.219591 -0.000000 0.031067 -0.000000 ) +( -0.000024 0.000000 0.219591 0.000000 -0.031067 0.000000 ) +( -0.000024 0.000000 0.219591 -0.000000 0.031067 -0.000000 ) +( -0.000024 0.000000 0.219591 -0.000000 -0.031067 -0.000000 ) +( 0.023646 -0.000000 0.207213 -0.000000 -0.067502 -0.000000 ) +( 0.023646 -0.000000 0.207213 -0.000000 0.067502 -0.000000 ) +( 0.023646 -0.000000 0.207213 -0.000000 -0.067502 -0.000000 ) +( 0.023646 -0.000000 0.207213 -0.000000 0.067502 -0.000000 ) +( -0.001864 0.000000 -0.057250 0.000000 0.076051 0.000000 ) +( -0.001864 0.000000 -0.057250 0.000000 -0.076051 0.000000 ) +( -0.001864 0.000000 -0.057250 0.000000 0.076051 0.000000 ) +( -0.001864 0.000000 -0.057250 0.000000 -0.076051 0.000000 ) +( 0.047638 -0.000000 -0.108472 0.000000 -0.195825 0.000000 ) +( 0.047638 -0.000000 -0.108472 0.000000 0.195825 0.000000 ) +( 0.047638 -0.000000 -0.108472 0.000000 -0.195825 0.000000 ) +( 0.047638 -0.000000 -0.108472 0.000000 0.195825 0.000000 ) +( -0.013662 0.000000 -0.204677 0.000000 -0.042805 0.000000 ) +( -0.013662 0.000000 -0.204677 0.000000 0.042805 0.000000 ) +( -0.013662 0.000000 -0.204677 0.000000 -0.042805 0.000000 ) +( -0.013662 0.000000 -0.204677 0.000000 0.042805 0.000000 ) + freq ( 41) = 46.80465655 [THz] = 1561.23529000 [cm-1] +( 0.185330 0.000000 0.032923 0.000000 -0.060197 0.000000 ) +( -0.185330 0.000000 -0.032923 0.000000 -0.060197 0.000000 ) +( 0.185330 0.000000 0.032923 0.000000 -0.060197 0.000000 ) +( -0.185330 0.000000 -0.032923 0.000000 -0.060197 0.000000 ) +( -0.132461 0.000000 -0.176574 0.000000 0.172735 0.000000 ) +( 0.132461 0.000000 0.176574 0.000000 0.172735 0.000000 ) +( -0.132461 0.000000 -0.176574 0.000000 0.172735 0.000000 ) +( 0.132461 0.000000 0.176574 0.000000 0.172735 0.000000 ) +( 0.034296 0.000000 -0.016616 0.000000 -0.032144 0.000000 ) +( -0.034296 0.000000 0.016616 0.000000 -0.032144 0.000000 ) +( 0.034296 0.000000 -0.016616 0.000000 -0.032144 0.000000 ) +( -0.034296 0.000000 0.016616 0.000000 -0.032144 0.000000 ) +( -0.101183 0.000000 -0.016959 0.000000 -0.027587 0.000000 ) +( 0.101183 0.000000 0.016959 0.000000 -0.027587 0.000000 ) +( -0.101183 0.000000 -0.016959 0.000000 -0.027587 0.000000 ) +( 0.101183 0.000000 0.016959 0.000000 -0.027587 0.000000 ) +( 0.216987 0.000000 -0.040207 0.000000 -0.044423 0.000000 ) +( -0.216987 0.000000 0.040207 0.000000 -0.044423 0.000000 ) +( 0.216987 0.000000 -0.040207 0.000000 -0.044423 0.000000 ) +( -0.216987 0.000000 0.040207 0.000000 -0.044423 0.000000 ) +( 0.181250 0.000000 0.183598 0.000000 -0.037125 0.000000 ) +( -0.181250 0.000000 -0.183598 0.000000 -0.037125 0.000000 ) +( 0.181250 0.000000 0.183598 0.000000 -0.037125 0.000000 ) +( -0.181250 0.000000 -0.183598 0.000000 -0.037125 0.000000 ) + freq ( 42) = 49.60221699 [THz] = 1654.55186166 [cm-1] +( -0.019198 0.000000 0.038924 0.000000 0.058024 0.000000 ) +( -0.019198 0.000000 0.038924 0.000000 -0.058024 0.000000 ) +( -0.019198 0.000000 0.038924 0.000000 0.058024 0.000000 ) +( -0.019198 0.000000 0.038924 0.000000 -0.058024 0.000000 ) +( -0.137526 0.000000 -0.007726 0.000000 0.186645 0.000000 ) +( -0.137526 0.000000 -0.007726 0.000000 -0.186645 0.000000 ) +( -0.137526 0.000000 -0.007726 0.000000 0.186645 0.000000 ) +( -0.137526 0.000000 -0.007726 0.000000 -0.186645 0.000000 ) +( 0.257928 0.000000 0.056237 0.000000 0.243581 0.000000 ) +( 0.257928 0.000000 0.056237 0.000000 -0.243581 0.000000 ) +( 0.257928 0.000000 0.056237 0.000000 0.243581 0.000000 ) +( 0.257928 0.000000 0.056237 0.000000 -0.243581 0.000000 ) +( -0.011852 0.000000 0.001630 0.000000 -0.093598 0.000000 ) +( -0.011852 0.000000 0.001630 0.000000 0.093598 0.000000 ) +( -0.011852 0.000000 0.001630 0.000000 -0.093598 0.000000 ) +( -0.011852 0.000000 0.001630 0.000000 0.093598 0.000000 ) +( -0.053878 0.000000 0.009642 0.000000 0.042085 0.000000 ) +( -0.053878 0.000000 0.009642 0.000000 -0.042085 0.000000 ) +( -0.053878 0.000000 0.009642 0.000000 0.042085 0.000000 ) +( -0.053878 0.000000 0.009642 0.000000 -0.042085 0.000000 ) +( -0.098882 0.000000 -0.045903 0.000000 -0.190691 0.000000 ) +( -0.098882 0.000000 -0.045903 0.000000 0.190691 0.000000 ) +( -0.098882 0.000000 -0.045903 0.000000 -0.190691 0.000000 ) +( -0.098882 0.000000 -0.045903 0.000000 0.190691 0.000000 ) + freq ( 43) = 49.63172853 [THz] = 1655.53626068 [cm-1] +( 0.057934 -0.000000 -0.258886 0.000000 0.015176 0.000000 ) +( -0.057934 0.000000 0.258886 -0.000000 0.015176 -0.000000 ) +( -0.057934 0.000000 0.258886 -0.000000 -0.015176 -0.000000 ) +( 0.057934 -0.000000 -0.258886 0.000000 -0.015176 0.000000 ) +( 0.039541 -0.000000 0.012819 -0.000000 0.051065 -0.000000 ) +( -0.039541 0.000000 -0.012819 0.000000 0.051065 0.000000 ) +( -0.039541 0.000000 -0.012819 0.000000 -0.051065 0.000000 ) +( 0.039541 -0.000000 0.012819 -0.000000 -0.051065 -0.000000 ) +( -0.023927 0.000000 -0.070584 0.000000 -0.093705 0.000000 ) +( 0.023927 -0.000000 0.070584 -0.000000 -0.093705 -0.000000 ) +( 0.023927 -0.000000 0.070584 -0.000000 0.093705 -0.000000 ) +( -0.023927 0.000000 -0.070584 0.000000 0.093705 0.000000 ) +( -0.070042 0.000000 0.297345 -0.000000 0.029758 -0.000000 ) +( 0.070042 -0.000000 -0.297345 0.000000 0.029758 0.000000 ) +( 0.070042 -0.000000 -0.297345 0.000000 -0.029758 0.000000 ) +( -0.070042 0.000000 0.297345 0.000000 -0.029758 0.000000 ) +( 0.116312 -0.000000 0.137190 -0.000000 0.033880 -0.000000 ) +( -0.116312 0.000000 -0.137190 0.000000 0.033880 0.000000 ) +( -0.116312 0.000000 -0.137190 0.000000 -0.033880 0.000000 ) +( 0.116312 -0.000000 0.137190 -0.000000 -0.033880 -0.000000 ) +( 0.091298 -0.000000 -0.124856 0.000000 -0.095357 0.000000 ) +( -0.091298 0.000000 0.124856 -0.000000 -0.095357 -0.000000 ) +( -0.091298 0.000000 0.124856 -0.000000 0.095357 -0.000000 ) +( 0.091298 -0.000000 -0.124856 0.000000 0.095357 0.000000 ) + freq ( 44) = 50.51897743 [THz] = 1685.13169821 [cm-1] +( -0.060581 0.000000 0.056351 0.000000 0.006704 0.000000 ) +( -0.060581 0.000000 0.056351 0.000000 -0.006704 0.000000 ) +( -0.060581 0.000000 0.056351 0.000000 0.006704 0.000000 ) +( -0.060581 0.000000 0.056351 0.000000 -0.006704 0.000000 ) +( -0.055721 0.000000 0.113949 0.000000 -0.025570 0.000000 ) +( -0.055721 0.000000 0.113949 0.000000 0.025570 0.000000 ) +( -0.055721 0.000000 0.113949 0.000000 -0.025570 0.000000 ) +( -0.055721 0.000000 0.113949 0.000000 0.025570 0.000000 ) +( -0.076890 0.000000 0.121985 0.000000 0.045100 0.000000 ) +( -0.076890 0.000000 0.121985 0.000000 -0.045100 0.000000 ) +( -0.076890 0.000000 0.121985 0.000000 0.045100 0.000000 ) +( -0.076890 0.000000 0.121985 0.000000 -0.045100 0.000000 ) +( -0.089587 0.000000 -0.078438 0.000000 -0.161995 0.000000 ) +( -0.089587 0.000000 -0.078438 0.000000 0.161995 0.000000 ) +( -0.089587 0.000000 -0.078438 0.000000 -0.161995 0.000000 ) +( -0.089587 0.000000 -0.078438 0.000000 0.161995 0.000000 ) +( 0.119955 0.000000 -0.004806 0.000000 0.309689 0.000000 ) +( 0.119955 0.000000 -0.004806 0.000000 -0.309689 0.000000 ) +( 0.119955 0.000000 -0.004806 0.000000 0.309689 0.000000 ) +( 0.119955 0.000000 -0.004806 0.000000 -0.309689 0.000000 ) +( 0.150840 0.000000 -0.144949 0.000000 0.095064 0.000000 ) +( 0.150840 0.000000 -0.144949 0.000000 -0.095064 0.000000 ) +( 0.150840 0.000000 -0.144949 0.000000 0.095064 0.000000 ) +( 0.150840 0.000000 -0.144949 0.000000 -0.095064 0.000000 ) + freq ( 45) = 51.27034823 [THz] = 1710.19473041 [cm-1] +( 0.051022 -0.000000 0.019571 -0.000000 -0.158220 -0.000000 ) +( 0.051022 -0.000000 0.019571 -0.000000 0.158220 -0.000000 ) +( -0.051022 0.000000 -0.019571 0.000000 0.158220 0.000000 ) +( -0.051022 0.000000 -0.019571 0.000000 -0.158220 0.000000 ) +( -0.135843 0.000000 -0.014010 0.000000 0.052920 0.000000 ) +( -0.135843 0.000000 -0.014010 0.000000 -0.052920 0.000000 ) +( 0.135843 -0.000000 0.014010 -0.000000 -0.052920 -0.000000 ) +( 0.135843 -0.000000 0.014010 -0.000000 0.052920 -0.000000 ) +( 0.208506 -0.000000 0.043080 -0.000000 0.249205 -0.000000 ) +( 0.208506 -0.000000 0.043080 -0.000000 -0.249205 -0.000000 ) +( -0.208506 0.000000 -0.043080 0.000000 -0.249205 0.000000 ) +( -0.208506 0.000000 -0.043080 0.000000 0.249205 0.000000 ) +( 0.071436 -0.000000 0.050418 -0.000000 -0.092681 -0.000000 ) +( 0.071436 -0.000000 0.050418 -0.000000 0.092681 -0.000000 ) +( -0.071436 0.000000 -0.050418 0.000000 0.092681 0.000000 ) +( -0.071436 0.000000 -0.050418 0.000000 -0.092681 0.000000 ) +( -0.066250 0.000000 -0.028373 0.000000 -0.188395 0.000000 ) +( -0.066250 0.000000 -0.028373 0.000000 0.188395 0.000000 ) +( 0.066250 -0.000000 0.028373 -0.000000 0.188395 -0.000000 ) +( 0.066250 -0.000000 0.028373 -0.000000 -0.188395 -0.000000 ) +( -0.073885 0.000000 0.047155 -0.000000 -0.168797 -0.000000 ) +( -0.073885 0.000000 0.047155 -0.000000 0.168797 -0.000000 ) +( 0.073885 -0.000000 -0.047155 0.000000 0.168797 0.000000 ) +( 0.073885 -0.000000 -0.047155 0.000000 -0.168797 0.000000 ) + freq ( 46) = 54.28209714 [THz] = 1810.65586007 [cm-1] +( -0.113314 0.000000 -0.023750 0.000000 0.033806 0.000000 ) +( 0.113314 0.000000 0.023750 0.000000 0.033806 0.000000 ) +( 0.113314 0.000000 0.023750 0.000000 -0.033806 0.000000 ) +( -0.113314 0.000000 -0.023750 0.000000 -0.033806 0.000000 ) +( -0.144901 0.000000 0.010075 0.000000 0.109985 0.000000 ) +( 0.144901 0.000000 -0.010075 0.000000 0.109985 0.000000 ) +( 0.144901 0.000000 -0.010075 0.000000 -0.109985 0.000000 ) +( -0.144901 0.000000 0.010075 0.000000 -0.109985 0.000000 ) +( 0.152631 0.000000 -0.021406 0.000000 0.182565 0.000000 ) +( -0.152631 0.000000 0.021406 0.000000 0.182565 0.000000 ) +( -0.152631 0.000000 0.021406 0.000000 -0.182565 0.000000 ) +( 0.152631 0.000000 -0.021406 0.000000 -0.182565 0.000000 ) +( 0.073841 0.000000 0.013511 0.000000 0.005467 0.000000 ) +( -0.073841 0.000000 -0.013511 0.000000 0.005467 0.000000 ) +( -0.073841 0.000000 -0.013511 0.000000 -0.005467 0.000000 ) +( 0.073841 0.000000 0.013511 0.000000 -0.005467 0.000000 ) +( -0.109258 0.000000 0.071476 0.000000 -0.063659 0.000000 ) +( 0.109258 0.000000 -0.071476 0.000000 -0.063659 0.000000 ) +( 0.109258 0.000000 -0.071476 0.000000 0.063659 0.000000 ) +( -0.109258 0.000000 0.071476 0.000000 0.063659 0.000000 ) +( -0.112002 0.000000 -0.036714 0.000000 -0.323293 0.000000 ) +( 0.112002 0.000000 0.036714 0.000000 -0.323293 0.000000 ) +( 0.112002 0.000000 0.036714 0.000000 0.323293 0.000000 ) +( -0.112002 0.000000 -0.036714 0.000000 0.323293 0.000000 ) + freq ( 47) = 54.52725249 [THz] = 1818.83336252 [cm-1] +( 0.050378 0.000000 -0.052977 0.000000 -0.078930 0.000000 ) +( -0.050378 0.000000 0.052977 0.000000 -0.078930 0.000000 ) +( 0.050378 0.000000 -0.052977 0.000000 -0.078930 0.000000 ) +( -0.050378 0.000000 0.052977 0.000000 -0.078930 0.000000 ) +( 0.166929 0.000000 -0.027477 0.000000 -0.197416 0.000000 ) +( -0.166929 0.000000 0.027477 0.000000 -0.197416 0.000000 ) +( 0.166929 0.000000 -0.027477 0.000000 -0.197416 0.000000 ) +( -0.166929 0.000000 0.027477 0.000000 -0.197416 0.000000 ) +( -0.231177 0.000000 0.062648 0.000000 -0.196421 0.000000 ) +( 0.231177 0.000000 -0.062648 0.000000 -0.196421 0.000000 ) +( -0.231177 0.000000 0.062648 0.000000 -0.196421 0.000000 ) +( 0.231177 0.000000 -0.062648 0.000000 -0.196421 0.000000 ) +( -0.000136 0.000000 0.032406 0.000000 0.024921 0.000000 ) +( 0.000136 0.000000 -0.032406 0.000000 0.024921 0.000000 ) +( -0.000136 0.000000 0.032406 0.000000 0.024921 0.000000 ) +( 0.000136 0.000000 -0.032406 0.000000 0.024921 0.000000 ) +( 0.091592 0.000000 -0.051381 0.000000 -0.036438 0.000000 ) +( -0.091592 0.000000 0.051381 0.000000 -0.036438 0.000000 ) +( 0.091592 0.000000 -0.051381 0.000000 -0.036438 0.000000 ) +( -0.091592 0.000000 0.051381 0.000000 -0.036438 0.000000 ) +( 0.100184 0.000000 0.050831 0.000000 0.219624 0.000000 ) +( -0.100184 0.000000 -0.050831 0.000000 0.219624 0.000000 ) +( 0.100184 0.000000 0.050831 0.000000 0.219624 0.000000 ) +( -0.100184 0.000000 -0.050831 0.000000 0.219624 0.000000 ) + freq ( 48) = 55.14169428 [THz] = 1839.32893451 [cm-1] +( 0.140232 0.000000 0.034371 0.000000 -0.237560 0.000000 ) +( 0.140232 0.000000 0.034371 0.000000 0.237560 0.000000 ) +( -0.140232 0.000000 -0.034371 0.000000 0.237560 0.000000 ) +( -0.140232 0.000000 -0.034371 0.000000 -0.237560 0.000000 ) +( 0.162896 0.000000 0.013421 0.000000 -0.224451 0.000000 ) +( 0.162896 0.000000 0.013421 0.000000 0.224451 0.000000 ) +( -0.162896 0.000000 -0.013421 0.000000 0.224451 0.000000 ) +( -0.162896 0.000000 -0.013421 0.000000 -0.224451 0.000000 ) +( -0.083426 0.000000 -0.008656 0.000000 -0.067813 0.000000 ) +( -0.083426 0.000000 -0.008656 0.000000 0.067813 0.000000 ) +( 0.083426 0.000000 0.008656 0.000000 0.067813 0.000000 ) +( 0.083426 0.000000 0.008656 0.000000 -0.067813 0.000000 ) +( -0.044859 0.000000 -0.119052 0.000000 -0.020248 0.000000 ) +( -0.044859 0.000000 -0.119052 0.000000 0.020248 0.000000 ) +( 0.044859 0.000000 0.119052 0.000000 0.020248 0.000000 ) +( 0.044859 0.000000 0.119052 0.000000 -0.020248 0.000000 ) +( 0.049048 0.000000 0.011693 0.000000 -0.243169 0.000000 ) +( 0.049048 0.000000 0.011693 0.000000 0.243169 0.000000 ) +( -0.049048 0.000000 -0.011693 0.000000 0.243169 0.000000 ) +( -0.049048 0.000000 -0.011693 0.000000 -0.243169 0.000000 ) +( 0.049766 0.000000 -0.046362 0.000000 0.033117 0.000000 ) +( 0.049766 0.000000 -0.046362 0.000000 -0.033117 0.000000 ) +( -0.049766 0.000000 0.046362 0.000000 -0.033117 0.000000 ) +( -0.049766 0.000000 0.046362 0.000000 0.033117 0.000000 ) + freq ( 49) = 56.31602196 [THz] = 1878.50028933 [cm-1] +( 0.020085 -0.000000 0.010547 -0.000000 0.127885 -0.000000 ) +( -0.020085 0.000000 -0.010547 0.000000 0.127885 0.000000 ) +( -0.020085 0.000000 -0.010547 0.000000 -0.127885 0.000000 ) +( 0.020085 -0.000000 0.010547 -0.000000 -0.127885 -0.000000 ) +( 0.075025 -0.000000 0.055771 -0.000000 0.048869 -0.000000 ) +( -0.075025 0.000000 -0.055771 0.000000 0.048869 0.000000 ) +( -0.075025 0.000000 -0.055771 0.000000 -0.048869 0.000000 ) +( 0.075025 -0.000000 0.055771 -0.000000 -0.048869 -0.000000 ) +( -0.064489 0.000000 0.137770 -0.000000 -0.223161 -0.000000 ) +( 0.064489 -0.000000 -0.137770 0.000000 -0.223161 0.000000 ) +( 0.064489 -0.000000 -0.137770 0.000000 0.223161 0.000000 ) +( -0.064489 0.000000 0.137770 -0.000000 0.223161 -0.000000 ) +( 0.058367 -0.000000 -0.070576 0.000000 0.220608 0.000000 ) +( -0.058367 0.000000 0.070576 -0.000000 0.220608 -0.000000 ) +( -0.058367 0.000000 0.070576 -0.000000 -0.220608 -0.000000 ) +( 0.058367 -0.000000 -0.070576 0.000000 -0.220608 0.000000 ) +( -0.011419 0.000000 0.106122 -0.000000 -0.231810 -0.000000 ) +( 0.011419 -0.000000 -0.106122 0.000000 -0.231810 0.000000 ) +( 0.011419 -0.000000 -0.106122 0.000000 0.231810 0.000000 ) +( -0.011419 0.000000 0.106122 -0.000000 0.231810 -0.000000 ) +( 0.000056 -0.000000 0.127763 -0.000000 -0.102744 -0.000000 ) +( -0.000056 0.000000 -0.127763 0.000000 -0.102744 0.000000 ) +( -0.000056 0.000000 -0.127763 0.000000 0.102744 0.000000 ) +( 0.000056 -0.000000 0.127763 -0.000000 0.102744 -0.000000 ) + freq ( 50) = 58.29574016 [THz] = 1944.53658035 [cm-1] +( -0.006898 0.000000 0.094633 0.000000 0.169929 0.000000 ) +( 0.006898 0.000000 -0.094633 0.000000 0.169929 0.000000 ) +( -0.006898 0.000000 0.094633 0.000000 0.169929 0.000000 ) +( 0.006898 0.000000 -0.094633 0.000000 0.169929 0.000000 ) +( 0.052995 0.000000 0.219133 0.000000 0.137153 0.000000 ) +( -0.052995 0.000000 -0.219133 0.000000 0.137153 0.000000 ) +( 0.052995 0.000000 0.219133 0.000000 0.137153 0.000000 ) +( -0.052995 0.000000 -0.219133 0.000000 0.137153 0.000000 ) +( -0.003779 0.000000 0.012064 0.000000 -0.175182 0.000000 ) +( 0.003779 0.000000 -0.012064 0.000000 -0.175182 0.000000 ) +( -0.003779 0.000000 0.012064 0.000000 -0.175182 0.000000 ) +( 0.003779 0.000000 -0.012064 0.000000 -0.175182 0.000000 ) +( 0.010808 0.000000 0.131464 0.000000 0.220816 0.000000 ) +( -0.010808 0.000000 -0.131464 0.000000 0.220816 0.000000 ) +( 0.010808 0.000000 0.131464 0.000000 0.220816 0.000000 ) +( -0.010808 0.000000 -0.131464 0.000000 0.220816 0.000000 ) +( 0.025414 0.000000 0.130445 0.000000 -0.051382 0.000000 ) +( -0.025414 0.000000 -0.130445 0.000000 -0.051382 0.000000 ) +( 0.025414 0.000000 0.130445 0.000000 -0.051382 0.000000 ) +( -0.025414 0.000000 -0.130445 0.000000 -0.051382 0.000000 ) +( 0.013482 0.000000 0.152230 0.000000 -0.042629 0.000000 ) +( -0.013482 0.000000 -0.152230 0.000000 -0.042629 0.000000 ) +( 0.013482 0.000000 0.152230 0.000000 -0.042629 0.000000 ) +( -0.013482 0.000000 -0.152230 0.000000 -0.042629 0.000000 ) + freq ( 51) = 59.04907493 [THz] = 1969.66512333 [cm-1] +( 0.003946 -0.000000 -0.076453 0.000000 0.108490 0.000000 ) +( 0.003946 -0.000000 -0.076453 0.000000 -0.108490 0.000000 ) +( -0.003946 0.000000 0.076453 -0.000000 -0.108490 -0.000000 ) +( -0.003946 0.000000 0.076453 -0.000000 0.108490 -0.000000 ) +( 0.107059 -0.000000 -0.197150 0.000000 0.096568 0.000000 ) +( 0.107059 -0.000000 -0.197150 0.000000 -0.096568 0.000000 ) +( -0.107059 0.000000 0.197150 -0.000000 -0.096568 -0.000000 ) +( -0.107059 0.000000 0.197150 -0.000000 0.096568 -0.000000 ) +( 0.070569 -0.000000 0.064633 -0.000000 -0.092700 -0.000000 ) +( 0.070569 -0.000000 0.064633 -0.000000 0.092700 -0.000000 ) +( -0.070569 0.000000 -0.064633 0.000000 0.092700 0.000000 ) +( -0.070569 0.000000 -0.064633 0.000000 -0.092700 0.000000 ) +( -0.024340 0.000000 -0.187326 0.000000 0.201015 0.000000 ) +( -0.024340 0.000000 -0.187326 0.000000 -0.201015 0.000000 ) +( 0.024340 -0.000000 0.187326 -0.000000 -0.201015 -0.000000 ) +( 0.024340 -0.000000 0.187326 -0.000000 0.201015 -0.000000 ) +( -0.048574 0.000000 -0.142934 0.000000 -0.117425 0.000000 ) +( -0.048574 0.000000 -0.142934 0.000000 0.117425 0.000000 ) +( 0.048574 -0.000000 0.142934 -0.000000 0.117425 -0.000000 ) +( 0.048574 -0.000000 0.142934 -0.000000 -0.117425 -0.000000 ) +( -0.140206 0.000000 -0.057196 0.000000 -0.139161 0.000000 ) +( -0.140206 0.000000 -0.057196 0.000000 0.139161 0.000000 ) +( 0.140206 -0.000000 0.057196 -0.000000 0.139161 -0.000000 ) +( 0.140206 -0.000000 0.057196 -0.000000 -0.139161 -0.000000 ) + freq ( 52) = 60.20277639 [THz] = 2008.14846173 [cm-1] +( -0.163774 0.000000 0.026706 0.000000 0.103550 0.000000 ) +( -0.163774 0.000000 0.026706 0.000000 -0.103550 0.000000 ) +( -0.163774 0.000000 0.026706 0.000000 0.103550 0.000000 ) +( -0.163774 0.000000 0.026706 0.000000 -0.103550 0.000000 ) +( -0.247048 0.000000 0.023815 0.000000 0.054060 0.000000 ) +( -0.247048 0.000000 0.023815 0.000000 -0.054060 0.000000 ) +( -0.247048 0.000000 0.023815 0.000000 0.054060 0.000000 ) +( -0.247048 0.000000 0.023815 0.000000 -0.054060 0.000000 ) +( -0.174540 0.000000 -0.052840 0.000000 -0.007674 0.000000 ) +( -0.174540 0.000000 -0.052840 0.000000 0.007674 0.000000 ) +( -0.174540 0.000000 -0.052840 0.000000 -0.007674 0.000000 ) +( -0.174540 0.000000 -0.052840 0.000000 0.007674 0.000000 ) +( 0.247641 0.000000 0.045641 0.000000 0.088701 0.000000 ) +( 0.247641 0.000000 0.045641 0.000000 -0.088701 0.000000 ) +( 0.247641 0.000000 0.045641 0.000000 0.088701 0.000000 ) +( 0.247641 0.000000 0.045641 0.000000 -0.088701 0.000000 ) +( -0.033890 0.000000 -0.093368 0.000000 -0.047736 0.000000 ) +( -0.033890 0.000000 -0.093368 0.000000 0.047736 0.000000 ) +( -0.033890 0.000000 -0.093368 0.000000 -0.047736 0.000000 ) +( -0.033890 0.000000 -0.093368 0.000000 0.047736 0.000000 ) +( 0.119570 0.000000 -0.098612 0.000000 -0.080386 0.000000 ) +( 0.119570 0.000000 -0.098612 0.000000 0.080386 0.000000 ) +( 0.119570 0.000000 -0.098612 0.000000 -0.080386 0.000000 ) +( 0.119570 0.000000 -0.098612 0.000000 0.080386 0.000000 ) + freq ( 53) = 60.82625670 [THz] = 2028.94552636 [cm-1] +( -0.096127 0.000000 -0.154718 0.000000 0.168870 0.000000 ) +( 0.096127 0.000000 0.154718 0.000000 0.168870 0.000000 ) +( 0.096127 0.000000 0.154718 0.000000 -0.168870 0.000000 ) +( -0.096127 0.000000 -0.154718 0.000000 -0.168870 0.000000 ) +( -0.160795 0.000000 -0.060871 0.000000 0.143896 0.000000 ) +( 0.160795 0.000000 0.060871 0.000000 0.143896 0.000000 ) +( 0.160795 0.000000 0.060871 0.000000 -0.143896 0.000000 ) +( -0.160795 0.000000 -0.060871 0.000000 -0.143896 0.000000 ) +( -0.030753 0.000000 0.160880 0.000000 -0.006645 0.000000 ) +( 0.030753 0.000000 -0.160880 0.000000 -0.006645 0.000000 ) +( 0.030753 0.000000 -0.160880 0.000000 0.006645 0.000000 ) +( -0.030753 0.000000 0.160880 0.000000 0.006645 0.000000 ) +( 0.082948 0.000000 -0.097547 0.000000 0.005745 0.000000 ) +( -0.082948 0.000000 0.097547 0.000000 0.005745 0.000000 ) +( -0.082948 0.000000 0.097547 0.000000 -0.005745 0.000000 ) +( 0.082948 0.000000 -0.097547 0.000000 -0.005745 0.000000 ) +( 0.042110 0.000000 0.073728 0.000000 0.257098 0.000000 ) +( -0.042110 0.000000 -0.073728 0.000000 0.257098 0.000000 ) +( -0.042110 0.000000 -0.073728 0.000000 -0.257098 0.000000 ) +( 0.042110 0.000000 0.073728 0.000000 -0.257098 0.000000 ) +( 0.054443 0.000000 0.102868 0.000000 0.088786 0.000000 ) +( -0.054443 0.000000 -0.102868 0.000000 0.088786 0.000000 ) +( -0.054443 0.000000 -0.102868 0.000000 -0.088786 0.000000 ) +( 0.054443 0.000000 0.102868 0.000000 -0.088786 0.000000 ) + freq ( 54) = 61.21843051 [THz] = 2042.02703658 [cm-1] +( -0.098497 0.000000 0.059176 -0.000000 0.166011 -0.000000 ) +( 0.098497 -0.000000 -0.059176 0.000000 0.166011 0.000000 ) +( -0.098497 0.000000 0.059176 -0.000000 0.166011 -0.000000 ) +( 0.098497 -0.000000 -0.059176 0.000000 0.166011 0.000000 ) +( -0.084515 0.000000 -0.018282 0.000000 0.130989 0.000000 ) +( 0.084515 -0.000000 0.018282 -0.000000 0.130989 -0.000000 ) +( -0.084515 0.000000 -0.018282 0.000000 0.130989 0.000000 ) +( 0.084515 -0.000000 0.018282 -0.000000 0.130989 -0.000000 ) +( -0.057840 0.000000 -0.030265 0.000000 -0.066315 0.000000 ) +( 0.057840 -0.000000 0.030265 -0.000000 -0.066315 -0.000000 ) +( -0.057840 0.000000 -0.030265 0.000000 -0.066315 0.000000 ) +( 0.057840 -0.000000 0.030265 -0.000000 -0.066315 -0.000000 ) +( 0.028789 -0.000000 -0.079867 0.000000 0.049893 0.000000 ) +( -0.028789 0.000000 0.079867 -0.000000 0.049893 -0.000000 ) +( 0.028789 -0.000000 -0.079867 0.000000 0.049893 0.000000 ) +( -0.028789 0.000000 0.079867 -0.000000 0.049893 -0.000000 ) +( 0.055245 -0.000000 -0.143717 0.000000 0.314945 0.000000 ) +( -0.055245 0.000000 0.143717 -0.000000 0.314945 -0.000000 ) +( 0.055245 -0.000000 -0.143717 0.000000 0.314945 0.000000 ) +( -0.055245 0.000000 0.143717 -0.000000 0.314945 -0.000000 ) +( 0.078499 -0.000000 -0.112496 0.000000 0.156625 0.000000 ) +( -0.078499 0.000000 0.112496 -0.000000 0.156625 -0.000000 ) +( 0.078499 -0.000000 -0.112496 0.000000 0.156625 0.000000 ) +( -0.078499 0.000000 0.112496 -0.000000 0.156625 -0.000000 ) + freq ( 55) = 63.09021344 [THz] = 2104.46299446 [cm-1] +( 0.004301 -0.000000 0.237251 -0.000000 -0.034735 -0.000000 ) +( -0.004301 0.000000 -0.237251 0.000000 -0.034735 0.000000 ) +( 0.004301 -0.000000 0.237251 -0.000000 -0.034735 -0.000000 ) +( -0.004301 0.000000 -0.237251 0.000000 -0.034735 0.000000 ) +( 0.015649 -0.000000 0.010228 -0.000000 -0.048016 -0.000000 ) +( -0.015649 0.000000 -0.010228 0.000000 -0.048016 0.000000 ) +( 0.015649 -0.000000 0.010228 -0.000000 -0.048016 -0.000000 ) +( -0.015649 0.000000 -0.010228 0.000000 -0.048016 0.000000 ) +( -0.020377 0.000000 -0.262799 0.000000 -0.031774 0.000000 ) +( 0.020377 -0.000000 0.262799 -0.000000 -0.031774 -0.000000 ) +( -0.020377 0.000000 -0.262799 0.000000 -0.031774 0.000000 ) +( 0.020377 -0.000000 0.262799 0.000000 -0.031774 0.000000 ) +( -0.023223 0.000000 0.147696 -0.000000 0.032001 -0.000000 ) +( 0.023223 -0.000000 -0.147696 0.000000 0.032001 0.000000 ) +( -0.023223 0.000000 0.147696 -0.000000 0.032001 -0.000000 ) +( 0.023223 -0.000000 -0.147696 0.000000 0.032001 0.000000 ) +( 0.025506 -0.000000 -0.211667 0.000000 -0.134372 0.000000 ) +( -0.025506 0.000000 0.211667 -0.000000 -0.134372 -0.000000 ) +( 0.025506 -0.000000 -0.211667 0.000000 -0.134372 0.000000 ) +( -0.025506 0.000000 0.211667 -0.000000 -0.134372 -0.000000 ) +( 0.029689 -0.000000 -0.164008 0.000000 -0.068392 0.000000 ) +( -0.029689 0.000000 0.164008 -0.000000 -0.068392 -0.000000 ) +( 0.029689 -0.000000 -0.164008 0.000000 -0.068392 0.000000 ) +( -0.029689 0.000000 0.164008 -0.000000 -0.068392 -0.000000 ) + freq ( 56) = 63.41177648 [THz] = 2115.18918284 [cm-1] +( -0.023392 0.000000 0.215622 -0.000000 0.025590 -0.000000 ) +( 0.023392 -0.000000 -0.215622 0.000000 0.025590 0.000000 ) +( 0.023392 -0.000000 -0.215622 0.000000 -0.025590 0.000000 ) +( -0.023392 0.000000 0.215622 -0.000000 -0.025590 -0.000000 ) +( -0.044027 0.000000 0.279659 -0.000000 0.017815 -0.000000 ) +( 0.044027 -0.000000 -0.279659 0.000000 0.017815 0.000000 ) +( 0.044027 -0.000000 -0.279659 0.000000 -0.017815 0.000000 ) +( -0.044027 0.000000 0.279659 0.000000 -0.017815 0.000000 ) +( -0.001660 0.000000 -0.030506 0.000000 0.018950 0.000000 ) +( 0.001660 -0.000000 0.030506 -0.000000 0.018950 -0.000000 ) +( 0.001660 -0.000000 0.030506 -0.000000 -0.018950 -0.000000 ) +( -0.001660 0.000000 -0.030506 0.000000 -0.018950 0.000000 ) +( 0.028762 -0.000000 0.217601 -0.000000 -0.039518 -0.000000 ) +( -0.028762 0.000000 -0.217601 0.000000 -0.039518 0.000000 ) +( -0.028762 0.000000 -0.217601 0.000000 0.039518 0.000000 ) +( 0.028762 -0.000000 0.217601 -0.000000 0.039518 -0.000000 ) +( -0.017015 0.000000 0.153875 -0.000000 0.092419 -0.000000 ) +( 0.017015 -0.000000 -0.153875 0.000000 0.092419 0.000000 ) +( 0.017015 -0.000000 -0.153875 0.000000 -0.092419 0.000000 ) +( -0.017015 0.000000 0.153875 -0.000000 -0.092419 -0.000000 ) +( -0.012658 0.000000 0.185399 -0.000000 0.061379 -0.000000 ) +( 0.012658 -0.000000 -0.185399 0.000000 0.061379 0.000000 ) +( 0.012658 -0.000000 -0.185399 0.000000 -0.061379 0.000000 ) +( -0.012658 0.000000 0.185399 -0.000000 -0.061379 -0.000000 ) + freq ( 57) = 63.91738221 [THz] = 2132.05437462 [cm-1] +( 0.045467 -0.000000 0.074599 -0.000000 0.201290 -0.000000 ) +( 0.045467 -0.000000 0.074599 -0.000000 -0.201290 -0.000000 ) +( 0.045467 -0.000000 0.074599 -0.000000 0.201290 -0.000000 ) +( 0.045467 -0.000000 0.074599 -0.000000 -0.201290 -0.000000 ) +( 0.086896 -0.000000 -0.024096 0.000000 0.154672 0.000000 ) +( 0.086896 -0.000000 -0.024096 0.000000 -0.154672 0.000000 ) +( 0.086896 -0.000000 -0.024096 0.000000 0.154672 0.000000 ) +( 0.086896 -0.000000 -0.024096 0.000000 -0.154672 0.000000 ) +( 0.064249 -0.000000 -0.146954 0.000000 -0.126808 0.000000 ) +( 0.064249 -0.000000 -0.146954 0.000000 0.126808 0.000000 ) +( 0.064249 -0.000000 -0.146954 0.000000 -0.126808 0.000000 ) +( 0.064249 -0.000000 -0.146954 0.000000 0.126808 0.000000 ) +( -0.062726 0.000000 0.050029 -0.000000 0.145037 -0.000000 ) +( -0.062726 0.000000 0.050029 -0.000000 -0.145037 -0.000000 ) +( -0.062726 0.000000 0.050029 -0.000000 0.145037 -0.000000 ) +( -0.062726 0.000000 0.050029 -0.000000 -0.145037 -0.000000 ) +( -0.012051 0.000000 -0.171124 0.000000 0.149864 0.000000 ) +( -0.012051 0.000000 -0.171124 0.000000 -0.149864 0.000000 ) +( -0.012051 0.000000 -0.171124 0.000000 0.149864 0.000000 ) +( -0.012051 0.000000 -0.171124 0.000000 -0.149864 0.000000 ) +( -0.122345 0.000000 -0.151165 0.000000 0.103976 0.000000 ) +( -0.122345 0.000000 -0.151165 0.000000 -0.103976 0.000000 ) +( -0.122345 0.000000 -0.151165 0.000000 0.103976 0.000000 ) +( -0.122345 0.000000 -0.151165 0.000000 -0.103976 0.000000 ) + freq ( 58) = 63.92822844 [THz] = 2132.41616579 [cm-1] +( -0.144967 0.000000 -0.165449 0.000000 -0.008858 0.000000 ) +( -0.144967 0.000000 -0.165449 0.000000 0.008858 0.000000 ) +( 0.144967 -0.000000 0.165449 -0.000000 0.008858 -0.000000 ) +( 0.144967 -0.000000 0.165449 -0.000000 -0.008858 -0.000000 ) +( -0.200129 0.000000 -0.160591 0.000000 -0.032721 0.000000 ) +( -0.200129 0.000000 -0.160591 0.000000 0.032721 0.000000 ) +( 0.200129 -0.000000 0.160591 -0.000000 0.032721 -0.000000 ) +( 0.200129 0.000000 0.160591 -0.000000 -0.032721 -0.000000 ) +( -0.188481 0.000000 -0.013471 0.000000 -0.036282 0.000000 ) +( -0.188481 0.000000 -0.013471 0.000000 0.036282 0.000000 ) +( 0.188481 -0.000000 0.013471 -0.000000 0.036282 -0.000000 ) +( 0.188481 -0.000000 0.013471 -0.000000 -0.036282 -0.000000 ) +( 0.147399 -0.000000 0.030213 -0.000000 0.006539 -0.000000 ) +( 0.147399 -0.000000 0.030213 -0.000000 -0.006539 -0.000000 ) +( -0.147399 0.000000 -0.030213 0.000000 -0.006539 0.000000 ) +( -0.147399 0.000000 -0.030213 0.000000 0.006539 0.000000 ) +( 0.039015 -0.000000 0.046287 -0.000000 -0.125409 -0.000000 ) +( 0.039015 -0.000000 0.046287 -0.000000 0.125409 -0.000000 ) +( -0.039015 0.000000 -0.046287 0.000000 0.125409 0.000000 ) +( -0.039015 0.000000 -0.046287 0.000000 -0.125409 0.000000 ) +( 0.185543 -0.000000 -0.100397 0.000000 -0.104966 0.000000 ) +( 0.185543 -0.000000 -0.100397 0.000000 0.104966 0.000000 ) +( -0.185543 0.000000 0.100397 -0.000000 0.104966 -0.000000 ) +( -0.185543 0.000000 0.100397 -0.000000 -0.104966 -0.000000 ) + freq ( 59) = 65.98983871 [THz] = 2201.18408234 [cm-1] +( 0.125535 -0.000000 -0.034501 0.000000 0.113687 0.000000 ) +( -0.125535 0.000000 0.034501 -0.000000 0.113687 -0.000000 ) +( -0.125535 0.000000 0.034501 -0.000000 -0.113687 -0.000000 ) +( 0.125535 -0.000000 -0.034501 0.000000 -0.113687 0.000000 ) +( 0.233811 -0.000000 0.008418 -0.000000 0.074478 -0.000000 ) +( -0.233811 0.000000 -0.008418 0.000000 0.074478 0.000000 ) +( -0.233811 0.000000 -0.008418 0.000000 -0.074478 0.000000 ) +( 0.233811 -0.000000 0.008418 -0.000000 -0.074478 -0.000000 ) +( 0.259082 0.000000 0.048401 -0.000000 0.013939 -0.000000 ) +( -0.259082 0.000000 -0.048401 0.000000 0.013939 0.000000 ) +( -0.259082 0.000000 -0.048401 0.000000 -0.013939 0.000000 ) +( 0.259082 -0.000000 0.048401 -0.000000 -0.013939 -0.000000 ) +( -0.170056 0.000000 -0.021012 0.000000 0.043613 0.000000 ) +( 0.170056 -0.000000 0.021012 -0.000000 0.043613 -0.000000 ) +( 0.170056 -0.000000 0.021012 -0.000000 -0.043613 -0.000000 ) +( -0.170056 0.000000 -0.021012 0.000000 -0.043613 0.000000 ) +( -0.085230 0.000000 0.024147 -0.000000 0.122514 -0.000000 ) +( 0.085230 -0.000000 -0.024147 0.000000 0.122514 0.000000 ) +( 0.085230 -0.000000 -0.024147 0.000000 -0.122514 0.000000 ) +( -0.085230 0.000000 0.024147 -0.000000 -0.122514 -0.000000 ) +( -0.181388 0.000000 0.027615 -0.000000 0.048951 -0.000000 ) +( 0.181388 -0.000000 -0.027615 0.000000 0.048951 0.000000 ) +( 0.181388 -0.000000 -0.027615 0.000000 -0.048951 0.000000 ) +( -0.181388 0.000000 0.027615 -0.000000 -0.048951 -0.000000 ) + freq ( 60) = 68.40609608 [THz] = 2281.78175255 [cm-1] +( -0.178479 0.000000 0.074263 -0.000000 -0.072131 -0.000000 ) +( 0.178479 -0.000000 -0.074263 0.000000 -0.072131 0.000000 ) +( -0.178479 0.000000 0.074263 -0.000000 -0.072131 -0.000000 ) +( 0.178479 -0.000000 -0.074263 0.000000 -0.072131 0.000000 ) +( -0.217482 0.000000 0.127661 -0.000000 -0.037866 -0.000000 ) +( 0.217482 0.000000 -0.127661 0.000000 -0.037866 0.000000 ) +( -0.217482 0.000000 0.127661 -0.000000 -0.037866 -0.000000 ) +( 0.217482 -0.000000 -0.127661 0.000000 -0.037866 0.000000 ) +( -0.194826 0.000000 0.085215 -0.000000 0.056005 -0.000000 ) +( 0.194826 -0.000000 -0.085215 0.000000 0.056005 0.000000 ) +( -0.194826 0.000000 0.085215 -0.000000 0.056005 -0.000000 ) +( 0.194826 -0.000000 -0.085215 0.000000 0.056005 0.000000 ) +( 0.196766 -0.000000 -0.091723 0.000000 -0.034562 0.000000 ) +( -0.196766 0.000000 0.091723 -0.000000 -0.034562 -0.000000 ) +( 0.196766 -0.000000 -0.091723 0.000000 -0.034562 0.000000 ) +( -0.196766 0.000000 0.091723 -0.000000 -0.034562 -0.000000 ) +( 0.031030 -0.000000 -0.029862 0.000000 -0.099930 0.000000 ) +( -0.031030 0.000000 0.029862 -0.000000 -0.099930 -0.000000 ) +( 0.031030 -0.000000 -0.029862 0.000000 -0.099930 0.000000 ) +( -0.031030 0.000000 0.029862 -0.000000 -0.099930 -0.000000 ) +( 0.140608 -0.000000 0.067399 -0.000000 -0.097795 -0.000000 ) +( -0.140608 0.000000 -0.067399 0.000000 -0.097795 0.000000 ) +( 0.140608 -0.000000 0.067399 -0.000000 -0.097795 -0.000000 ) +( -0.140608 0.000000 -0.067399 0.000000 -0.097795 0.000000 ) + freq ( 61) = 103.08493805 [THz] = 3438.54340589 [cm-1] +( -0.100605 0.000000 -0.012336 0.000000 -0.146502 0.000000 ) +( 0.100605 -0.000000 0.012336 -0.000000 -0.146502 -0.000000 ) +( -0.100605 0.000000 -0.012336 0.000000 -0.146502 0.000000 ) +( 0.100605 -0.000000 0.012336 -0.000000 -0.146502 -0.000000 ) +( 0.090637 -0.000000 -0.008901 0.000000 0.142250 0.000000 ) +( -0.090637 0.000000 0.008901 -0.000000 0.142250 -0.000000 ) +( 0.090637 -0.000000 -0.008901 0.000000 0.142250 0.000000 ) +( -0.090637 0.000000 0.008901 -0.000000 0.142250 -0.000000 ) +( -0.126984 0.000000 0.029715 -0.000000 0.229013 -0.000000 ) +( 0.126984 -0.000000 -0.029715 0.000000 0.229013 0.000000 ) +( -0.126984 0.000000 0.029715 -0.000000 0.229013 -0.000000 ) +( 0.126984 -0.000000 -0.029715 0.000000 0.229013 0.000000 ) +( -0.061949 0.000000 0.004269 -0.000000 0.212461 -0.000000 ) +( 0.061949 -0.000000 -0.004269 0.000000 0.212461 0.000000 ) +( -0.061949 0.000000 0.004269 -0.000000 0.212461 -0.000000 ) +( 0.061949 -0.000000 -0.004269 0.000000 0.212461 0.000000 ) +( 0.189521 -0.000000 -0.033468 0.000000 -0.021798 0.000000 ) +( -0.189521 0.000000 0.033468 -0.000000 -0.021798 -0.000000 ) +( 0.189521 -0.000000 -0.033468 0.000000 -0.021798 0.000000 ) +( -0.189521 0.000000 0.033468 -0.000000 -0.021798 -0.000000 ) +( -0.175179 0.000000 -0.009164 0.000000 0.054762 0.000000 ) +( 0.175179 -0.000000 0.009164 -0.000000 0.054762 -0.000000 ) +( -0.175179 0.000000 -0.009164 0.000000 0.054762 0.000000 ) +( 0.175179 -0.000000 0.009164 -0.000000 0.054762 -0.000000 ) + freq ( 62) = 103.29414154 [THz] = 3445.52168304 [cm-1] +( -0.211399 0.000000 -0.006364 0.000000 -0.248485 0.000000 ) +( -0.211399 0.000000 -0.006364 0.000000 0.248485 0.000000 ) +( -0.211399 0.000000 -0.006364 0.000000 -0.248485 0.000000 ) +( -0.211399 0.000000 -0.006364 0.000000 0.248485 0.000000 ) +( 0.153730 0.000000 0.000532 0.000000 0.241134 0.000000 ) +( 0.153730 0.000000 0.000532 0.000000 -0.241134 0.000000 ) +( 0.153730 0.000000 0.000532 0.000000 0.241134 0.000000 ) +( 0.153730 0.000000 0.000532 0.000000 -0.241134 0.000000 ) +( -0.100286 0.000000 0.003419 0.000000 0.115853 0.000000 ) +( -0.100286 0.000000 0.003419 0.000000 -0.115853 0.000000 ) +( -0.100286 0.000000 0.003419 0.000000 0.115853 0.000000 ) +( -0.100286 0.000000 0.003419 0.000000 -0.115853 0.000000 ) +( 0.010702 0.000000 0.017511 0.000000 0.112048 0.000000 ) +( 0.010702 0.000000 0.017511 0.000000 -0.112048 0.000000 ) +( 0.010702 0.000000 0.017511 0.000000 0.112048 0.000000 ) +( 0.010702 0.000000 0.017511 0.000000 -0.112048 0.000000 ) +( 0.137696 0.000000 -0.015736 0.000000 0.005207 0.000000 ) +( 0.137696 0.000000 -0.015736 0.000000 -0.005207 0.000000 ) +( 0.137696 0.000000 -0.015736 0.000000 0.005207 0.000000 ) +( 0.137696 0.000000 -0.015736 0.000000 -0.005207 0.000000 ) +( -0.072189 0.000000 -0.007212 0.000000 0.027954 0.000000 ) +( -0.072189 0.000000 -0.007212 0.000000 -0.027954 0.000000 ) +( -0.072189 0.000000 -0.007212 0.000000 0.027954 0.000000 ) +( -0.072189 0.000000 -0.007212 0.000000 -0.027954 0.000000 ) + freq ( 63) = 104.18820150 [THz] = 3475.34431315 [cm-1] +( 0.119393 0.000000 0.005223 0.000000 0.206268 0.000000 ) +( -0.119393 0.000000 -0.005223 0.000000 0.206268 0.000000 ) +( -0.119393 0.000000 -0.005223 0.000000 -0.206268 0.000000 ) +( 0.119393 0.000000 0.005223 0.000000 -0.206268 0.000000 ) +( -0.117403 0.000000 -0.022722 0.000000 -0.212742 0.000000 ) +( 0.117403 0.000000 0.022722 0.000000 -0.212742 0.000000 ) +( 0.117403 0.000000 0.022722 0.000000 0.212742 0.000000 ) +( -0.117403 0.000000 -0.022722 0.000000 0.212742 0.000000 ) +( 0.145091 0.000000 -0.028228 0.000000 -0.204609 0.000000 ) +( -0.145091 0.000000 0.028228 0.000000 -0.204609 0.000000 ) +( -0.145091 0.000000 0.028228 0.000000 0.204609 0.000000 ) +( 0.145091 0.000000 -0.028228 0.000000 0.204609 0.000000 ) +( 0.076643 0.000000 -0.000891 0.000000 -0.235937 0.000000 ) +( -0.076643 0.000000 0.000891 0.000000 -0.235937 0.000000 ) +( -0.076643 0.000000 0.000891 0.000000 0.235937 0.000000 ) +( 0.076643 0.000000 -0.000891 0.000000 0.235937 0.000000 ) +( -0.057912 0.000000 -0.006577 0.000000 -0.006906 0.000000 ) +( 0.057912 0.000000 0.006577 0.000000 -0.006906 0.000000 ) +( 0.057912 0.000000 0.006577 0.000000 0.006906 0.000000 ) +( -0.057912 0.000000 -0.006577 0.000000 0.006906 0.000000 ) +( 0.029955 0.000000 -0.009856 0.000000 -0.062603 0.000000 ) +( -0.029955 0.000000 0.009856 0.000000 -0.062603 0.000000 ) +( -0.029955 0.000000 0.009856 0.000000 0.062603 0.000000 ) +( 0.029955 0.000000 -0.009856 0.000000 0.062603 0.000000 ) + freq ( 64) = 104.84303169 [THz] = 3497.18709734 [cm-1] +( 0.178229 0.000000 -0.000997 0.000000 0.221509 0.000000 ) +( 0.178229 0.000000 -0.000997 0.000000 -0.221509 0.000000 ) +( -0.178229 0.000000 0.000997 0.000000 -0.221509 0.000000 ) +( -0.178229 0.000000 0.000997 0.000000 0.221509 0.000000 ) +( -0.119959 0.000000 -0.014186 0.000000 -0.218400 0.000000 ) +( -0.119959 0.000000 -0.014186 0.000000 0.218400 0.000000 ) +( 0.119959 0.000000 0.014186 0.000000 0.218400 0.000000 ) +( 0.119959 0.000000 0.014186 0.000000 -0.218400 0.000000 ) +( 0.150397 0.000000 0.013734 0.000000 -0.147571 0.000000 ) +( 0.150397 0.000000 0.013734 0.000000 0.147571 0.000000 ) +( -0.150397 0.000000 -0.013734 0.000000 0.147571 0.000000 ) +( -0.150397 0.000000 -0.013734 0.000000 -0.147571 0.000000 ) +( 0.014109 0.000000 -0.026600 0.000000 -0.143160 0.000000 ) +( 0.014109 0.000000 -0.026600 0.000000 0.143160 0.000000 ) +( -0.014109 0.000000 0.026600 0.000000 0.143160 0.000000 ) +( -0.014109 0.000000 0.026600 0.000000 -0.143160 0.000000 ) +( -0.169774 0.000000 -0.017268 0.000000 -0.001892 0.000000 ) +( -0.169774 0.000000 -0.017268 0.000000 0.001892 0.000000 ) +( 0.169774 0.000000 0.017268 0.000000 0.001892 0.000000 ) +( 0.169774 0.000000 0.017268 0.000000 -0.001892 0.000000 ) +( 0.095319 0.000000 -0.012668 0.000000 -0.050194 0.000000 ) +( 0.095319 0.000000 -0.012668 0.000000 0.050194 0.000000 ) +( -0.095319 0.000000 0.012668 0.000000 0.050194 0.000000 ) +( -0.095319 0.000000 0.012668 0.000000 -0.050194 0.000000 ) + freq ( 65) = 107.61946957 [THz] = 3589.79909602 [cm-1] +( -0.057165 0.000000 -0.018443 0.000000 -0.172966 0.000000 ) +( 0.057165 0.000000 0.018443 0.000000 -0.172966 0.000000 ) +( -0.057165 0.000000 -0.018443 0.000000 -0.172966 0.000000 ) +( 0.057165 0.000000 0.018443 0.000000 -0.172966 0.000000 ) +( 0.130553 0.000000 -0.017270 0.000000 0.157897 0.000000 ) +( -0.130553 0.000000 0.017270 0.000000 0.157897 0.000000 ) +( 0.130553 0.000000 -0.017270 0.000000 0.157897 0.000000 ) +( -0.130553 0.000000 0.017270 0.000000 0.157897 0.000000 ) +( -0.021117 0.000000 -0.017505 0.000000 0.054137 0.000000 ) +( 0.021117 0.000000 0.017505 0.000000 0.054137 0.000000 ) +( -0.021117 0.000000 -0.017505 0.000000 0.054137 0.000000 ) +( 0.021117 0.000000 0.017505 0.000000 0.054137 0.000000 ) +( -0.064829 0.000000 0.009477 0.000000 0.087556 0.000000 ) +( 0.064829 0.000000 -0.009477 0.000000 0.087556 0.000000 ) +( -0.064829 0.000000 0.009477 0.000000 0.087556 0.000000 ) +( 0.064829 0.000000 -0.009477 0.000000 0.087556 0.000000 ) +( -0.283790 0.000000 0.011885 0.000000 0.026247 0.000000 ) +( 0.283790 0.000000 -0.011885 0.000000 0.026247 0.000000 ) +( -0.283790 0.000000 0.011885 0.000000 0.026247 0.000000 ) +( 0.283790 0.000000 -0.011885 0.000000 0.026247 0.000000 ) +( 0.277707 0.000000 -0.004956 0.000000 0.006807 0.000000 ) +( -0.277707 0.000000 0.004956 0.000000 0.006807 0.000000 ) +( 0.277707 0.000000 -0.004956 0.000000 0.006807 0.000000 ) +( -0.277707 0.000000 0.004956 0.000000 0.006807 0.000000 ) + freq ( 66) = 108.61450361 [THz] = 3622.98985884 [cm-1] +( 0.090277 0.000000 0.001557 0.000000 0.026080 0.000000 ) +( 0.090277 0.000000 0.001557 0.000000 -0.026080 0.000000 ) +( 0.090277 0.000000 0.001557 0.000000 0.026080 0.000000 ) +( 0.090277 0.000000 0.001557 0.000000 -0.026080 0.000000 ) +( -0.004423 0.000000 -0.002846 0.000000 -0.051984 0.000000 ) +( -0.004423 0.000000 -0.002846 0.000000 0.051984 0.000000 ) +( -0.004423 0.000000 -0.002846 0.000000 -0.051984 0.000000 ) +( -0.004423 0.000000 -0.002846 0.000000 0.051984 0.000000 ) +( -0.114652 0.000000 0.016464 0.000000 0.271090 0.000000 ) +( -0.114652 0.000000 0.016464 0.000000 -0.271090 0.000000 ) +( -0.114652 0.000000 0.016464 0.000000 0.271090 0.000000 ) +( -0.114652 0.000000 0.016464 0.000000 -0.271090 0.000000 ) +( -0.192497 0.000000 0.021207 0.000000 0.261433 0.000000 ) +( -0.192497 0.000000 0.021207 0.000000 -0.261433 0.000000 ) +( -0.192497 0.000000 0.021207 0.000000 0.261433 0.000000 ) +( -0.192497 0.000000 0.021207 0.000000 -0.261433 0.000000 ) +( -0.166437 0.000000 -0.007203 0.000000 0.018946 0.000000 ) +( -0.166437 0.000000 -0.007203 0.000000 -0.018946 0.000000 ) +( -0.166437 0.000000 -0.007203 0.000000 0.018946 0.000000 ) +( -0.166437 0.000000 -0.007203 0.000000 -0.018946 0.000000 ) +( 0.131674 0.000000 -0.003221 0.000000 0.014810 0.000000 ) +( 0.131674 0.000000 -0.003221 0.000000 -0.014810 0.000000 ) +( 0.131674 0.000000 -0.003221 0.000000 0.014810 0.000000 ) +( 0.131674 0.000000 -0.003221 0.000000 -0.014810 0.000000 ) + freq ( 67) = 109.89896644 [THz] = 3665.83492706 [cm-1] +( 0.002897 -0.000000 -0.000449 0.000000 -0.050551 0.000000 ) +( -0.002897 0.000000 0.000449 -0.000000 -0.050551 -0.000000 ) +( -0.002897 0.000000 0.000449 -0.000000 0.050551 -0.000000 ) +( 0.002897 -0.000000 -0.000449 0.000000 0.050551 0.000000 ) +( 0.050942 -0.000000 -0.007764 0.000000 0.042731 0.000000 ) +( -0.050942 0.000000 0.007764 -0.000000 0.042731 -0.000000 ) +( -0.050942 0.000000 0.007764 -0.000000 -0.042731 -0.000000 ) +( 0.050942 -0.000000 -0.007764 0.000000 -0.042731 0.000000 ) +( 0.020636 -0.000000 0.008821 -0.000000 -0.000491 -0.000000 ) +( -0.020636 0.000000 -0.008821 0.000000 -0.000491 0.000000 ) +( -0.020636 0.000000 -0.008821 0.000000 0.000491 0.000000 ) +( 0.020636 -0.000000 0.008821 -0.000000 0.000491 -0.000000 ) +( -0.046505 0.000000 -0.001784 0.000000 0.022279 0.000000 ) +( 0.046505 -0.000000 0.001784 -0.000000 0.022279 -0.000000 ) +( 0.046505 -0.000000 0.001784 -0.000000 -0.022279 -0.000000 ) +( -0.046505 0.000000 -0.001784 0.000000 -0.022279 0.000000 ) +( -0.359839 0.000000 0.023947 -0.000000 0.037960 -0.000000 ) +( 0.359839 -0.000000 -0.023947 0.000000 0.037960 0.000000 ) +( 0.359839 0.000000 -0.023947 0.000000 -0.037960 0.000000 ) +( -0.359839 0.000000 0.023947 -0.000000 -0.037960 -0.000000 ) +( 0.328898 -0.000000 -0.002589 0.000000 -0.010465 0.000000 ) +( -0.328898 0.000000 0.002589 -0.000000 -0.010465 -0.000000 ) +( -0.328898 0.000000 0.002589 -0.000000 0.010465 -0.000000 ) +( 0.328898 -0.000000 -0.002589 0.000000 0.010465 0.000000 ) + freq ( 68) = 112.09573785 [THz] = 3739.11133392 [cm-1] +( -0.099914 0.000000 -0.013497 0.000000 -0.070160 0.000000 ) +( -0.099914 0.000000 -0.013497 0.000000 0.070160 0.000000 ) +( 0.099914 0.000000 0.013497 0.000000 0.070160 0.000000 ) +( 0.099914 0.000000 0.013497 0.000000 -0.070160 0.000000 ) +( 0.037365 0.000000 -0.017981 0.000000 0.081270 0.000000 ) +( 0.037365 0.000000 -0.017981 0.000000 -0.081270 0.000000 ) +( -0.037365 0.000000 0.017981 0.000000 -0.081270 0.000000 ) +( -0.037365 0.000000 0.017981 0.000000 0.081270 0.000000 ) +( 0.123142 0.000000 -0.025373 0.000000 -0.263347 0.000000 ) +( 0.123142 0.000000 -0.025373 0.000000 0.263347 0.000000 ) +( -0.123142 0.000000 0.025373 0.000000 0.263347 0.000000 ) +( -0.123142 0.000000 0.025373 0.000000 -0.263347 0.000000 ) +( 0.167661 0.000000 -0.014889 0.000000 -0.257413 0.000000 ) +( 0.167661 0.000000 -0.014889 0.000000 0.257413 0.000000 ) +( -0.167661 0.000000 0.014889 0.000000 0.257413 0.000000 ) +( -0.167661 0.000000 0.014889 0.000000 -0.257413 0.000000 ) +( 0.167108 0.000000 -0.013592 0.000000 -0.007823 0.000000 ) +( 0.167108 0.000000 -0.013592 0.000000 0.007823 0.000000 ) +( -0.167108 0.000000 0.013592 0.000000 0.007823 0.000000 ) +( -0.167108 0.000000 0.013592 0.000000 -0.007823 0.000000 ) +( -0.136443 0.000000 0.006433 0.000000 0.002533 0.000000 ) +( -0.136443 0.000000 0.006433 0.000000 -0.002533 0.000000 ) +( 0.136443 0.000000 -0.006433 0.000000 -0.002533 0.000000 ) +( 0.136443 0.000000 -0.006433 0.000000 0.002533 0.000000 ) + freq ( 69) = 113.72860354 [THz] = 3793.57787036 [cm-1] +( 0.158306 -0.000000 0.003350 -0.000000 0.186512 -0.000000 ) +( -0.158306 0.000000 -0.003350 0.000000 0.186512 0.000000 ) +( 0.158306 -0.000000 0.003350 -0.000000 0.186512 -0.000000 ) +( -0.158306 0.000000 -0.003350 0.000000 0.186512 0.000000 ) +( -0.126072 0.000000 -0.012373 0.000000 -0.200403 0.000000 ) +( 0.126072 -0.000000 0.012373 -0.000000 -0.200403 -0.000000 ) +( -0.126072 0.000000 -0.012373 0.000000 -0.200403 0.000000 ) +( 0.126072 -0.000000 0.012373 -0.000000 -0.200403 -0.000000 ) +( -0.098704 0.000000 0.020781 -0.000000 0.221040 -0.000000 ) +( 0.098704 -0.000000 -0.020781 0.000000 0.221040 0.000000 ) +( -0.098704 0.000000 0.020781 -0.000000 0.221040 -0.000000 ) +( 0.098704 -0.000000 -0.020781 0.000000 0.221040 0.000000 ) +( -0.140061 0.000000 0.007416 -0.000000 0.199929 -0.000000 ) +( 0.140061 -0.000000 -0.007416 0.000000 0.199929 0.000000 ) +( -0.140061 0.000000 0.007416 -0.000000 0.199929 -0.000000 ) +( 0.140061 -0.000000 -0.007416 0.000000 0.199929 0.000000 ) +( -0.081190 0.000000 0.005041 -0.000000 0.007827 -0.000000 ) +( 0.081190 -0.000000 -0.005041 0.000000 0.007827 0.000000 ) +( -0.081190 0.000000 0.005041 -0.000000 0.007827 -0.000000 ) +( 0.081190 -0.000000 -0.005041 0.000000 0.007827 0.000000 ) +( 0.092301 -0.000000 0.007274 -0.000000 0.002207 -0.000000 ) +( -0.092301 0.000000 -0.007274 0.000000 0.002207 0.000000 ) +( 0.092301 -0.000000 0.007274 -0.000000 0.002207 -0.000000 ) +( -0.092301 0.000000 -0.007274 0.000000 0.002207 0.000000 ) + freq ( 70) = 117.36226097 [THz] = 3914.78363559 [cm-1] +( 0.152808 -0.000000 0.004267 -0.000000 0.198026 -0.000000 ) +( -0.152808 0.000000 -0.004267 0.000000 0.198026 0.000000 ) +( -0.152808 0.000000 -0.004267 0.000000 -0.198026 0.000000 ) +( 0.152808 -0.000000 0.004267 -0.000000 -0.198026 -0.000000 ) +( -0.124799 0.000000 0.002200 -0.000000 -0.214225 -0.000000 ) +( 0.124799 -0.000000 -0.002200 0.000000 -0.214225 0.000000 ) +( 0.124799 -0.000000 -0.002200 0.000000 0.214225 0.000000 ) +( -0.124799 0.000000 0.002200 -0.000000 0.214225 -0.000000 ) +( -0.106305 0.000000 0.011827 -0.000000 0.230648 -0.000000 ) +( 0.106305 -0.000000 -0.011827 0.000000 0.230648 0.000000 ) +( 0.106305 -0.000000 -0.011827 0.000000 -0.230648 0.000000 ) +( -0.106305 0.000000 0.011827 -0.000000 -0.230648 -0.000000 ) +( -0.134903 0.000000 0.018669 -0.000000 0.203065 -0.000000 ) +( 0.134903 -0.000000 -0.018669 0.000000 0.203065 0.000000 ) +( 0.134903 -0.000000 -0.018669 0.000000 -0.203065 0.000000 ) +( -0.134903 0.000000 0.018669 -0.000000 -0.203065 -0.000000 ) +( -0.016369 0.000000 0.008751 -0.000000 0.002902 -0.000000 ) +( 0.016369 -0.000000 -0.008751 0.000000 0.002902 0.000000 ) +( 0.016369 -0.000000 -0.008751 0.000000 -0.002902 0.000000 ) +( -0.016369 0.000000 0.008751 -0.000000 -0.002902 -0.000000 ) +( 0.031296 -0.000000 -0.013827 0.000000 0.000261 0.000000 ) +( -0.031296 0.000000 0.013827 -0.000000 0.000261 -0.000000 ) +( -0.031296 0.000000 0.013827 -0.000000 -0.000261 -0.000000 ) +( 0.031296 -0.000000 -0.013827 0.000000 -0.000261 0.000000 ) + freq ( 71) = 117.80103679 [THz] = 3929.41962143 [cm-1] +( 0.037769 0.000000 0.004160 0.000000 0.108868 0.000000 ) +( 0.037769 0.000000 0.004160 0.000000 -0.108868 0.000000 ) +( 0.037769 0.000000 0.004160 0.000000 0.108868 0.000000 ) +( 0.037769 0.000000 0.004160 0.000000 -0.108868 0.000000 ) +( -0.127500 0.000000 -0.015699 0.000000 -0.162292 0.000000 ) +( -0.127500 0.000000 -0.015699 0.000000 0.162292 0.000000 ) +( -0.127500 0.000000 -0.015699 0.000000 -0.162292 0.000000 ) +( -0.127500 0.000000 -0.015699 0.000000 0.162292 0.000000 ) +( -0.092737 0.000000 0.016168 0.000000 0.133354 0.000000 ) +( -0.092737 0.000000 0.016168 0.000000 -0.133354 0.000000 ) +( -0.092737 0.000000 0.016168 0.000000 0.133354 0.000000 ) +( -0.092737 0.000000 0.016168 0.000000 -0.133354 0.000000 ) +( -0.009989 0.000000 0.000780 0.000000 0.077688 0.000000 ) +( -0.009989 0.000000 0.000780 0.000000 -0.077688 0.000000 ) +( -0.009989 0.000000 0.000780 0.000000 0.077688 0.000000 ) +( -0.009989 0.000000 0.000780 0.000000 -0.077688 0.000000 ) +( 0.294758 0.000000 0.002375 0.000000 -0.014274 0.000000 ) +( 0.294758 0.000000 0.002375 0.000000 0.014274 0.000000 ) +( 0.294758 0.000000 0.002375 0.000000 -0.014274 0.000000 ) +( 0.294758 0.000000 0.002375 0.000000 0.014274 0.000000 ) +( -0.269661 0.000000 0.027237 0.000000 0.023046 0.000000 ) +( -0.269661 0.000000 0.027237 0.000000 -0.023046 0.000000 ) +( -0.269661 0.000000 0.027237 0.000000 0.023046 0.000000 ) +( -0.269661 0.000000 0.027237 0.000000 -0.023046 0.000000 ) + freq ( 72) = 119.15567532 [THz] = 3974.60549896 [cm-1] +( 0.075122 0.000000 -0.014285 0.000000 0.144483 0.000000 ) +( 0.075122 0.000000 -0.014285 0.000000 -0.144483 0.000000 ) +( -0.075122 0.000000 0.014285 0.000000 -0.144483 0.000000 ) +( -0.075122 0.000000 0.014285 0.000000 0.144483 0.000000 ) +( -0.136376 0.000000 -0.023312 0.000000 -0.196866 0.000000 ) +( -0.136376 0.000000 -0.023312 0.000000 0.196866 0.000000 ) +( 0.136376 0.000000 0.023312 0.000000 0.196866 0.000000 ) +( 0.136376 0.000000 0.023312 0.000000 -0.196866 0.000000 ) +( -0.073221 0.000000 -0.021462 0.000000 0.099258 0.000000 ) +( -0.073221 0.000000 -0.021462 0.000000 -0.099258 0.000000 ) +( 0.073221 0.000000 0.021462 0.000000 -0.099258 0.000000 ) +( 0.073221 0.000000 0.021462 0.000000 0.099258 0.000000 ) +( 0.005974 0.000000 0.016466 0.000000 0.040380 0.000000 ) +( 0.005974 0.000000 0.016466 0.000000 -0.040380 0.000000 ) +( -0.005974 0.000000 -0.016466 0.000000 -0.040380 0.000000 ) +( -0.005974 0.000000 -0.016466 0.000000 0.040380 0.000000 ) +( 0.271228 0.000000 0.008036 0.000000 -0.026986 0.000000 ) +( 0.271228 0.000000 0.008036 0.000000 0.026986 0.000000 ) +( -0.271228 0.000000 -0.008036 0.000000 0.026986 0.000000 ) +( -0.271228 0.000000 -0.008036 0.000000 -0.026986 0.000000 ) +( -0.269401 0.000000 0.022549 0.000000 0.018017 0.000000 ) +( -0.269401 0.000000 0.022549 0.000000 -0.018017 0.000000 ) +( 0.269401 0.000000 -0.022549 0.000000 -0.018017 0.000000 ) +( 0.269401 0.000000 -0.022549 0.000000 0.018017 0.000000 ) +*************************************************************************** diff --git a/tests/aiida_ensemble/test_aiida_ensemble.py b/tests/aiida_ensemble/test_aiida_ensemble.py index 6773e152..cc904ef4 100644 --- a/tests/aiida_ensemble/test_aiida_ensemble.py +++ b/tests/aiida_ensemble/test_aiida_ensemble.py @@ -1,6 +1,39 @@ """Tests for :mod:`sscha.aiida_ensemble`.""" import pytest +import numpy as np + +from sscha.aiida_ensemble import AiiDAEnsemble + + +def get_ensemble() -> AiiDAEnsemble: + """Return an AiiDAEnsemble instance.""" + import os + from cellconstructor.Phonons import Phonons + + path = os.path.dirname(os.path.abspath(__file__)) + + return AiiDAEnsemble(Phonons(os.path.join(path,"dyn"), 3), 0, (2,1,2)) + + +def test_clean_runs(): + """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._clean_runs` method.""" + ensemble = get_ensemble() + num_configs, num_atoms = 4, 1 + ensemble.generate(num_configs) + + ensemble.energies = np.ones((num_configs,)) # (configs,) + ensemble.forces = np.ones((num_configs, num_atoms, 3)) # (configs, atoms, force index) + ensemble.stresses = np.ones((num_configs, 3, 3)) # (configs, 3, 3) + ensemble.force_computed = np.array([True, False, True, True], dtype=bool) + ensemble.stress_computed = np.copy(ensemble.force_computed) + ensemble._clean_runs() + + assert all(ensemble.force_computed) + assert len(ensemble.force_computed) == 3 + assert len(ensemble.stress_computed) == 3 + assert np.all(np.isclose(ensemble.forces, np.ones((num_configs-1, num_atoms, 3)))) + @pytest.mark.usefixtures('aiida_profile') def test_get_running_workchains(generate_workchain_pw_node): diff --git a/tests/aiida_ensemble/test_otf_flare.py b/tests/aiida_ensemble/test_otf_flare.py index 3345b069..0ebedb13 100644 --- a/tests/aiida_ensemble/test_otf_flare.py +++ b/tests/aiida_ensemble/test_otf_flare.py @@ -6,7 +6,8 @@ from ase.calculators.lj import LennardJones from flare.atoms import FLARE_Atoms -from .get_sgp import get_sgp_calc, get_random_atoms +from flare.bffs.sgp.calculator import SGP_Calculator +from .get_sgp import get_sgp_calc, get_random_atoms, get_empty_sgp @pytest.fixture @@ -71,7 +72,8 @@ def test_no_otf(generate_ensemble): assert ensemble.flare_name is None assert ensemble.atoms_name is None assert ensemble.checkpt_files is None - assert ensemble.write_model is None + assert ensemble.write_model is None + assert ensemble.init_atoms is None def test_set_otf(generate_ensemble): @@ -104,7 +106,6 @@ def test_predict_with_model(generate_ensemble): ensemble._predict_with_model( ensemble.structures, - ensemble, dft_indices ) @@ -124,11 +125,12 @@ def test_write_model(generate_ensemble): ensemble._write_model() - -def test_update_gp(generate_ensemble): +@pytest.mark.parametrize('flare_calc', (get_sgp_calc(), SGP_Calculator(get_empty_sgp()))) +def test_update_gp(generate_ensemble, flare_calc): """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._update_gp` method.""" ensemble = generate_ensemble() - ensemble.set_otf(get_sgp_calc(), max_atoms_added=-1) + ensemble.set_otf(flare_calc, max_atoms_added=-1) + ensemble.init_atoms = [1] atoms = get_random_atoms() atoms.calc = LennardJones() @@ -143,6 +145,7 @@ def test_update_gp(generate_ensemble): stress ) + assert len(ensemble.gp_model.training_data) in [1, 2] def test_train_gp(generate_ensemble): """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._train_gp` method.""" From a64e3c13c8e8126fd41feba10d4dce8f3007be3a Mon Sep 17 00:00:00 2001 From: bastonero Date: Sat, 9 Sep 2023 00:13:21 +0000 Subject: [PATCH 03/22] Add on-the-fly examples :rocket: Examples for running SSCHA using AiiDA+FLARE to perform the SSCHA minimization are added. These examples serve as well as for testing some hard-to-test logic within the OTF workflow. --- Examples/sscha_and_aiida/clean_runs.sh | 9 + Examples/sscha_and_aiida/get_sgp.py | 175 ++++++++++++++++++ .../run_aiida_flare_ensemble.py | 76 ++++++++ .../sscha_and_aiida/run_aiida_flare_sscha.py | 92 +++++++++ Examples/sscha_and_aiida/run_aiida_sscha.py | 2 +- 5 files changed, 353 insertions(+), 1 deletion(-) create mode 100755 Examples/sscha_and_aiida/clean_runs.sh create mode 100644 Examples/sscha_and_aiida/get_sgp.py create mode 100644 Examples/sscha_and_aiida/run_aiida_flare_ensemble.py create mode 100644 Examples/sscha_and_aiida/run_aiida_flare_sscha.py diff --git a/Examples/sscha_and_aiida/clean_runs.sh b/Examples/sscha_and_aiida/clean_runs.sh new file mode 100755 index 00000000..e6e5ce7b --- /dev/null +++ b/Examples/sscha_and_aiida/clean_runs.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +rm dyn_* +rm -r ensemble*_* +rm -r disp_* +rm minim_* +rm nohup.out +rm *.log +rm otf_run* diff --git a/Examples/sscha_and_aiida/get_sgp.py b/Examples/sscha_and_aiida/get_sgp.py new file mode 100644 index 00000000..e0bb4bd5 --- /dev/null +++ b/Examples/sscha_and_aiida/get_sgp.py @@ -0,0 +1,175 @@ +import numpy as np +from flare.bffs.sgp._C_flare import NormalizedDotProduct, DotProduct, B2 +from flare.bffs.sgp import SGP_Wrapper +from flare.bffs.sgp.calculator import SGP_Calculator +from flare.atoms import FLARE_Atoms +from ase import Atoms +from ase.calculators.lj import LennardJones +from ase.build import make_supercell + +# Define kernel. +sigma = 2.0 +power = 1.0 +dotprod_kernel = DotProduct(sigma, power) +normdotprod_kernel = NormalizedDotProduct(sigma, power) + +# Define remaining parameters for the SGP wrapper. +sigma_e = 0.005 +sigma_f = 0.01 +sigma_s = 0.001 +species_map = {6: 0, 8: 1} +single_atom_energies = {0: 0, 1: 0} +variance_type = "local" +max_iterations = 40 +opt_method = "L-BFGS-B" +bounds = [(None, None), (sigma_e, None), (None, None), (None, None)] + + +def get_atoms(a=2.0, sc_size=2, numbers=[6, 8]) -> Atoms: + """Return an ase.Atoms instance.""" + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) + unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) + multiplier = np.identity(3) * sc_size + atoms = make_supercell(unit_cell, multiplier) + + return atoms + + +def get_random_atoms(a=2.0, sc_size=2, numbers=[6, 8], set_seed: int = 0) -> FLARE_Atoms: + """Create a random structure.""" + if set_seed: + np.random.seed(set_seed) + + atoms = get_atoms(a, sc_size, numbers) + atoms.positions += (2 * np.random.rand(len(atoms), 3) - 1) * 0.05 + flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) + + return flare_atoms + + +def get_isolated_atoms(numbers=[6, 8]) -> FLARE_Atoms: + """Create a random structure.""" + a = 30.0 + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [1, 1, 1], [a / 2, a / 2, a / 2]]) + if 8 in numbers: + numbers = [6, 8, 8] + else: + numbers = [6, 6, 6] + unit_cell = Atoms(cell=cell, positions=positions, numbers=numbers, pbc=True) + atoms = unit_cell + flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) + + return flare_atoms + + +def get_empty_sgp( + n_types=2, power=2, multiple_cutoff=False, the_map=None, + the_atom_energies=None, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: + """Return an empty SGP model.""" + if kernel_type == "NormalizedDotProduct": + kernel = normdotprod_kernel + elif kernel_type == "DotProduct": + kernel = dotprod_kernel + + kernel.power = power + + # Define B2 calculator. + cutoff = 5.0 + cutoff_function = "quadratic" + radial_basis = "chebyshev" + radial_hyps = [0.0, cutoff] + cutoff_hyps = [] + cutoff_matrix = cutoff * np.ones((n_types, n_types)) + if multiple_cutoff: + cutoff_matrix += np.eye(n_types) - 1 + + descriptor_settings = [n_types, 8, 4] + b2_calc = B2( + radial_basis, + cutoff_function, + radial_hyps, + cutoff_hyps, + descriptor_settings, + cutoff_matrix, + ) + + species_map = species_map if the_map is None else the_map + single_atom_energies = single_atom_energies if the_map is None else the_atom_energies + + empty_sgp = SGP_Wrapper( + [kernel], + [b2_calc], + cutoff, + sigma_e, + sigma_f, + sigma_s, + species_map, + single_atom_energies=single_atom_energies, + variance_type=variance_type, + opt_method=opt_method, + bounds=bounds, + max_iterations=max_iterations, + ) + + return empty_sgp + + +def get_updated_sgp(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: + """Return the SGP updated with the new structure properties.""" + if n_types == 1: + numbers = [6, 6] + elif n_types == 2: + numbers = [6, 8] + + sgp = get_empty_sgp(n_types, power, multiple_cutoff, kernel_type) + + # add a random structure to the training set + training_structure = get_random_atoms(numbers=numbers) + training_structure.calc = LennardJones() + + forces = training_structure.get_forces() + energy = training_structure.get_potential_energy() + stress = training_structure.get_stress() + + sgp.update_db( + training_structure, + forces, + custom_range=(1, 2, 3, 4, 5), + energy=energy, + stress=stress, + mode="specific", + rel_e_noise=0.1, + rel_f_noise=0.2, + rel_s_noise=0.1, + ) + + # add an isolated atom to the training data + training_structure = get_isolated_atoms(numbers=numbers) + training_structure.calc = LennardJones() + + forces = training_structure.get_forces() + energy = training_structure.get_potential_energy() + stress = training_structure.get_stress() + + custom_range = [0] + sgp.update_db( + training_structure, + forces, + custom_range=custom_range, + energy=energy, + stress=stress, + mode="specific", + ) + + print("sparse_indices", sgp.sparse_gp.sparse_indices) + + return sgp + + +def get_sgp_calc(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Calculator: + """Return an SGP calculator, ASE type.""" + sgp = get_updated_sgp(n_types, power, multiple_cutoff, kernel_type) + + return SGP_Calculator(sgp) diff --git a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py new file mode 100644 index 00000000..9b77a27d --- /dev/null +++ b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py @@ -0,0 +1,76 @@ +"""Test for an actual AiiDA-FLARE-powered ensemble computation.""" +import numpy as np + +from ase import Atoms +from ase.build import make_supercell +from ase.calculators.lj import LennardJones + +from cellconstructor.Phonons import compute_phonons_finite_displacements +from cellconstructor.Structure import Structure +from sscha.aiida_ensemble import AiiDAEnsemble + +from aiida import load_profile +from aiida_quantumespresso.common.types import ElectronicType + +from flare.bffs.sgp.calculator import SGP_Calculator +from get_sgp import get_empty_sgp + +load_profile() + +# PID: 1013277 + +def main(): + """Run with AiiDA-QuantumESPRESSO + FLARE some ensemble configuration for testing.""" + # =========== GENERAL INPUTS =============== # + np.random.seed(0) + number_of_configurations = 2 + temperature = 0.0 + + # =========== AiiDA ENSEMBLE =============== # + a, sc_size, numbers = 2.0, 1, [6, 8] + cell = np.eye(3) * a + positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) + unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) + multiplier = np.identity(3) * sc_size + atoms = make_supercell(unit_cell, multiplier) + + structure = Structure() + structure.generate_from_ase_atoms(atoms) + + dyn = compute_phonons_finite_displacements(structure, LennardJones(), supercell=[1,1,1]) + dyn.Symmetrize() + dyn.ForcePositiveDefinite() + + ensemble = AiiDAEnsemble(dyn, temperature) + flare_calc = SGP_Calculator(get_empty_sgp()) + ensemble.set_otf(flare_calc) + + # =========== AiiDA INPUTS =============== # + pw_code_label = 'pw@localhost' + aiida_inputs = dict( + pw_code=pw_code_label, + protocol='fast', + overrides={ + 'meta_parameters':{'conv_thr_per_atom': 1e-6}, + 'kpoints_distance': 1000 + }, + options={ + 'resources':{'num_machines': 1, 'num_mpiprocs_per_machine': 2,}, + 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate aiida-sscha\nexport OMP_NUM_THREADS=1', + }, + electronic_type=ElectronicType.INSULATOR, + ) + + # =========== GENERATE & COMPUTE =============== # + ensemble.generate(number_of_configurations) + ensemble.compute_ensemble(**aiida_inputs) # this should include the training too + + print("First population has run.") + + ensemble.generate(number_of_configurations) # here hopefully the model is called + ensemble.compute_ensemble(**aiida_inputs) + + +if __name__ == '__main__': + main() + diff --git a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py new file mode 100644 index 00000000..de71cf90 --- /dev/null +++ b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py @@ -0,0 +1,92 @@ +"""Test for an actual AiiDA-FLARE-powered ensemble computation.""" +import numpy as np + +from ase.build import bulk, make_supercell +from ase.calculators.lj import LennardJones + +from cellconstructor.Phonons import compute_phonons_finite_displacements +from cellconstructor.Structure import Structure +from sscha.aiida_ensemble import AiiDAEnsemble +from sscha.SchaMinimizer import SSCHA_Minimizer +from sscha.Relax import SSCHA +from sscha.Utilities import IOInfo + +from aiida import load_profile +from aiida_quantumespresso.common.types import ElectronicType + +from flare.bffs.sgp.calculator import SGP_Calculator +from get_sgp import get_empty_sgp + +load_profile() + +# PID: 1230420, 1292679 + +def main(): + """Run with AiiDA-QuantumESPRESSO + FLARE + SSCHA @ NVT.""" + # =========== GENERAL INPUTS =============== # + np.random.seed(0) + number_of_configurations = 8 + max_iterations = 20 + temperature = 0.0 + + # =========== AiiDA ENSEMBLE =============== # + atoms = bulk('Si') + matrix = [[-1,1,1],[1,-1,1],[1,1,-1]] # ==> 8 atoms cell | i.e. conventional cell + atoms = make_supercell(atoms, matrix) + structure = Structure() + structure.generate_from_ase_atoms(atoms) + + dyn = compute_phonons_finite_displacements(structure, LennardJones(), supercell=[1,1,1]) + dyn.Symmetrize() + dyn.ForcePositiveDefinite() + + ensemble = AiiDAEnsemble(dyn, temperature) + flare_calc = SGP_Calculator(get_empty_sgp(n_types=1, the_map={14: 0}, the_atom_energies={0: 0})) + ensemble.set_otf(flare_calc, std_tolerance_factor=-0.001, max_atoms_added=-1) + + # =========== AiiDA INPUTS =============== # + pw_code_label = 'pw@localhost' + aiida_inputs = dict( + pw_code=pw_code_label, + protocol='fast', + overrides={ + 'meta_parameters':{'conv_thr_per_atom': 1e-8}, + 'kpoints_distance': 0.8, + }, + options={ + 'resources':{'num_machines': 1, 'num_mpiprocs_per_machine': 1,}, + 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate aiida-sscha\nexport OMP_NUM_THREADS=1', + }, + electronic_type=ElectronicType.METAL, + ) + + # =========== SSCHA SETTINGS & COMPUTE =============== # + minim = SSCHA_Minimizer(ensemble) + minim.set_minimization_step(0.1) + + relax = SSCHA( + minimizer=minim, + aiida_inputs=aiida_inputs, + N_configs=number_of_configurations, + max_pop=max_iterations, + save_ensemble=True, + ) + + ioinfo = IOInfo() + ioinfo.SetupSaving('./minim_t0') + relax.setup_custom_functions( custom_function_post = ioinfo.CFP_SaveAll) + + # Run the NVT simulation + relax.vc_relax( + target_press = 0.0, + restart_from_ens = False, + ensemble_loc = './ensembles_P0_T0', + ) + + # Print in standard output + relax.minim.finalize() + + +if __name__ == '__main__': + main() + diff --git a/Examples/sscha_and_aiida/run_aiida_sscha.py b/Examples/sscha_and_aiida/run_aiida_sscha.py index a6134521..646e61d6 100644 --- a/Examples/sscha_and_aiida/run_aiida_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_sscha.py @@ -31,7 +31,7 @@ directory_output = "./thermal_expansion" aiida_inputs = dict( - pw_code_label=pw_code_label, + pw_code=pw_code_label, protocol='precise', overrides={ 'pseudo_family': 'SSSP/1.3/PBEsol/precision', From f8d2b9d122cc4b2423621ea78b7098526c976748 Mon Sep 17 00:00:00 2001 From: bastonero Date: Sat, 9 Sep 2023 00:18:18 +0000 Subject: [PATCH 04/22] Update testsuite yaml to perform tests using FLARE The mir-flare python package must be installed to perform the tests during the continous integration workflow. --- .github/workflows/python-testsuite.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/python-testsuite.yml b/.github/workflows/python-testsuite.yml index d4fd8e76..18306830 100644 --- a/.github/workflows/python-testsuite.yml +++ b/.github/workflows/python-testsuite.yml @@ -36,6 +36,7 @@ jobs: run: | python -m pip install --upgrade pip pip install flake8 pytest~=6.0 pgtest~=1.3 aiida-core~=2.3 aiida-quantumespresso~=4.3 + pip install git+https://github.com/mir-group/flare.git@development if [ ${{matrix.python-version}} -eq 2.7 ]; then pip install -r requirements2.txt; else pip install -r requirements.txt; fi From 2256e933cfc72427e60068e557d9c7b17a3563b3 Mon Sep 17 00:00:00 2001 From: bastonero Date: Tue, 5 Dec 2023 15:30:16 +0000 Subject: [PATCH 05/22] Improve on-the-fly --- .../sscha_and_aiida/run_aiida_flare_sscha.py | 2 +- Modules/aiida_ensemble.py | 33 +++++++++++-------- tests/aiida_ensemble/test_otf_flare.py | 1 + 3 files changed, 22 insertions(+), 14 deletions(-) diff --git a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py index de71cf90..07bcbd63 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py @@ -25,7 +25,7 @@ def main(): """Run with AiiDA-QuantumESPRESSO + FLARE + SSCHA @ NVT.""" # =========== GENERAL INPUTS =============== # np.random.seed(0) - number_of_configurations = 8 + number_of_configurations = 4 max_iterations = 20 temperature = 0.0 diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index f9065dbd..ecfcbc2d 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -39,27 +39,30 @@ def compute_ensemble( # pylint: disable=arguments-renamed options: dict = None, overrides: dict = None, group_label: str = None, + waiting_time: int = 2.5, **kwargs ) -> None: - """Get ensemble properties. - - All the parameters refer to the - :func:`aiida_quantumespresso.workflows.pw.base.PwBaseWorkChain.get_builder_from_protocol` - method. + """Compute ensemble properties. Args: ---- pw_code: The string associated with the AiiDA code for `pw.x` protocol: The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' options: The options for the calculations, such as the resources, wall-time, etc. - overrides: The overrides for the get_builder_from_protocol + overrides: The overrides for the :func:`aiida_quantumespresso.workflows.pw.base.PwBaseWorkChain.get_builder_from_protocol` group_label: The group label where to add the submitted nodes for eventual future inspection + waiting_time: Time delay in seconds for WorkChain submission; usefull for many configurations kwargs: The kwargs for the get_builder_from_protocol """ from aiida.orm import load_group - group = None if group_label is None else load_group(group_label) + try: + group = None if group_label is None else load_group(group_label) + except: # NotExsistent + from aiida.orm import Group + group = Group(group_label) + group.store() # Check if not all the calculation needs to be done if self.force_computed is None: @@ -100,6 +103,7 @@ def compute_ensemble( # pylint: disable=arguments-renamed protocol=protocol, options=options, overrides=overrides, + waiting_time=waiting_time, **kwargs ) @@ -250,9 +254,12 @@ def _update_gp( from ase.calculators.singlepoint import SinglePointCalculator tic = time.time() - is_not_empty_model = len(self.gp_model.training_data) > 0 + is_empty_model = len(self.gp_model.training_data) == 0 - if is_not_empty_model: + if is_empty_model: + std_in_bound = False + train_atoms = self.init_atoms + else: self._compute_properties(atoms) # get max uncertainty atoms @@ -273,15 +280,12 @@ def _update_gp( ) self.output.write_wall_time(tic, task='Env Selection') - else: - std_in_bound = False - train_atoms = self.init_atoms # Here we make the decision to skip adding environments even if the # DFT calculation was performed. This avoids slowing down the model, # while the SSCHA is feeded with the DFT results. if not std_in_bound: - if is_not_empty_model: + if not is_empty_model: stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) self.output.add_atom_info(train_atoms, stds) @@ -396,6 +400,7 @@ def submit_and_get_workchains( protocol: str = 'moderate', options: dict = None, overrides: dict = None, + waiting_time: int = 2.5, **kwargs ) -> list[WorkChainNode]: """Submit and return the workchains for a list of :class:`~cellconstructor.Structure.Structure`. @@ -409,6 +414,7 @@ def submit_and_get_workchains( protocol: The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' options: The options for the calculations, such as the resources, wall-time, etc. overrides: The overrides for the get_builder_from_protocol + waiting_time: Time delay in seconds for WorkChain submission; usefull for many configurations kwargs: The kwargs for the get_builder_from_protocol """ @@ -428,5 +434,6 @@ def submit_and_get_workchains( builder.metadata.label = f'T_{temperature}_id_{i}' workchains.append(submit(builder)) print(f'Launched with PK={workchains[-1].pk}') + time.sleep(waiting_time) return workchains diff --git a/tests/aiida_ensemble/test_otf_flare.py b/tests/aiida_ensemble/test_otf_flare.py index 0ebedb13..46075029 100644 --- a/tests/aiida_ensemble/test_otf_flare.py +++ b/tests/aiida_ensemble/test_otf_flare.py @@ -125,6 +125,7 @@ def test_write_model(generate_ensemble): ensemble._write_model() + @pytest.mark.parametrize('flare_calc', (get_sgp_calc(), SGP_Calculator(get_empty_sgp()))) def test_update_gp(generate_ensemble, flare_calc): """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._update_gp` method.""" From 3f9e92238ce4c364eb1584e48301ec9a26c8bf21 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Thu, 4 Apr 2024 09:15:37 +0200 Subject: [PATCH 06/22] Add submission in batches In AiiDAEnsemble it is added the possibility of splitting the submission of all the calculations in a certain number of batches. This is convenient especially when performing the calculations using active-learning/on-the-fly simulations. --- Modules/aiida_ensemble.py | 184 +++++++++++++++++++++++--------------- 1 file changed, 112 insertions(+), 72 deletions(-) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index ecfcbc2d..d528ab52 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -35,11 +35,12 @@ class AiiDAEnsemble(Ensemble): def compute_ensemble( # pylint: disable=arguments-renamed self, pw_code: str, - protocol: str = 'moderate', - options: dict = None, - overrides: dict = None, - group_label: str = None, - waiting_time: int = 2.5, + protocol: str['fast', 'moderate', 'precise'] = 'moderate', + options: dict | None = None, + overrides: dict | None = None, + group_label: str | None = None, + waiting_time: int | float = 2.5, + batch_number: int = 1, **kwargs ) -> None: """Compute ensemble properties. @@ -52,6 +53,10 @@ def compute_ensemble( # pylint: disable=arguments-renamed overrides: The overrides for the :func:`aiida_quantumespresso.workflows.pw.base.PwBaseWorkChain.get_builder_from_protocol` group_label: The group label where to add the submitted nodes for eventual future inspection waiting_time: Time delay in seconds for WorkChain submission; usefull for many configurations + batch_number: Number of batches used to split the submission of all the structures, one after the other. + For example: 2 would submit two batches, computing the first one, then the second. + This is particularly useful when performing on-the-fly simulations, so that the ML potential + can be trained on previous batches and (hopefully) predict on the following batches. kwargs: The kwargs for the get_builder_from_protocol """ @@ -77,80 +82,87 @@ def compute_ensemble( # pylint: disable=arguments-renamed pass structures = copy(self.structures) - dft_indices = np.arange(0, len(structures), 1).tolist() # store here the indices to run with DFT/AiiDA - - # ============= FLARE SECTION ============= # - # If a model is specified and it's not empty, try to predict. - # Predict only the ones that are within uncertainty, the rest do via DFT/AiiDA. - if self.gp_model is not None: - number_of_atoms = structures[0].get_ase_atoms().get_global_number_of_atoms() - - if self.max_atoms_added < 0: - self.max_atoms_added = number_of_atoms - - if self.init_atoms is None: - self.init_atoms = list(range(number_of_atoms)) + dft_indices_batches = split_array(list(range(len(structures))), batch_number) # store here the indices to run with DFT/AiiDA + + if batch_number > 1: + print(f"Submission in batches is active. Number of batches that will be submitted: {batch_number}") + + for batch_n, dft_indices in enumerate(dft_indices_batches): + if batch_number > 1: + print(f"Batch submitted: {batch_n}/{batch_number}") - if len(self.gp_model.training_data) > 0: - self._predict_with_model(structures, dft_indices) - - # ============= AIIDA SECTION START ============= # - workchains = submit_and_get_workchains( - structures=[structures[i] for i in dft_indices], - pw_code=pw_code, - temperature=self.current_T, - dft_indices=dft_indices, - protocol=protocol, - options=options, - overrides=overrides, - waiting_time=waiting_time, - **kwargs - ) + # ================ FLARE SECTION ================= # + # If a model is specified and it's not empty, try to predict. + # Predict only the ones that are within uncertainty, the rest do via DFT/AiiDA. + if self.gp_model is not None: + number_of_atoms = structures[0].get_ase_atoms().get_global_number_of_atoms() + + if self.max_atoms_added < 0: + self.max_atoms_added = number_of_atoms + + if self.init_atoms is None: + self.init_atoms = list(range(number_of_atoms)) + + if len(self.gp_model.training_data) > 0: + self._predict_with_model(structures, dft_indices) + + # ================= AIIDA SECTION ================ # + workchains = submit_and_get_workchains( + structures=[structures[i] for i in dft_indices], + pw_code=pw_code, + temperature=self.current_T, + dft_indices=dft_indices, + protocol=protocol, + options=options, + overrides=overrides, + waiting_time=waiting_time, + **kwargs + ) - if group: - group.add_nodes(workchains) + if group: + group.add_nodes(workchains) - workchains_copy = copy(workchains) - while workchains_copy: - workchains_copy = get_running_workchains(workchains_copy, self.force_computed) - if workchains_copy: - time.sleep(60) # wait before checking again + workchains_copy = copy(workchains) + while workchains_copy: + workchains_copy = get_running_workchains(workchains_copy, self.force_computed) + if workchains_copy: + time.sleep(60) # wait before checking again - for i, is_computed in enumerate(self.force_computed): - if is_computed and i in dft_indices: - dft_stress = None - wc = workchains[dft_indices.index(i)] + for i, is_computed in enumerate(self.force_computed): + if is_computed and i in dft_indices: + dft_stress = None + wc = workchains[dft_indices.index(i)] - dft_energy = wc.outputs.output_parameters.dict.energy - dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] + dft_energy = wc.outputs.output_parameters.dict.energy + dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] - self.energies[i] = dft_energy / CONSTANTS.ry_to_ev - self.forces[i] = dft_forces / CONSTANTS.ry_to_ev + self.energies[i] = dft_energy / CONSTANTS.ry_to_ev + self.forces[i] = dft_forces / CONSTANTS.ry_to_ev - if self.has_stress: - stress = wc.outputs.output_trajectory.get_array('stress')[-1] + if self.has_stress: + stress = wc.outputs.output_trajectory.get_array('stress')[-1] - self.stresses[i] = stress * gpa_to_rybohr3 + self.stresses[i] = stress * gpa_to_rybohr3 - dft_stress = ase_stress_units * np.array([ - stress[0, 0], stress[1, 1], stress[2, 2], - stress[1, 2], stress[0, 2], stress[0, 1], - ]) + dft_stress = ase_stress_units * np.array([ + stress[0, 0], stress[1, 1], stress[2, 2], + stress[1, 2], stress[0, 2], stress[0, 1], + ]) - if self.gp_model is not None: - self._update_gp( - FLARE_Atoms.from_ase_atoms(wc.inputs.pw.structure.get_ase()), - dft_frcs=dft_forces, - dft_energy=dft_energy, - dft_stress=dft_stress, - ) - # ============= AIIDA SECTION END ============= # + if self.gp_model is not None: + self._update_gp( + FLARE_Atoms.from_ase_atoms(wc.inputs.pw.structure.get_ase()), + dft_frcs=dft_forces, + dft_energy=dft_energy, + dft_stress=dft_stress, + ) - if self.gp_model is not None: - self._train_gp() - self._write_model() + # ================ TRAIN SECTION ================ # + if self.gp_model is not None: + self._train_gp() + self._write_model() - # ============= FINALIZE ============= # + # ================ FINALIZE ================ # if self.has_stress: self.stress_computed = copy(self.force_computed) @@ -168,10 +180,13 @@ def _predict_with_model( Args: ---- structures: list of :class:`~cellconstructor.Structure.Structure` to simulate + sub_indices: list of integers related to the structures batch dft_indices: list of integers related to the structures """ - for index, structure in enumerate(structures): + sub_indices = copy(dft_indices) + for index in sub_indices: + structure = structures[index] atoms = FLARE_Atoms.from_ase_atoms(structure.get_ase_atoms()) self._compute_properties(atoms) @@ -195,9 +210,9 @@ def _predict_with_model( self.output.write_wall_time(tic, task='Env Selection') if not std_in_bound: - print(f"[DFT CALLED] For structure index {index}") + print(f"[DFT CALLED] For structure with id={index}") else: - print(f"[BFFS USED] For structure index {index}") + print(f"[BFFS USED] For structure with id={index}") dft_indices.remove(index) # remove index computed via ML-FF self.energies[index] = atoms.potential_energy / units.Ry @@ -400,7 +415,7 @@ def submit_and_get_workchains( protocol: str = 'moderate', options: dict = None, overrides: dict = None, - waiting_time: int = 2.5, + waiting_time: int | float = 2.5, **kwargs ) -> list[WorkChainNode]: """Submit and return the workchains for a list of :class:`~cellconstructor.Structure.Structure`. @@ -433,7 +448,32 @@ def submit_and_get_workchains( ) builder.metadata.label = f'T_{temperature}_id_{i}' workchains.append(submit(builder)) - print(f'Launched with PK={workchains[-1].pk}') + print(f'Launched with id={i} PK={workchains[-1].pk}') time.sleep(waiting_time) return workchains + +def split_array(array: list, n: int) -> list[list]: + """Split a generic array into N subarrays. + + .. note:: if `n` is larger then len(array) + + Args: + ---- + array: a flat array to split into (semi)equal pieces. + n: number of pieces + + """ + array = np.array(array) + # Ensure N does not exceed the number of elements in the array + n = min(n, len(array)) + + # Calculate the size of each chunk + chunk_sizes = np.full(n, len(array) // n) + chunk_sizes[:len(array) % n] += 1 + + # Generate the indices at which to split the array + indices = np.cumsum(chunk_sizes) + + # Split the array at the calculated indices + return np.split(array, indices[:-1]) \ No newline at end of file From 8d145daff8a89862d5bbd6f4e328df3923e7c281 Mon Sep 17 00:00:00 2001 From: bastonero Date: Thu, 25 Apr 2024 09:28:26 +0000 Subject: [PATCH 07/22] Add tweaks and examples --- Examples/sscha_and_aiida/Si.pwi | 38 + Examples/sscha_and_aiida/analysis.ipynb | 140 + Examples/sscha_and_aiida/clean_runs.sh | 4 + Examples/sscha_and_aiida/dataset-sscha.xyz | 1638 ++++++++ Examples/sscha_and_aiida/get_sgp.py | 48 +- Examples/sscha_and_aiida/log2 | 3460 +++++++++++++++++ Examples/sscha_and_aiida/log3 | 1273 ++++++ Examples/sscha_and_aiida/model.ipynb | 575 +++ Examples/sscha_and_aiida/model.json | 1 + .../run_aiida_flare_ensemble.py | 12 +- .../sscha_and_aiida/run_aiida_flare_sscha.py | 70 +- Examples/sscha_and_aiida/run_aiida_sscha.py | 8 +- Examples/sscha_and_aiida/run_flare_sscha.py | 105 + Examples/sscha_and_aiida/submit.sh | 9 + Examples/sscha_and_aiida/write_xyz.ipynb | 377 ++ Modules/Ensemble.py | 1 + Modules/aiida_ensemble.py | 140 +- tests/aiida_ensemble/get_sgp.py | 2 +- tests/aiida_ensemble/test_aiida_ensemble.py | 35 +- 19 files changed, 7784 insertions(+), 152 deletions(-) create mode 100644 Examples/sscha_and_aiida/Si.pwi create mode 100644 Examples/sscha_and_aiida/analysis.ipynb create mode 100644 Examples/sscha_and_aiida/dataset-sscha.xyz create mode 100644 Examples/sscha_and_aiida/log2 create mode 100644 Examples/sscha_and_aiida/log3 create mode 100644 Examples/sscha_and_aiida/model.ipynb create mode 100644 Examples/sscha_and_aiida/model.json create mode 100644 Examples/sscha_and_aiida/run_flare_sscha.py create mode 100755 Examples/sscha_and_aiida/submit.sh create mode 100644 Examples/sscha_and_aiida/write_xyz.ipynb diff --git a/Examples/sscha_and_aiida/Si.pwi b/Examples/sscha_and_aiida/Si.pwi new file mode 100644 index 00000000..400f106e --- /dev/null +++ b/Examples/sscha_and_aiida/Si.pwi @@ -0,0 +1,38 @@ +&CONTROL + calculation = 'scf' + etot_conv_thr = 2.0000000000d-05 + forc_conv_thr = 1.0000000000d-04 + outdir = './out/' + prefix = 'aiida' + pseudo_dir = './pseudo/' + tprnfor = .true. + tstress = .true. + verbosity = 'high' +/ +&SYSTEM + degauss = 1.4699723600d-02 + ecutrho = 2.4000000000d+02 + ecutwfc = 3.0000000000d+01 + ibrav = 0 + nat = 2 + nosym = .false. + ntyp = 1 + occupations = 'smearing' + smearing = 'cold' +/ +&ELECTRONS + conv_thr = 4.0000000000d-10 + electron_maxstep = 80 + mixing_beta = 4.0000000000d-01 +/ +ATOMIC_SPECIES +Si 28.0855 Si.pbesol-n-rrkjus_psl.1.0.0.UPF +ATOMIC_POSITIONS crystal +Si 0.0000000000 0.0000000000 0.0000000000 +Si 0.2500000000 0.2500000000 0.2500000000 +K_POINTS automatic +11 11 11 0 0 0 +CELL_PARAMETERS angstrom + 2.7154800000 2.7154800000 0.0000000000 + 2.7154800000 0.0000000000 2.7154800000 + 0.0000000000 2.7154800000 2.7154800000 diff --git a/Examples/sscha_and_aiida/analysis.ipynb b/Examples/sscha_and_aiida/analysis.ipynb new file mode 100644 index 00000000..833f2e09 --- /dev/null +++ b/Examples/sscha_and_aiida/analysis.ipynb @@ -0,0 +1,140 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "plt.rcParams.update({\n", + " 'text.usetex': False,\n", + " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", + " 'pdf.fonttype':42,\n", + " 'font.family':'sans-serif',\n", + " 'font.sans-serif':'Arial',\n", + " 'font.size':14,\n", + " 'mathtext.fontset': 'stixsans',\n", + "})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Thermal expansion" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import scipy, scipy.optimize\n", + "\n", + "# Load the data from the final data file\n", + "temperatures, volumes = np.loadtxt('./thermal_expansion/thermal_expansion.dat', unpack = True)\n", + "volumes2 = np.array([volumes[0]]+volumes[:-1].tolist())\n", + "t_step = 10\n", + "\n", + "# Prepare the figure and plot the V(T) from the sscha data\n", + "plt.figure(dpi = 300)\n", + "# plt.scatter(temperatures, (volumes-volumes2)/(volumes2*t_step), label = \"SSCHA data\")\n", + "plt.scatter(temperatures, volumes, label = \"SSCHA data\")\n", + "\n", + "\n", + "# Evaluate the volume thermal expansion\n", + "# plt.text(0.6, 0.2, r\"$\\alpha_v = \"+\"{:.1f}\".format(vol_thermal_expansion*1e6)+r\"\\times 10^{-6} $ K$^{-1}$\",\n", + "# transform = plt.gca().transAxes)\n", + "\n", + "# Adjust the plot adding labels, legend, and saving in eps\n", + "plt.xlabel(\"Temperature [K]\")\n", + "plt.ylabel(r\"Volume [$\\AA^3$]\")\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "5.439671260411459" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(volumes[0]*4)**(1/3)\n", + "(40.24*4)**(1/3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.8.12 ('aiida')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.18" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "ad8f63c217015a5132ad55bc66b40838ad2ef6ce473dcbccdf600c93ceb49af4" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Examples/sscha_and_aiida/clean_runs.sh b/Examples/sscha_and_aiida/clean_runs.sh index e6e5ce7b..4c9c21cb 100755 --- a/Examples/sscha_and_aiida/clean_runs.sh +++ b/Examples/sscha_and_aiida/clean_runs.sh @@ -6,4 +6,8 @@ rm -r disp_* rm minim_* rm nohup.out rm *.log +rm -r thermal* +rm *.dat +rm *.pdf rm otf_run* +rm input_tmp.in diff --git a/Examples/sscha_and_aiida/dataset-sscha.xyz b/Examples/sscha_and_aiida/dataset-sscha.xyz new file mode 100644 index 00000000..addd9b53 --- /dev/null +++ b/Examples/sscha_and_aiida/dataset-sscha.xyz @@ -0,0 +1,1638 @@ +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.4769424614865 stress="-0.014820901214644265 -0.01557470866708033 -0.005781638889147252 -0.01557470866708033 -0.0047973738599006496 0.0135979151894983 -0.005781638889147252 0.0135979151894983 -0.004756056764456529" free_energy=-2462.4769424614865 pbc="T T T" +Si 0.09972678 -0.02068351 -0.04557743 28.08550000 -0.33648618 -0.49672247 0.96134754 +Si 1.43339991 1.18521479 1.59897180 28.08550000 -1.42965058 1.61206289 -1.96754978 +Si -0.10758289 2.76321767 2.75046847 28.08550000 1.88071977 -0.53454057 -0.48149948 +Si 1.50678482 3.92813582 4.04282464 28.08550000 -1.14124917 1.83131371 -0.45745170 +Si 2.86837446 -0.03325038 2.73159308 28.08550000 0.89224297 -0.71371354 1.47523058 +Si 4.24337347 1.57638970 4.11219467 28.08550000 -1.58451635 -2.20272215 1.37846377 +Si 2.63904836 2.78791788 5.71902841 28.08550000 1.41272783 0.60749510 -3.75212211 +Si 4.18050070 4.00837220 6.58843482 28.08550000 0.21762562 1.08964687 2.86787167 +Si 2.60953181 2.63158105 -0.04900964 28.08550000 -0.53567082 1.33829851 1.47327526 +Si 4.05408195 4.03322869 1.70005328 28.08550000 0.45992561 -0.40197835 -2.29028672 +Si 2.52630759 5.68412200 2.48616260 28.08550000 2.19139644 -2.76047541 2.98546776 +Si 4.00814780 6.85641882 4.01827420 28.08550000 -1.56978572 0.21876591 -0.68009431 +Si 5.66541808 2.32193637 2.62361829 28.08550000 -0.95835041 3.84808674 1.16447189 +Si 6.61727572 4.16460070 4.03215422 28.08550000 1.01294881 -0.73419341 0.08929775 +Si 5.20295363 5.67302025 5.52688110 28.08550000 -0.53908756 -2.21700591 -2.89808419 +Si 6.76225781 6.74937796 6.47352748 28.08550000 0.02720998 -0.48431792 0.13166208 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.922420317944 stress="-0.021717183523106236 0.007882383653061643 -0.02436882289294223 0.007882383653061643 -0.013498754160432412 0.00536112267329376 -0.02436882289294223 0.00536112267329376 -0.019646737962517532" free_energy=-2461.922420317944 pbc="T T T" +Si -0.12998041 0.27726547 0.24962234 28.08550000 -0.58803674 -2.64511232 -2.19633836 +Si 1.25986391 1.26970733 1.55388541 28.08550000 2.91875714 1.38579167 -1.43786937 +Si 0.04046622 2.68572250 2.72521375 28.08550000 -0.43669081 -0.99657937 -0.84595232 +Si 1.22196100 3.84249852 4.03640899 28.08550000 0.92672404 4.92823313 1.57268876 +Si 2.74799632 -0.18268193 2.46045432 28.08550000 0.02177236 1.47943973 1.05557410 +Si 3.95619787 1.07580238 4.03791389 28.08550000 -0.14447543 2.58361282 -0.19411469 +Si 2.77196306 3.12686265 5.33340682 28.08550000 0.59916447 -3.89547242 0.94533625 +Si 4.23345855 3.99565458 6.88123975 28.08550000 -0.31525272 0.06025869 -1.84102296 +Si 2.83617218 2.74656735 -0.10885403 28.08550000 -2.13579557 1.06574564 1.67394985 +Si 4.06838956 4.11935734 1.37214169 28.08550000 -1.12290229 0.70797021 0.17314554 +Si 2.85884186 5.51297850 3.02038904 28.08550000 -1.85562889 -0.97677262 -2.11002823 +Si 4.23635814 6.96320679 4.14601799 28.08550000 -0.73707741 -1.26382728 0.07930002 +Si 5.20128801 2.71530559 2.66809878 28.08550000 2.23901713 -1.44006277 0.85994221 +Si 6.94889812 4.12581142 3.88493816 28.08550000 -2.76276755 -1.80662135 1.53799198 +Si 5.22012900 5.36714542 5.36125051 28.08550000 3.31573932 -0.07829806 0.08235937 +Si 6.83759662 6.66839610 6.68747261 28.08550000 0.07745320 0.89169430 0.64503758 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2463.357141462776 stress="-0.012632013313782421 -0.0014800701745760474 -0.000781352182732144 -0.0014800701745760474 -0.020262821763473198 0.020178351257231882 -0.000781352182732144 0.020178351257231882 -0.02263901383034839" free_energy=-2463.357141462776 pbc="T T T" +Si 0.15000253 0.21386150 0.13826607 28.08550000 -1.00443794 -2.61143602 -1.50176025 +Si 1.41142920 1.28958389 1.56923231 28.08550000 0.05676610 2.83817054 -1.12290075 +Si -0.12683562 2.64926404 2.75433155 28.08550000 1.19300779 0.73856043 -0.30931733 +Si 1.35280360 4.02499182 3.98369427 28.08550000 -1.06174192 -0.62650867 2.40797717 +Si 2.77683619 -0.10929058 2.51427728 28.08550000 -0.57990202 1.08474969 4.46136348 +Si 4.11725801 1.30354360 4.19326665 28.08550000 0.07800598 0.90633930 -1.60244902 +Si 2.77197745 2.75160142 5.51353159 28.08550000 -0.39756993 -0.12098866 -1.21987890 +Si 4.16887593 4.24758168 6.75453809 28.08550000 -1.43054815 -5.48656642 1.74741193 +Si 2.62927672 2.61990888 -0.13401943 28.08550000 0.76408762 0.63854092 0.97888401 +Si 4.09029590 4.14263991 1.25638144 28.08550000 -0.43651212 -0.60290774 0.55123320 +Si 2.54030893 5.38903513 2.77906741 28.08550000 2.23884435 1.12048083 -2.06638324 +Si 4.27242359 6.61056985 4.13808658 28.08550000 -5.25093022 2.96142434 -3.48324900 +Si 5.62344235 2.77630895 2.68160179 28.08550000 -3.13399678 -0.87517908 -0.63382037 +Si 6.66070402 4.16364838 4.03034521 28.08550000 1.77961114 0.12655741 0.79416696 +Si 5.21076470 5.45940006 5.50307077 28.08550000 5.40793798 -0.52942047 -0.61947002 +Si 6.66003648 6.77695147 6.63392841 28.08550000 1.77737788 0.43818359 1.61819188 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2464.228303563621 stress="-0.011500843056290054 0.019807415555911333 0.00814038596016826 0.019807415555911333 -0.012316167073054033 -0.010755299022942817 0.00814038596016826 -0.010755299022942817 -0.006005669362222039" free_energy=-2464.228303563621 pbc="T T T" +Si 0.31029685 0.00472207 0.06895048 28.08550000 -2.38107880 0.60784992 -0.14964283 +Si 1.24789634 1.48670075 1.47917265 28.08550000 0.61956875 0.89181437 -0.40807623 +Si -0.20405999 2.80281396 2.70616937 28.08550000 0.35644951 0.70679059 0.59463599 +Si 1.36779219 3.99401564 4.19540059 28.08550000 0.44364179 -0.99528147 -1.72780007 +Si 2.60835553 0.16836400 2.69870159 28.08550000 1.70390166 -1.08833278 0.41731112 +Si 4.03625013 1.21569885 4.27407948 28.08550000 0.70070710 1.28854870 -0.72546528 +Si 2.59243742 2.68537281 5.68141251 28.08550000 1.41884500 -0.34717117 -1.29989857 +Si 4.16139570 4.27195771 6.53923588 28.08550000 -2.37653849 -1.21966421 2.69211492 +Si 2.63854417 2.59309529 -0.12946238 28.08550000 -0.54100406 2.20430492 1.82503507 +Si 4.07800990 4.22184693 1.18371556 28.08550000 0.77126897 -2.36587921 0.01700116 +Si 2.77296415 5.28200110 2.72741722 28.08550000 -0.24401877 0.44358959 0.81877653 +Si 4.10055072 6.74040386 4.22899537 28.08550000 -1.80209775 1.14627593 -3.57712641 +Si 5.67625811 2.58635515 2.51108132 28.08550000 -3.60374761 2.73116072 2.70710779 +Si 6.74630183 4.18630523 4.09126623 28.08550000 1.52525370 -2.52524467 -2.46824074 +Si 5.47578867 5.50581721 5.26561825 28.08550000 0.83202491 -0.69795808 0.95571323 +Si 6.70081828 6.56412945 6.78784590 28.08550000 2.57682383 -0.78080288 0.32855433 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2465.4392891762413 stress="-0.00872708871547477 0.01877357001213179 0.002921577726737582 0.01877357001213179 -0.01040639910585913 0.007378315088643371 0.002921577726737582 0.007378315088643371 -0.0037984183078294707" free_energy=-2465.4392891762413 pbc="T T T" +Si 0.01109723 0.05331162 -0.30805493 28.08550000 -0.04119113 -0.85191599 2.92302749 +Si 1.35288393 1.40202392 1.26507280 28.08550000 -0.50257121 -0.69757576 -0.63377975 +Si 0.10441297 2.68617608 2.81684596 28.08550000 0.72942067 -0.79872270 -0.95828921 +Si 1.38083001 3.95928750 4.11758296 28.08550000 1.74781302 1.52316520 -0.21222117 +Si 2.71573018 0.09571817 2.64455118 28.08550000 -0.30191795 -0.81187672 0.23402798 +Si 3.94508287 1.40206995 4.12009270 28.08550000 0.09425613 -0.13187496 -0.95854170 +Si 2.79538518 2.76095563 5.50206754 28.08550000 -0.68307602 -0.00346945 1.86466554 +Si 4.28878509 4.06606145 7.00006336 28.08550000 -2.49562607 0.02595940 -0.61967313 +Si 2.51167709 2.67589694 -0.26718413 28.08550000 0.20652077 2.03077629 1.84385735 +Si 4.16937067 3.96955271 1.47750425 28.08550000 -1.22917550 1.30283323 -3.53240644 +Si 2.89326855 5.37842774 2.74523127 28.08550000 -0.70178851 0.30872958 0.91534768 +Si 4.14509763 7.00372473 4.17449134 28.08550000 -0.66068043 -2.37463459 -0.45883469 +Si 5.31308932 2.51804420 2.60926715 28.08550000 1.39052482 0.38865515 1.88564163 +Si 6.64436822 4.18943451 3.95024094 28.08550000 -0.66130084 -0.19983308 -0.02463682 +Si 5.25796655 5.48913687 5.58486009 28.08550000 1.66182376 0.07514049 -1.64145728 +Si 6.78055451 6.65977798 6.87696750 28.08550000 1.44696824 0.21464392 -0.62672721 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.551010810532 stress="-0.03343012100267611 0.007133166989008258 0.058551833190377864 0.007133166989008258 -0.015116547986488862 -0.010076780499982703 0.058551833190377864 -0.010076780499982703 -0.029238731209289225" free_energy=-2460.551010810532 pbc="T T T" +Si 0.12998041 -0.27726547 -0.24962234 28.08550000 -5.88010898 5.26277067 5.05002371 +Si 1.45561609 1.44577267 1.16159459 28.08550000 -4.49475491 -4.45721989 4.66046971 +Si -0.04046622 2.74523750 2.70574625 28.08550000 -0.25481175 -0.14411367 -0.25971021 +Si 1.49351900 4.30394148 4.11003101 28.08550000 4.47487437 -5.91326104 -3.95136718 +Si 2.68296368 0.18268193 2.97050568 28.08550000 -0.08124017 -0.83902962 -1.57457389 +Si 4.19024213 1.63967762 4.10852611 28.08550000 0.60366056 -2.98081252 -0.19174464 +Si 2.65899694 2.30409735 5.52851318 28.08550000 1.75810437 4.56780175 -1.69124001 +Si 3.91298145 4.15078542 6.69616025 28.08550000 0.39845928 0.00793417 1.17410607 +Si 2.59478782 2.68439265 0.10885403 28.08550000 4.31744367 2.59126057 -3.89816334 +Si 4.07805044 4.02708266 1.34333831 28.08550000 1.35995106 -0.50474380 -0.77139084 +Si 2.57211814 5.34894150 2.41057096 28.08550000 1.39884568 0.15377793 1.68866556 +Si 3.91008186 6.61419321 4.00042201 28.08550000 1.19534852 1.16238132 0.22730223 +Si 5.66063199 2.71565441 2.76286122 28.08550000 -3.22072755 2.40693767 0.57046325 +Si 6.62850188 4.02062858 4.26150184 28.08550000 2.89545524 0.85676175 -0.81222947 +Si 5.64179100 5.49477458 5.50066949 28.08550000 -3.95346597 0.35390875 0.17295116 +Si 6.73980338 6.90900390 6.88992739 28.08550000 -0.51703315 -2.52435430 -0.39356184 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2464.133808224995 stress="-0.015515946575782025 0.0006601553694293908 0.0010154823902488268 0.0006601553694293908 -0.016128357746031545 -0.005514455005275273 0.0010154823902488268 -0.005514455005275273 -0.012512652815832737" free_energy=-2464.133808224995 pbc="T T T" +Si -0.15000253 -0.21386150 -0.13826607 28.08550000 -0.35345083 2.53045912 1.23488900 +Si 1.30405080 1.42589611 1.14624769 28.08550000 -0.39034539 -1.66490600 1.53860390 +Si 0.12683562 2.78169596 2.67662845 28.08550000 -0.97095884 -0.58733688 0.08993153 +Si 1.36267640 4.12144818 4.16274573 28.08550000 1.30358759 -0.36227769 -2.28412687 +Si 2.65412381 0.10929058 2.91668272 28.08550000 -1.06290894 -1.58594665 -3.75326625 +Si 4.02918199 1.41193640 3.95317335 28.08550000 -0.41585433 -1.39211787 3.20492606 +Si 2.65898255 2.67935858 5.34838841 28.08550000 0.36470944 -0.19681949 1.21302691 +Si 3.97756407 3.89885832 6.82286191 28.08550000 0.70342759 2.29617404 -0.04835422 +Si 2.80168328 2.81105112 0.13401943 28.08550000 -1.19192947 -1.22438450 -1.19510298 +Si 4.05614410 4.00380009 1.45909856 28.08550000 1.11737853 1.19116199 -0.57009301 +Si 2.89065107 5.47288487 2.65189259 28.08550000 -1.65970800 -0.31919243 1.78931037 +Si 3.87401641 6.96683015 4.00835342 28.08550000 3.33762892 -0.48670494 0.54792804 +Si 5.23847765 2.65465105 2.74935821 28.08550000 4.35886903 0.98797363 -0.65589998 +Si 6.91669598 3.98279162 4.11609479 28.08550000 -1.25123042 0.05223325 -0.56400361 +Si 5.65115530 5.40251994 5.35884923 28.08550000 -2.14666388 0.70945245 1.22489821 +Si 6.91736352 6.80044853 6.94347159 28.08550000 -1.74255151 0.05223222 -1.77266736 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.2350019695195 stress="-0.017624036601108704 -0.01304334795287055 0.005422639237621671 -0.01304334795287055 -0.013040593479840944 -0.012783509330410862 0.005422639237621671 -0.012783509330410862 -0.008559984018345217" free_energy=-2462.2350019695195 pbc="T T T" +Si -0.09972678 0.02068351 0.04557743 28.08550000 1.85045454 2.63913811 -2.04646773 +Si 1.28208009 1.53026521 1.11650820 28.08550000 0.48466194 -1.14199942 1.50034409 +Si 0.10758289 2.66774233 2.68049153 28.08550000 -1.80654344 1.06399935 0.99510227 +Si 1.20869518 4.21830418 4.10361536 28.08550000 0.99500508 -2.25326001 -0.37885616 +Si 2.56258554 0.03325038 2.69936692 28.08550000 -1.27637426 0.31141407 -1.47272375 +Si 3.90306653 1.13909030 4.03424533 28.08550000 2.12306192 1.23184327 -0.63239907 +Si 2.79191164 2.64304212 5.14289159 28.08550000 -1.88663253 1.93540610 3.22928701 +Si 3.96593930 4.13806780 6.98896518 28.08550000 1.58558027 -1.78203594 -2.47885271 +Si 2.82142819 2.79937895 0.04900964 28.08550000 -0.77035572 -3.39809098 -2.32800224 +Si 4.09235805 4.11321131 1.01542672 28.08550000 -0.45088536 0.39430309 5.01779750 +Si 2.90465241 5.17779800 2.94479740 28.08550000 -0.48350314 1.37030360 -1.82631677 +Si 4.13829220 6.72098118 4.12816580 28.08550000 1.37173545 -0.14464486 0.19053880 +Si 5.19650192 3.10902363 2.80734171 28.08550000 0.66564394 -2.51126430 0.03383649 +Si 6.96012428 3.98183930 4.11428578 28.08550000 -0.31044939 -0.26813726 -1.92622392 +Si 5.65896637 5.18889975 5.33503890 28.08550000 -2.23081171 2.82911255 3.13762615 +Si 6.81514219 6.82802204 7.10387252 28.08550000 0.13941292 -0.27608788 -1.01468996 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2463.3602264173173 stress="-0.02627032744104831 0.008967646026727207 -0.001646256714029065 0.008967646026727207 -0.014955870393095061 0.019030654161561873 -0.001646256714029065 0.019030654161561873 -0.021276467838368947" free_energy=-2463.3602264173173 pbc="T T T" +Si -0.09075728 -0.12552688 0.01892316 28.08550000 0.23276299 1.70960617 -0.93533441 +Si 1.32707075 1.12563922 1.32778461 28.08550000 1.41302505 1.30534006 0.94591218 +Si 0.10913736 2.67319441 2.76779308 28.08550000 -0.41303332 0.13287667 -1.71883052 +Si 1.35123765 4.20076497 4.03967129 28.08550000 -2.38193010 -3.72627044 2.81813085 +Si 2.83919384 -0.10793155 2.91223934 28.08550000 -2.10646673 -0.03664953 -0.87669911 +Si 4.11950198 1.41699138 3.96853002 28.08550000 1.00882425 0.11075644 0.08531049 +Si 2.76627155 2.65760083 5.32359830 28.08550000 0.15312230 1.70413075 0.29394522 +Si 4.03774415 4.11817051 6.80433171 28.08550000 0.93949471 -1.07211375 -0.24688144 +Si 2.73975869 2.78385554 -0.08392631 28.08550000 -0.89169970 -2.05146055 0.97670268 +Si 4.10621442 3.97082419 1.34140456 28.08550000 -7.33309592 5.57419168 -5.04747343 +Si 2.66291236 5.25577298 2.88171048 28.08550000 3.22825060 3.51514997 -3.64740751 +Si 4.06889422 6.82238797 4.01542441 28.08550000 -0.26535687 -0.09786698 -0.02488879 +Si 5.23728226 2.97165352 2.45153627 28.08550000 8.13474222 -6.73147630 7.51940782 +Si 6.66204702 4.11052671 4.31055399 28.08550000 0.39830758 -0.35087690 -2.77632266 +Si 5.37039093 5.51704213 5.39753862 28.08550000 0.01746756 1.17801723 2.31725400 +Si 7.00270011 6.91863407 6.83248647 28.08550000 -2.13441463 -1.16335449 0.31717437 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2463.5368696572145 stress="-0.012662312517108107 -0.011550423570823 -0.0018904866559876438 -0.011550423570823 -0.019274884103520448 0.011678047487861507 -0.0018904866559876438 0.011678047487861507 -0.011663356965036929" free_energy=-2463.5368696572145 pbc="T T T" +Si -0.31029685 -0.00472207 -0.06895048 28.08550000 2.29185844 -0.38584930 0.49691633 +Si 1.46758366 1.22877925 1.23630735 28.08550000 -0.69261687 -0.38647074 0.17660676 +Si 0.20405999 2.62814604 2.72479063 28.08550000 -0.51230849 -0.79323596 -0.78256640 +Si 1.34768781 4.15242436 3.95103941 28.08550000 -0.35390875 0.55269153 1.48472335 +Si 2.82260447 -0.16836400 2.73225841 28.08550000 -2.15989529 2.34008693 0.55620160 +Si 4.11018987 1.49978115 3.87236052 28.08550000 -3.37994002 -6.02495670 2.89575117 +Si 2.83852258 2.74558719 5.18050749 28.08550000 -1.57952635 1.31078977 2.11226843 +Si 3.98504430 3.87448229 7.03816412 28.08550000 2.39901970 -1.12968563 -3.06849562 +Si 2.79241583 2.83786471 0.12946238 28.08550000 -0.88164592 -2.35145352 -2.02385539 +Si 4.06843010 3.92459307 1.53176444 28.08550000 -1.50856287 4.19956270 -1.74421347 +Si 2.65799585 5.57991890 2.70354278 28.08550000 -0.00312080 -0.82612474 -0.89653440 +Si 4.04588928 6.83699614 3.91744463 28.08550000 1.31336113 0.07463861 2.73746121 +Si 5.18566189 2.84460485 2.91987868 28.08550000 6.83238336 1.76039008 -2.25213361 +Si 6.83109817 3.96013477 4.05517377 28.08550000 -0.42455083 1.55200398 1.74947061 +Si 5.38613133 5.35610279 5.59630175 28.08550000 0.09846091 0.67552161 -0.59078370 +Si 6.87658172 7.01327055 6.78955410 28.08550000 -1.43900785 -0.56790886 -0.85081685 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2464.767180250134 stress="-0.014505973131592416 -0.033112438446594644 -0.0037892367310641117 -0.033112438446594644 -0.017701161845937726 -0.009416625130553313 -0.0037892367310641117 -0.009416625130553313 -0.003312712896941922" free_energy=-2464.767180250134 pbc="T T T" +Si -0.01109723 -0.05331162 0.30805493 28.08550000 1.90607624 1.88743883 -4.13980461 +Si 1.36259607 1.31345608 1.45040720 28.08550000 0.68024061 1.08966821 0.98253960 +Si -0.10441297 2.74478392 2.61411404 28.08550000 -0.45376268 0.16862040 0.46586846 +Si 1.33464999 4.18715250 4.02885704 28.08550000 -1.82599307 -1.71032016 1.07845229 +Si 2.71522982 -0.09571817 2.78640882 28.08550000 0.59738398 0.62629012 -0.41876868 +Si 4.20135713 1.31341005 4.02634730 28.08550000 -0.24226091 0.11107654 0.84572709 +Si 2.63557482 2.67000437 5.35985246 28.08550000 0.95735179 0.24944123 -2.41774453 +Si 3.85765491 4.08037855 6.57733664 28.08550000 2.25649574 0.63111017 1.06386359 +Si 2.91928291 2.75506306 0.26718413 28.08550000 -3.04290517 -5.08927186 -3.87639844 +Si 3.97706933 4.17688729 1.23797575 28.08550000 1.00557771 1.33836202 5.49439029 +Si 2.53769145 5.48349226 2.68572873 28.08550000 0.54329466 0.00436882 -1.42308347 +Si 4.00134237 6.57367527 3.97194866 28.08550000 1.57147931 2.20087661 1.13307872 +Si 5.54883068 2.91291580 2.82169285 28.08550000 -1.62881131 -1.52694652 -1.76084157 +Si 6.93303178 3.95700549 4.19619906 28.08550000 1.53317090 -0.02589152 0.47450994 +Si 5.60395345 5.37278313 5.27705991 28.08550000 -2.12101764 0.82255194 1.38336018 +Si 6.79684549 6.91762202 6.70043250 28.08550000 -1.73631993 -0.77737534 1.11485088 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2463.6015629526282 stress="-0.006387622955661019 -0.004035302988375762 -0.011694574326039152 -0.004035302988375762 -0.011925031902849692 0.025224545847473794 -0.011694574326039152 0.025224545847473794 -0.013735638840978703" free_energy=-2463.6015629526282 pbc="T T T" +Si -0.40735564 0.05801364 -0.03763144 28.08550000 3.50974088 -0.37459070 -0.31970819 +Si 1.26666958 0.97930261 1.16787208 28.08550000 1.10904147 2.89116766 1.41072263 +Si 0.07746394 2.75790850 2.81952611 28.08550000 -0.30000454 -0.67724142 -0.03816134 +Si 1.52145311 4.33986919 4.30675383 28.08550000 -3.09555314 -0.18490191 -1.04236737 +Si 2.77348403 0.03061417 2.75687658 28.08550000 -1.41749569 -1.41518812 -1.17967199 +Si 4.14199193 1.32628473 3.97243804 28.08550000 -1.70114158 3.19203918 -1.39540580 +Si 2.62832220 2.75181076 5.28651157 28.08550000 2.43975498 -0.75083076 1.19184514 +Si 4.10509752 4.13598030 6.74911276 28.08550000 -0.31220854 -1.80291844 1.15136852 +Si 2.66640877 2.86063954 0.00329535 28.08550000 -0.86312395 -2.81034787 -0.67973822 +Si 4.09743123 4.09364948 1.22452261 28.08550000 -1.31615643 -2.00480352 2.47554679 +Si 2.71220509 5.27162260 2.67982083 28.08550000 1.07587810 1.84790632 0.15225944 +Si 4.05230838 6.56236134 4.30195134 28.08550000 -0.32366126 1.96459635 -1.71263724 +Si 5.48166700 2.78855196 2.64836183 28.08550000 -1.30565373 -1.23033301 -1.06349104 +Si 6.69767373 3.99196681 3.96432671 28.08550000 1.67209275 2.46736142 1.98311858 +Si 5.50094603 5.41310285 5.57015956 28.08550000 1.55534307 0.41703961 -0.29497880 +Si 6.99383310 6.94792152 6.89570222 28.08550000 -0.72685214 -1.52895506 -0.63870135 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.3151861613046 stress="-0.001231249444234789 -0.002224696050246751 -0.011537569363351497 -0.002224696050246751 -0.0022724402494266236 -0.025593645233441268 -0.011537569363351497 -0.025593645233441268 -0.005974452001219815" free_energy=-2462.3151861613046 pbc="T T T" +Si 0.17082354 0.04291067 -0.05569712 28.08550000 -2.44121408 -0.35496701 -0.18640678 +Si 1.40470979 1.30329331 1.39118167 28.08550000 0.75620539 0.23100899 0.27797224 +Si 0.30908693 2.82336876 2.85382006 28.08550000 -3.38174005 -2.37582732 -1.57399822 +Si 1.47504522 4.12058164 4.07615673 28.08550000 1.62443889 1.37824060 2.39925419 +Si 2.79314288 -0.33975391 2.80145611 28.08550000 0.42312413 4.34129245 -0.71928307 +Si 3.99329586 1.44937832 4.06051810 28.08550000 2.25148852 -0.83805749 -0.23945223 +Si 2.88892274 2.74858428 5.55284812 28.08550000 -2.41224057 -0.83449857 -0.24415015 +Si 4.07836783 4.06490689 6.94264522 28.08550000 3.12132639 -0.80644501 -0.59685819 +Si 2.51631877 2.81571349 -0.22778279 28.08550000 2.49085642 -2.23362681 3.96256279 +Si 3.93218921 4.16689183 1.43190787 28.08550000 2.40980574 -0.92617305 -1.96957915 +Si 2.77520802 5.49071774 2.72994368 28.08550000 -1.22513681 1.81693918 0.49526619 +Si 4.04249126 6.80534757 4.35979335 28.08550000 -0.77716965 2.02406751 -3.22482614 +Si 5.66983863 3.06303175 2.87415099 28.08550000 -4.25805813 -4.09067160 -3.82592409 +Si 6.90558684 4.17658083 4.10201931 28.08550000 -1.07241225 2.70385175 1.97281642 +Si 5.45425187 5.56503903 5.41380793 28.08550000 -0.60891512 -2.96655704 0.65584907 +Si 6.64091886 6.75360607 6.74342901 28.08550000 3.09964119 2.93142368 2.81675685 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2464.4415635295445 stress="-0.01446281972079522 0.022016502925656975 -0.03208134737584471 0.022016502925656975 -0.011046355006404733 0.016825239422522374 -0.03208134737584471 0.016825239422522374 -0.022958532701782913" free_energy=-2464.4415635295445 pbc="T T T" +Si 0.17809946 0.14854572 -0.00426497 28.08550000 -1.63471225 -1.77535648 -0.82079048 +Si 1.44889727 1.34282261 1.42785614 28.08550000 -5.33828217 6.06719196 -5.10515048 +Si -0.05590784 2.59376308 2.80976993 28.08550000 -0.28651628 0.12789670 0.28230095 +Si 1.41435654 4.05730579 3.99684937 28.08550000 -0.59949409 0.76245549 -0.19722598 +Si 2.55381629 0.30273611 2.58687497 28.08550000 6.20203295 -6.67270551 5.90054899 +Si 4.03731100 1.40220737 4.07522084 28.08550000 0.94267413 0.05808919 -0.24253910 +Si 2.65154448 2.72995905 5.40781641 28.08550000 0.20165162 -0.28462497 -0.06405646 +Si 4.00666560 3.96992671 6.80795296 28.08550000 -0.32362115 0.48978152 1.17184710 +Si 2.54009929 2.94549680 -0.02593322 28.08550000 3.47854003 -3.97042728 2.76604262 +Si 4.08843057 4.05718932 1.27699831 28.08550000 1.63057020 0.47652980 0.57279601 +Si 2.81118988 5.48757365 2.65860995 28.08550000 -0.41367558 -1.06547182 -0.11999595 +Si 3.97658705 6.63173389 4.26596829 28.08550000 0.14107566 1.69419446 -0.32509773 +Si 5.61577610 2.56508649 2.66208435 28.08550000 -1.94778005 1.91371088 1.03016620 +Si 6.86834307 4.10251515 4.14043881 28.08550000 -2.86872862 2.50841011 -4.37011195 +Si 5.39840629 5.26816181 5.50752520 28.08550000 -0.11149743 0.17398295 -0.10591119 +Si 6.77598495 6.70457646 6.71583264 28.08550000 0.92776302 -0.50365725 -0.37282255 +16 +Lattice="5.43096 5.43096 0.0 5.43096 0.0 5.43096 0.0 5.43096 5.43096" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2463.0666878361085 stress="-0.020557550377641252 -0.007166220665363554 0.015242335588174291 -0.007166220665363554 -0.0041133463908813225 -0.01158714987788444 0.015242335588174291 -0.01158714987788444 -0.015925444899517083" free_energy=-2463.0666878361085 pbc="T T T" +Si 0.40735564 -0.05801364 0.03763144 28.08550000 -2.35443909 0.20752685 0.25114895 +Si 1.44881042 1.73617739 1.54760792 28.08550000 1.94600676 -4.40018562 -1.82536520 +Si -0.07746394 2.67305150 2.61143389 28.08550000 -1.41863160 1.71065184 -1.61598665 +Si 1.19402689 3.80657081 3.83968617 28.08550000 3.98336636 3.13536924 3.40273234 +Si 2.65747597 -0.03061417 2.67408342 28.08550000 0.41912555 1.26564917 0.80813833 +Si 4.00444807 1.38919527 4.17400196 28.08550000 1.42742554 -1.76466763 -0.21348126 +Si 2.80263780 2.67914924 5.57540843 28.08550000 -2.86116649 -0.97502041 -1.30269053 +Si 4.04134248 4.01045970 6.82828724 28.08550000 0.05517562 2.38699285 -0.88344877 +Si 2.76455123 2.57032046 -0.00329535 28.08550000 0.71720382 2.87112463 -0.17192812 +Si 4.04900877 4.05279052 1.49095739 28.08550000 0.78564324 0.67535937 -1.09062081 +Si 2.71875491 5.59029740 2.75113917 28.08550000 -1.50242951 -2.08310672 -1.26492566 +Si 4.09413162 7.01503866 3.84448866 28.08550000 -1.72272419 -3.16878587 3.34591559 +Si 5.38025300 2.64240804 2.78259817 28.08550000 0.69085387 0.43399449 0.14373341 +Si 6.87972627 4.15447319 4.18211329 28.08550000 -0.52345320 -1.72267406 -0.85680186 +Si 5.36097397 5.44881715 5.29176044 28.08550000 -1.45327490 -0.66042460 -0.52021129 +Si 6.58356690 6.62947848 6.68169778 28.08550000 1.81131798 2.08819673 1.79379128 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2464.58870350722 stress="0.0077510871053169915 -0.02132696651057843 -0.0029445316686509825 -0.02132696651057843 0.0130139669072214 -0.0011981957678794926 -0.0029445316686509825 -0.0011981957678794926 0.008912556566135045" free_energy=-2464.58870350722 pbc="T T T" +Si -0.15507614 0.00296347 0.12528567 28.08550000 0.37868878 -0.19885863 -3.68917097 +Si 1.22454028 1.13386656 1.28835607 28.08550000 2.38306318 2.74585149 3.37917461 +Si 0.01226721 3.07468363 2.86989270 28.08550000 0.17370835 -2.69446568 -0.78498221 +Si 1.46239225 4.34216619 4.04489136 28.08550000 -0.43269094 0.18827931 1.26528561 +Si 2.72840363 -0.18906114 2.86354043 28.08550000 1.04347243 0.97023584 -3.64864344 +Si 4.03254813 1.16918646 4.09243095 28.08550000 0.52580473 2.62374517 0.41414969 +Si 2.55332768 2.75385721 5.33341773 28.08550000 1.57189326 -0.83148704 1.25966801 +Si 4.23012620 4.03678682 6.82566456 28.08550000 -1.77807259 0.98624893 -1.42790634 +Si 2.79883593 2.67221697 0.23015529 28.08550000 -1.74885406 -0.18303683 -1.29628257 +Si 4.16380534 4.15194995 1.30637406 28.08550000 0.33029393 -2.41264475 2.28143159 +Si 2.98468614 5.46410925 2.72197497 28.08550000 -1.21557873 1.84297546 -0.14059460 +Si 4.05324349 7.08120344 4.10610545 28.08550000 1.10464695 -0.33432028 -0.08094501 +Si 5.64155357 2.81097943 2.87151613 28.08550000 -1.33539805 -1.51121291 -1.13438947 +Si 6.96607046 4.15724390 4.13352870 28.08550000 -1.03155280 -1.50891254 2.81468609 +Si 5.45961165 5.56723404 5.33355420 28.08550000 0.20331306 0.02700172 1.21223373 +Si 6.89386243 6.82081207 6.90350999 28.08550000 -0.17273751 0.29060099 -0.42371471 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.8049055094884 stress="0.018213493829444823 -0.018159322526529197 -0.0025359515025924584 -0.018159322526529197 0.006743868134156989 0.010097898126543032 -0.0025359515025924584 0.010097898126543032 0.012762391703850531" free_energy=-2461.8049055094884 pbc="T T T" +Si 0.24578081 -0.00032550 0.14990377 28.08550000 -1.96747033 0.33811369 -1.66846312 +Si 1.20999179 1.60278115 1.44343413 28.08550000 1.07108736 -1.24102802 -0.36192107 +Si 0.02058784 2.66997573 2.98273229 28.08550000 -0.26158429 1.43588447 -1.32365711 +Si 1.27565426 4.03094791 4.17568366 28.08550000 1.85077619 1.51735193 1.06799947 +Si 2.55536260 0.17644497 2.75503012 28.08550000 2.04673770 0.24385550 -1.46941732 +Si 4.13958129 1.24743835 3.99601040 28.08550000 1.30102549 1.81035896 1.18580587 +Si 2.69188943 2.88953128 5.57786565 28.08550000 1.26000894 -1.99447797 0.98773297 +Si 4.36719665 4.18102056 7.10811009 28.08550000 -2.58114611 0.55215185 -1.17607939 +Si 2.67814649 2.55925422 -0.01887550 28.08550000 0.96463058 2.27249443 -0.39921904 +Si 4.07597506 4.29433510 1.12409166 28.08550000 0.04009327 -1.52468549 1.87544052 +Si 2.83652213 5.41815207 2.96967242 28.08550000 -1.68433711 -1.90438471 -2.65264437 +Si 4.07499580 6.90336969 3.95896839 28.08550000 -1.73179376 1.09921652 1.16006913 +Si 5.71660198 2.86037310 2.70058205 28.08550000 -0.84991233 -0.54771387 -0.55690428 +Si 7.14087089 4.26272976 4.10087977 28.08550000 -2.75809225 -1.78684776 1.39325533 +Si 5.08598650 5.56701639 5.31580711 28.08550000 3.38474053 -2.37252551 1.97864357 +Si 6.93505474 6.38715349 6.71030224 28.08550000 -0.08476361 2.10223624 -0.04064143 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.5769468223148 stress="-0.0004967233030059812 -0.023338649979868824 -0.0030335929632749757 -0.023338649979868824 0.018465987190492226 0.021644649066659888 -0.0030335929632749757 0.021644649066659888 0.007019315437117793" free_energy=-2459.5769468223148 pbc="T T T" +Si -0.02637544 -0.01446257 0.08560600 28.08550000 4.38226298 1.63608470 -0.66435428 +Si 1.49692327 1.58551224 1.24418529 28.08550000 -2.87634320 -3.90025596 3.11213855 +Si -0.04916256 2.47711566 2.77578920 28.08550000 0.66142810 3.46298357 -1.17532374 +Si 1.28197477 4.30257205 4.09328551 28.08550000 0.36365811 -1.81073717 -0.14743014 +Si 2.47218302 -0.16255746 2.81633497 28.08550000 2.43715482 2.27307010 -1.33393946 +Si 4.52873148 1.19304359 4.20023131 28.08550000 -3.45474421 2.75828894 -2.71004116 +Si 2.52843160 2.68202874 5.43002145 28.08550000 1.00758909 -0.25878179 0.88211051 +Si 4.16825930 4.36297120 7.02448194 28.08550000 -0.08750878 -1.46111008 -0.31006192 +Si 2.80206721 2.76450746 0.13615698 28.08550000 2.14661117 2.13988542 -3.17326601 +Si 4.29309628 4.30429408 1.20127222 28.08550000 -2.72306509 -2.12664321 1.95122687 +Si 3.00175447 5.43653406 2.78984674 28.08550000 -1.31922941 0.00490669 0.34518396 +Si 4.04670569 7.00740775 4.08997140 28.08550000 0.31921994 -0.94262657 1.82031710 +Si 5.55875870 3.24472252 2.75335192 28.08550000 -3.60741426 -4.79748585 -2.67852509 +Si 6.97722476 3.86611593 3.97821498 28.08550000 3.06005109 2.35792679 5.84650338 +Si 5.54080725 5.68111503 5.52170284 28.08550000 0.39576939 -0.55114886 0.39867422 +Si 6.91080860 6.80126814 7.39173567 28.08550000 -0.70543948 1.21564327 -2.16321252 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.9373656002026 stress="0.014742857812138703 0.014881499621295641 -0.015608680501112165 0.014881499621295641 0.0061277843332013275 0.013967932733142313 -0.015608680501112165 0.013967932733142313 0.013068138210137026" free_energy=-2462.9373656002026 pbc="T T T" +Si -0.30105592 -0.11161706 0.09045355 28.08550000 2.39327817 -1.27313339 -1.00645883 +Si 1.21591803 1.16419115 1.16471704 28.08550000 2.16887486 0.89105744 1.50069890 +Si 0.37224712 2.69077531 2.71853710 28.08550000 -1.49781721 -0.29314252 0.55862023 +Si 1.54882737 3.97298513 4.35173374 28.08550000 -4.35587703 4.12560904 -3.20779516 +Si 2.87397276 0.12612609 2.63775666 28.08550000 0.06533507 -1.43214789 0.01653065 +Si 4.23394798 1.39714641 4.36604235 28.08550000 -1.43653214 0.60699348 -3.14327487 +Si 2.69655114 2.70210099 5.38199044 28.08550000 3.85188888 -3.10687319 5.06370944 +Si 4.60874808 3.93619721 6.71434547 28.08550000 -1.70889963 1.48459222 -0.25371877 +Si 2.69575974 2.80683715 0.19222098 28.08550000 -1.37869337 0.45722750 -1.55838905 +Si 3.95634231 4.30520968 1.52408317 28.08550000 -0.84268959 -1.99105249 0.96457530 +Si 2.59672266 5.54256166 2.91014502 28.08550000 0.70630594 0.32961876 1.00999950 +Si 3.95769831 7.16222379 4.10045537 28.08550000 1.51891516 -0.48877365 0.00683759 +Si 5.28436797 2.66453004 2.63864237 28.08550000 1.48467758 0.38122234 0.77457541 +Si 6.87073106 4.08355514 3.88522701 28.08550000 0.23955328 0.68155444 0.98611446 +Si 5.54135000 5.83204032 5.45590824 28.08550000 -1.04875579 -2.35473297 -1.78061207 +Si 6.89806965 6.77533524 6.91793975 28.08550000 -0.15956420 1.98198112 0.06858803 +16 +Lattice="6.0059236251182 6.0059236251182 -3.2607472454298e-17 6.0059236251182 1.6303736227149e-17 6.0059236251182 -4.7253940824215e-17 6.0059236251182 6.0059236251182" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2415.569864701614 stress="-0.056663182849743296 -0.06691808593897398 0.0640451705690928 -0.06691808593897398 -0.12988442123813698 0.09321779442567144 0.0640451705690928 0.09321779442567144 -0.023289069465335883" free_energy=-2415.569864701614 pbc="T T T" +Si 0.61407302 0.39659172 1.05001454 28.08550000 -3.51180419 0.25831359 -2.94754604 +Si 2.57217708 0.89219138 2.03499194 28.08550000 49.96527899 72.64001302 -48.41893735 +Si -0.05772659 2.83029796 2.67513452 28.08550000 -0.31654290 -0.42550523 0.66662585 +Si 1.35705016 4.99801573 4.96038619 28.08550000 -0.91782365 -0.52514010 0.91727832 +Si 1.95721813 0.02030020 2.63136934 28.08550000 -49.05419292 -71.57511867 51.44208643 +Si 4.62234292 0.86008346 4.12097348 28.08550000 2.63176984 -1.92521373 -2.72187132 +Si 3.54041671 2.18873516 5.26513302 28.08550000 -2.23884769 2.44173730 2.78283526 +Si 3.94611768 5.23685508 7.60417903 28.08550000 2.05316931 -1.37952949 -0.23263804 +Si 2.77888079 2.56547763 -0.27571697 28.08550000 0.36265281 -0.00570939 0.68155367 +Si 4.29908692 4.86671142 1.21881141 28.08550000 0.34965691 -0.34543105 0.92283859 +Si 2.62186960 6.00691871 3.42454347 28.08550000 1.41951246 1.07734749 -1.57567587 +Si 4.96452301 7.63995188 4.90164198 28.08550000 -4.43115456 5.91169087 -4.18432660 +Si 5.96632468 2.89378101 2.77682520 28.08550000 -0.28007720 0.19625359 0.04165984 +Si 7.06683114 4.85887877 4.88459300 28.08550000 5.71212853 -7.74672059 -5.53116426 +Si 6.02030491 6.20069691 5.69173437 28.08550000 -1.30988551 1.79506989 7.76707293 +Si 7.78974608 7.60374924 7.09462171 28.08550000 -0.43384023 -0.39205749 0.39020861 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.7471608870783 stress="0.015131238509313439 0.01241349178676685 0.022716139075177413 0.01241349178676685 0.01453719049259464 -0.02185123454388049 0.022716139075177413 -0.02185123454388049 0.0030510379591291597" free_energy=-2462.7471608870783 pbc="T T T" +Si 0.30105592 0.11161706 -0.09045355 28.08550000 -1.94705191 0.81841786 1.43245231 +Si 1.53659188 1.58831876 1.58779287 28.08550000 -1.47496781 -0.10299968 -1.17076518 +Si -0.37224712 2.81424451 2.78648273 28.08550000 1.58789992 0.07231279 -0.16894976 +Si 1.20368255 4.28454461 3.90579600 28.08550000 1.67525495 -1.29275168 -0.31628014 +Si 2.63104707 -0.12612609 2.86726317 28.08550000 -3.39387335 4.23776544 3.34451691 +Si 4.02358176 1.35536351 3.89148739 28.08550000 1.95848304 1.25240618 2.31739412 +Si 2.80846869 2.80291883 5.62804921 28.08550000 -1.28565389 -0.65932957 -2.66769124 +Si 3.64878166 4.32133253 7.04820409 28.08550000 5.06218091 -3.81343624 -4.16563571 +Si 2.80926009 2.69818267 -0.19222098 28.08550000 1.48774568 -1.40566990 1.76204716 +Si 4.30118743 3.95232006 1.22842675 28.08550000 0.37649563 1.54147017 0.01781466 +Si 2.90829717 5.46747799 2.59487481 28.08550000 -0.64519467 -0.48706001 -0.37730835 +Si 4.29983143 6.60032578 4.15707437 28.08550000 -1.41102731 0.85663371 -0.58591866 +Si 5.72567168 2.84048979 2.86637745 28.08550000 -1.74873039 -0.89372547 -0.98112344 +Si 6.89181850 4.17397460 4.37230272 28.08550000 1.28866928 -1.58052471 -1.97397291 +Si 5.46868965 5.17799933 5.55413141 28.08550000 -1.88860354 2.92486069 3.28017865 +Si 6.86447991 6.98721433 6.84460982 28.08550000 0.35837347 -1.46836959 0.25324183 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.2345815795197 stress="0.013625459919794383 0.02170157484260512 0.015290997945030702 0.02170157484260512 0.014122183222800363 -0.01158898619323751 0.015290997945030702 -0.01158898619323751 0.0013148017927995658" free_energy=-2461.2345815795197 pbc="T T T" +Si -0.24578081 0.00032550 -0.14990377 28.08550000 3.03548908 -2.04783581 2.37922735 +Si 1.54251812 1.14972876 1.30907578 28.08550000 -1.12868162 1.23220528 -0.16553559 +Si -0.02058784 2.83504410 2.52228754 28.08550000 0.57400726 -0.97609333 0.72634949 +Si 1.47685565 4.22658183 4.08184608 28.08550000 -1.30464843 -0.39357290 -0.62544166 +Si 2.94965723 -0.17644497 2.74998970 28.08550000 -1.99120650 0.83275408 0.99264481 +Si 4.11794845 1.50507157 4.26151934 28.08550000 -0.04633642 -3.01176423 -2.39079937 +Si 2.81313040 2.61548855 5.43217400 28.08550000 -3.82013062 2.43316961 0.51269879 +Si 3.89033309 4.07650918 6.65443947 28.08550000 3.44000176 0.83860308 0.91333656 +Si 2.82687333 2.94576561 0.01887550 28.08550000 -0.52571757 -1.96612693 -0.22407318 +Si 4.18155467 3.96319464 1.62841825 28.08550000 -2.54650975 3.95499012 -3.44877540 +Si 2.66849769 5.59188758 2.53534741 28.08550000 0.82474920 0.55283114 1.76975533 +Si 4.18253394 6.85917988 4.29856135 28.08550000 0.40264118 -0.03165594 -0.89420010 +Si 5.29343767 2.64464673 2.80443777 28.08550000 0.95094846 -0.04650406 2.44197127 +Si 6.62167867 3.99479998 4.15664997 28.08550000 2.56213023 0.35150065 -0.51513799 +Si 5.92405315 5.44302326 5.69423254 28.08550000 -2.68592524 1.43946242 0.45083779 +Si 6.82749483 7.37539608 7.05224733 28.08550000 2.25918923 -3.16196319 -1.92285860 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.4492635021597 stress="-0.0073994327152037 -0.0037754643659160705 -0.03305734898600249 -0.0037754643659160705 0.015554509198196538 -0.007060632532561914 -0.03305734898600249 -0.007060632532561914 -0.015526046310223923" free_energy=-2460.4492635021597 pbc="T T T" +Si 0.10945875 0.20116410 0.09760266 28.08550000 -3.37121756 -1.90367818 -1.14868069 +Si 1.51931320 1.11754667 1.33938531 28.08550000 1.04836318 3.92498560 0.66258510 +Si 0.08191169 2.79280711 2.44519489 28.08550000 -0.81677724 -0.31110168 1.66746553 +Si 1.24993563 4.31405934 4.20953129 28.08550000 -2.15097870 -1.89312585 -0.80369958 +Si 2.85241402 0.44165280 2.96122497 28.08550000 -5.49287925 -6.56827424 -5.64389968 +Si 4.00190853 1.28620295 4.18595211 28.08550000 6.47810412 6.25474545 6.66013127 +Si 2.55799755 2.95951814 5.38476976 28.08550000 1.69689309 -1.69553426 2.02294702 +Si 3.82131915 4.19840964 7.11746860 28.08550000 1.40673948 -0.31588959 -1.60305040 +Si 2.67068103 2.62642642 -0.13393523 28.08550000 1.53782691 0.68085665 0.04623383 +Si 4.22220946 4.28470558 1.48542302 28.08550000 -0.76414265 -1.74954260 -0.59364611 +Si 2.52485755 5.37033403 2.81413182 28.08550000 4.30524224 -0.72086918 0.65053460 +Si 4.19794401 6.71655803 4.04058669 28.08550000 0.28966073 0.58487582 0.14456747 +Si 5.48054269 2.54572529 2.69241029 28.08550000 0.29889537 1.10454667 -0.04924460 +Si 6.94682007 4.21392810 3.98529727 28.08550000 0.85401838 -2.18926808 -0.85724332 +Si 5.62877441 5.19868345 5.38577383 28.08550000 -2.07570709 2.27848253 2.35648980 +Si 7.18411052 6.78247660 7.03938098 28.08550000 -3.24404128 2.51879120 -3.51149026 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.4701250834078 stress="0.003357702623092187 -0.0031997795027279936 -0.016813303372727406 -0.0031997795027279936 -0.004137218490471259 0.0028315982744370537 -0.016813303372727406 0.0028315982744370537 0.00594323464021759" free_energy=-2461.4701250834078 pbc="T T T" +Si -0.29973764 0.02577302 -0.40288252 28.08550000 5.01973637 -3.40007665 3.39441353 +Si 1.33401087 1.46388053 1.22050299 28.08550000 -0.28154608 -0.57344907 1.00678253 +Si 0.00392604 2.80739067 2.87683061 28.08550000 0.25860567 -0.72910571 -0.61896994 +Si 1.75341790 4.17630477 4.03905532 28.08550000 -3.21417149 -0.41767904 0.30170610 +Si 2.86820205 0.16244667 3.15592741 28.08550000 -4.72469869 -4.66501876 -4.86615693 +Si 4.06582342 1.43058418 4.15907476 28.08550000 0.13058993 5.63240608 0.75040421 +Si 2.66137626 2.71368033 5.60576754 28.08550000 0.36263301 0.44425345 -1.11248290 +Si 3.98546488 3.96925427 6.88365332 28.08550000 2.03298306 2.50964784 2.03184201 +Si 2.76896334 2.90236947 0.02775774 28.08550000 0.54347541 -2.33583484 -0.48013500 +Si 4.29855825 4.06332553 1.32018721 28.08550000 -0.82774788 1.26748442 -1.03502790 +Si 2.73328223 5.45775534 2.48416206 28.08550000 1.72131343 0.54649208 0.53008947 +Si 4.23312023 6.59235447 4.08507819 28.08550000 -0.63600992 2.10490299 -0.07374978 +Si 5.45398479 2.65143629 2.73442771 28.08550000 -1.20290217 1.61299388 1.50855156 +Si 6.73079217 3.91447640 4.20794603 28.08550000 1.03784274 2.65383479 0.49636123 +Si 5.65524298 5.66376143 5.66388755 28.08550000 -1.92772442 -2.97378338 -1.13079404 +Si 6.80377047 7.05540490 6.98882234 28.08550000 1.70762128 -1.67706886 -0.70283418 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.1525306868302 stress="-0.0016150393530268408 -0.039595549800615415 -0.01697948991218043 -0.039595549800615415 -0.0013919270376285906 -0.020215077564293325 -0.01697948991218043 -0.020215077564293325 0.0006950453611377593" free_energy=-2461.1525306868302 pbc="T T T" +Si -0.10945875 -0.20116410 -0.09760266 28.08550000 1.47691774 0.99632329 -0.41251473 +Si 1.23319671 1.63496324 1.41312460 28.08550000 0.11929353 -2.59212549 0.04247719 +Si -0.08191169 2.71221271 3.05982493 28.08550000 1.51929312 1.60953678 -3.13133158 +Si 1.50257428 3.94347040 4.04799845 28.08550000 1.30044339 1.73810505 1.44831473 +Si 2.65260580 -0.44165280 2.54379485 28.08550000 0.33369910 2.02531784 0.14323358 +Si 4.25562121 1.46630697 4.07157763 28.08550000 -0.77057915 -2.04321168 -0.36224915 +Si 2.94702227 2.54550169 5.62526989 28.08550000 -1.26897977 0.78445153 -1.01009771 +Si 4.43621059 4.05912009 6.64508096 28.08550000 -1.63318450 -1.17123415 2.27514961 +Si 2.83433880 2.87859341 0.13393523 28.08550000 -4.88074408 -3.69372850 -3.05272653 +Si 4.03532028 3.97282415 1.26708690 28.08550000 4.17401494 4.75439699 4.24625754 +Si 2.98016227 5.63970563 2.69088801 28.08550000 -2.42168963 -1.03083469 -0.60362919 +Si 4.05958573 7.04599153 4.21694305 28.08550000 -1.56397015 -1.54922204 0.74268910 +Si 5.52949696 2.95929453 2.81260954 28.08550000 -0.74792696 -1.47017965 -1.18441593 +Si 6.81572949 4.04360164 4.27223247 28.08550000 0.78128908 2.17216176 0.35366809 +Si 5.38126524 5.81135620 5.62426582 28.08550000 -1.64708363 -3.78229324 -3.93071916 +Si 6.57843905 6.98007296 6.72316858 28.08550000 5.22920723 3.25253621 4.43589362 +16 +Lattice="5.5050198252577 5.5050198252577 7.2182755466761e-18 5.5050198252577 2.8873102186705e-17 5.5050198252577 -2.1654826640028e-17 5.5050198252577 5.5050198252577" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.206667079795 stress="-0.012195888417427813 0.005875290972153924 -0.02803227202232091 0.005875290972153924 -0.002498307037854482 -0.01485854567938224 -0.02803227202232091 -0.01485854567938224 -0.023734375938455846" free_energy=-2460.206667079795 pbc="T T T" +Si 0.15772951 -0.04884908 -0.13188092 28.08550000 -1.98443087 0.04420986 0.00571196 +Si 1.07588358 1.49799296 1.29787509 28.08550000 2.64969712 -1.52963461 0.13537706 +Si -0.03258022 2.76509442 2.71848349 28.08550000 -1.56755401 1.18177901 1.15023183 +Si 1.46521606 3.75729604 4.41270646 28.08550000 -7.80907601 6.81067733 -10.45709034 +Si 2.89853921 0.20569163 2.84869269 28.08550000 -4.23885045 -4.06449340 -4.45957991 +Si 3.94536905 1.37892204 4.09156132 28.08550000 4.49636879 3.76537949 3.42791964 +Si 2.56798482 2.96321091 5.63261086 28.08550000 7.07195746 -7.71347288 5.85100795 +Si 4.00190941 4.09865527 6.68368133 28.08550000 3.08244154 2.93746706 3.03854792 +Si 2.74591347 2.65787251 0.03679593 28.08550000 -2.79358684 2.05069179 1.89678068 +Si 4.04249258 4.17293954 1.17052634 28.08550000 2.14177389 -0.59151390 1.00093610 +Si 2.81357798 5.22566263 2.77452379 28.08550000 -0.33779796 1.69055789 1.01323883 +Si 4.03383017 7.13044268 4.26443744 28.08550000 2.52815979 -3.96068666 -3.10995388 +Si 5.74149331 2.70487887 2.80174609 28.08550000 -1.57338038 0.05999181 -0.75211631 +Si 6.96413517 4.16153010 4.18491768 28.08550000 0.41509560 0.30496600 -0.74813213 +Si 5.54620542 5.52500991 5.44620111 28.08550000 -0.60588328 0.75509236 0.20479325 +Si 7.08249876 6.85384780 6.81731955 28.08550000 -1.47493465 -1.74101117 1.80232709 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.866783132874 stress="0.006695205777300582 0.00779791314682033 0.024039204287065803 0.00779791314682033 0.017835212866711983 0.0002607567801362267 0.024039204287065803 0.0002607567801362267 0.007916355487093475" free_energy=-2460.866783132874 pbc="T T T" +Si -0.31957421 -0.04881529 -0.04116242 28.08550000 2.29749790 0.63802181 -2.10069229 +Si 1.09423163 1.33204018 1.14302925 28.08550000 1.62190610 0.02195311 1.22910505 +Si -0.15078467 2.53608131 2.69166139 28.08550000 0.07027262 1.50728504 0.83801995 +Si 1.37517957 4.10308257 4.29773809 28.08550000 0.02771443 -0.45362409 -1.30305614 +Si 2.60624616 -0.18630236 2.85600107 28.08550000 0.39921724 2.63752757 -0.95681263 +Si 4.32635555 1.67582041 4.10272459 28.08550000 -2.70443307 -5.16004918 1.51390768 +Si 2.94687228 2.55775497 5.50025150 28.08550000 -2.06545944 3.03395182 2.02612722 +Si 4.16663496 4.76369214 6.81700761 28.08550000 -0.00370445 -2.65173369 -0.14250493 +Si 2.80595146 2.72097732 -0.11233307 28.08550000 -0.14307315 -0.85149253 1.45146099 +Si 4.10092017 4.22669352 1.34328623 28.08550000 0.00852912 -3.04596170 -0.22734671 +Si 2.96678224 5.51895653 2.63917643 28.08550000 -2.25935712 0.99807961 3.42225087 +Si 4.27044420 6.61337905 4.52228488 28.08550000 -3.13445933 2.18450074 -3.76399392 +Si 5.47457889 2.79119895 2.84135311 28.08550000 2.55704561 2.97891299 -3.35903001 +Si 6.87523975 4.07724101 4.27590640 28.08550000 0.33501165 -0.67033646 -0.72429800 +Si 5.92565261 5.76213545 5.47086811 28.08550000 1.24717168 -1.67832793 1.98252697 +Si 6.95678770 6.97758249 7.07372510 28.08550000 1.74612020 0.51129291 0.11433593 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.9407195651443 stress="0.008777587387684253 0.009997818939800607 0.008924492615930013 0.009997818939800607 0.022261651025292088 -0.015331396882798288 0.008924492615930013 -0.015331396882798288 0.019254684634636657" free_energy=-2461.9407195651443 pbc="T T T" +Si 0.12952669 -0.10746010 0.10237086 28.08550000 -2.01482773 -1.61855981 -1.96865047 +Si 1.41604089 1.09736985 1.20879766 28.08550000 2.67435245 4.37874725 2.49491825 +Si 0.10867239 2.97176763 2.50151398 28.08550000 -0.98183512 -1.04843852 0.19214805 +Si 1.20357083 3.98277618 4.30103518 28.08550000 2.45675999 0.03340043 -1.53370312 +Si 2.79796344 0.05569105 2.81014679 28.08550000 -2.26175005 1.23583902 3.18416749 +Si 4.15538929 1.17563735 4.49568842 28.08550000 1.03466666 0.68425642 -2.55194712 +Si 2.99432345 2.75209062 5.54053570 28.08550000 -2.06389672 1.30676445 0.58172931 +Si 3.88796575 4.48988589 6.94729242 28.08550000 2.10009271 -3.57120567 -0.89459502 +Si 2.90509464 2.78616388 -0.04777193 28.08550000 -0.17712741 -0.67014286 1.28630541 +Si 4.19854609 4.30337334 1.34842156 28.08550000 -0.58075100 -1.80103820 1.84217225 +Si 2.75643086 5.63331234 2.64857259 28.08550000 -0.37292822 -0.04163284 1.05444976 +Si 4.24907181 7.09926192 4.08522184 28.08550000 0.16554433 -0.68178533 -1.56951807 +Si 5.47703442 2.80373970 2.95809271 28.08550000 0.67424171 -0.22320312 -0.48379085 +Si 7.01242432 4.29113846 4.58863343 28.08550000 0.70528393 -0.91237291 -2.90133381 +Si 5.19539734 5.24468753 5.31585959 28.08550000 0.12349137 2.97146759 0.12017619 +Si 7.04473623 6.95275277 6.72777761 28.08550000 -1.48131715 -0.04209564 1.14747150 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.8115075870896 stress="0.0026883656768974355 -0.0071946835533361715 -0.026205138246014243 -0.0071946835533361715 -0.009389998557933769 0.01044587988595018 -0.026205138246014243 0.01044587988595018 -0.0019731208468758846" free_energy=-2459.8115075870896 pbc="T T T" +Si 0.16756323 -0.14375053 0.08010832 28.08550000 0.43246623 1.73895377 -1.69734895 +Si 1.72560562 1.42077917 1.04266790 28.08550000 -2.77171936 -3.56730479 4.39988558 +Si 0.13908783 2.75026885 2.85289815 28.08550000 -0.77159525 -1.56940006 -1.09075116 +Si 1.49954800 4.14886696 4.00236015 28.08550000 -1.11956397 -1.02465993 2.13311699 +Si 2.69761350 -0.17575283 2.85697066 28.08550000 1.52028556 1.41607695 -0.40559460 +Si 4.23513864 1.37229639 4.32459523 28.08550000 -0.93656082 0.00491801 -1.24807053 +Si 2.60659632 2.74735770 5.55759099 28.08550000 1.82615170 -0.26433897 0.30541748 +Si 4.34268776 4.10349187 6.98376339 28.08550000 -1.43080835 -0.23267686 0.25205732 +Si 2.67580918 2.98242574 0.06885125 28.08550000 3.05387581 1.56364902 -2.03295787 +Si 4.21059666 4.29915060 1.38853113 28.08550000 -5.09923231 4.38424221 -4.07406768 +Si 2.57589695 5.53489064 2.69600864 28.08550000 2.57447692 1.36970402 0.08100697 +Si 4.15613206 6.84171406 4.36657688 28.08550000 -0.65456917 1.37793927 -1.56410256 +Si 5.21403152 3.10639626 2.52955426 28.08550000 5.34554142 -6.92200841 6.58498461 +Si 6.77881527 4.23338550 4.37155352 28.08550000 0.44702047 -1.27001361 -3.51830214 +Si 5.70473666 5.63133080 5.62937205 28.08550000 -7.06225437 -4.39896435 -3.74853594 +Si 6.80232924 6.67933724 6.78078589 28.08550000 4.64648548 7.39388374 5.62326246 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.975737946255 stress="0.006160838009556625 -0.02400523245303397 0.00518850903010499 -0.02400523245303397 0.0032622142247324412 -0.010133706275927938 0.00518850903010499 -0.010133706275927938 0.0009603929296566659" free_energy=-2459.975737946255 pbc="T T T" +Si -0.12952669 0.10746010 -0.10237086 28.08550000 0.80975864 0.41935052 0.24016314 +Si 1.36056853 1.67923957 1.56781176 28.08550000 -0.44927045 -2.94979550 -0.71441494 +Si -0.10867239 2.58145121 3.05170486 28.08550000 1.11038976 1.89150220 -0.34100515 +Si 1.57303859 4.34705209 4.02879308 28.08550000 -5.48253776 -3.71515711 4.56998822 +Si 2.75525540 -0.05569105 2.74307205 28.08550000 1.13205670 0.61669837 -1.60737859 +Si 4.17443898 1.60097207 3.83413984 28.08550000 -1.79210618 -2.01874661 2.77745214 +Si 2.55889539 2.80112822 5.56590199 28.08550000 1.91878161 0.17672477 -0.28876393 +Si 4.44186251 3.83994237 6.93575469 28.08550000 -1.35573239 1.89776438 -0.48371937 +Si 2.64812421 2.76705496 0.04777193 28.08550000 0.33738812 0.39469055 -1.50722924 +Si 4.13128218 4.02645493 1.42818786 28.08550000 -0.24485284 1.70870628 -1.66909844 +Si 2.79678798 5.47312534 2.90464625 28.08550000 3.12566384 2.29327100 -4.15201067 +Si 4.08075646 6.78378519 4.24460642 28.08550000 0.50838936 0.50497211 2.61104624 +Si 5.62940327 2.74947914 2.59512613 28.08550000 -3.06414891 1.24162889 0.28480341 +Si 6.87062279 4.03868981 3.74119483 28.08550000 2.23319435 2.20167597 4.15108661 +Si 5.91104035 5.86175015 5.79057810 28.08550000 -4.95790571 -5.92321327 -5.84049471 +Si 6.83831088 6.93029433 7.15526950 28.08550000 6.17093160 1.25992718 1.96957529 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.3175281607696 stress="0.023904235108615012 0.026312562694168956 0.008835431321306021 0.026312562694168956 0.011061045529229308 -0.031671849052109645 0.008835431321306021 -0.031671849052109645 -0.0028380253781728052" free_energy=-2460.3175281607696 pbc="T T T" +Si 0.06106797 0.09221339 -0.15683911 28.08550000 1.37504857 -1.31793075 2.93431000 +Si 1.33771674 1.31640360 1.61724078 28.08550000 -0.39951574 1.00750990 -0.79553222 +Si -0.28825540 3.09736815 2.70768767 28.08550000 1.85082272 -1.62296616 1.31974518 +Si 1.71818817 4.46064845 4.25123928 28.08550000 -1.10768856 -1.05845142 -1.11568315 +Si 2.81818403 -0.28467712 2.70849229 28.08550000 -1.88176878 2.03372354 2.21073062 +Si 4.23648015 1.26640649 4.18590440 28.08550000 -0.87984229 -0.11777503 -2.67650755 +Si 2.88736683 2.61922784 5.38071421 28.08550000 -1.88504128 0.78294101 0.24851897 +Si 3.90969457 4.18518071 6.69781861 28.08550000 1.93965665 -0.40487855 -0.51017114 +Si 2.76016124 2.76663654 0.09040835 28.08550000 -0.29583164 -0.62977063 -0.05977995 +Si 4.18323808 4.21861517 1.37263585 28.08550000 0.16014836 -0.11018231 -0.57419186 +Si 2.75488696 5.75090829 2.55361329 28.08550000 1.89808397 -1.36722239 1.57570569 +Si 4.34776167 6.55666786 4.34350488 28.08550000 -2.07204815 2.80951406 -1.48563712 +Si 5.53785453 2.73375399 2.81949677 28.08550000 -0.84923588 1.12740481 0.18767999 +Si 6.55789622 4.29932085 4.41242404 28.08550000 7.04230313 -8.98150212 -8.78927900 +Si 5.84200206 5.45924283 5.64471967 28.08550000 -5.81910005 6.05567187 7.50734446 +Si 6.86794461 6.99427139 6.90312744 28.08550000 0.92400895 1.79391393 0.02274706 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2454.0190110040335 stress="-0.019388735655410917 0.01814463200370462 0.04533954422502469 0.01814463200370462 -0.00558423498869201 -0.01676372285819446 0.04533954422502469 -0.01676372285819446 -0.07263086300238103" free_energy=-2454.0190110040335 pbc="T T T" +Si -0.19096097 0.11251436 -0.00386049 28.08550000 0.78274458 -0.39247606 1.11119015 +Si 1.75482946 1.41490192 1.40146541 28.08550000 -3.30781287 2.62816156 -2.85629656 +Si 0.05580010 2.87932921 2.89589440 28.08550000 -0.89694989 -2.98219140 -1.18198856 +Si 1.40009306 4.02090309 4.19974443 28.08550000 -0.44870943 2.03606556 1.47593892 +Si 2.56579285 0.09057459 2.82879509 28.08550000 6.61099081 3.50151284 -2.29488720 +Si 3.96122959 1.83272312 4.55924607 28.08550000 8.51925377 -8.74355835 -9.35757403 +Si 2.89300027 2.81005299 5.66060914 28.08550000 -7.65591103 6.77831974 5.80367188 +Si 4.10927141 4.07468554 7.01863774 28.08550000 1.11252352 1.98083132 1.45097171 +Si 2.82555380 3.07743900 -0.17102221 28.08550000 0.31764231 -2.08578967 -0.16441690 +Si 3.89944561 4.07163574 1.54679507 28.08550000 2.47660685 -0.01428325 -0.69459148 +Si 2.41763079 5.37866715 2.59920011 28.08550000 0.66261698 1.43432613 0.92330139 +Si 4.25826289 6.50459005 4.05780334 28.08550000 -2.31405092 3.07312438 -2.18726391 +Si 6.07353992 2.13914240 2.69238125 28.08550000 -6.89453695 6.18340556 12.41506584 +Si 7.07828388 4.40077894 3.90806739 28.08550000 -5.24284847 -6.10531319 4.50935518 +Si 5.46230563 5.49645041 5.52072571 28.08550000 1.55015381 -1.53465931 1.17795398 +Si 6.85743995 7.11712976 6.70703583 28.08550000 4.72828692 -5.75747585 -10.13043066 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.80051334596 stress="0.004431947104639317 -0.03284525456272267 -0.01918031386283724 -0.03284525456272267 0.013493245214373194 0.0025377878179455304 -0.01918031386283724 0.0025377878179455304 0.012879915886447142" free_energy=-2460.80051334596 pbc="T T T" +Si 0.09175629 -0.00332958 0.28255769 28.08550000 0.43429763 0.93032975 -2.85277004 +Si 1.30257176 1.73978164 1.46906851 28.08550000 -2.42040331 -1.86397829 0.75737370 +Si -0.02685506 2.96054957 2.90496601 28.08550000 -0.18673562 -1.51174976 1.32817171 +Si 1.34943079 4.30988866 3.99233056 28.08550000 1.73909338 1.01824271 2.14307153 +Si 2.62062099 0.22111083 2.45137994 28.08550000 1.99805386 -2.29688675 2.24467741 +Si 4.14725615 1.33783066 4.00368813 28.08550000 0.03780421 0.50180400 0.89214553 +Si 2.56908027 2.44889183 5.97083139 28.08550000 2.93247835 2.72476458 -3.07265232 +Si 4.32029489 4.09074074 7.03908227 28.08550000 -3.28150997 0.92116634 -1.60127994 +Si 2.63032464 2.83011289 0.22699138 28.08550000 1.18819726 -0.63782872 -3.70483927 +Si 4.18827961 4.04417091 1.07123713 28.08550000 1.60076649 1.42464798 3.24228291 +Si 2.97009664 5.64861564 2.56515044 28.08550000 -0.31549569 -1.07069733 0.87408404 +Si 4.19795048 6.99147941 4.24103270 28.08550000 -0.50631063 -0.25288342 0.23784015 +Si 5.82921328 2.91633029 2.69078736 28.08550000 -3.95365597 -2.86564869 -2.29501293 +Si 7.02307052 3.89390133 4.09356161 28.08550000 1.54875539 4.07973567 1.74585281 +Si 5.56741784 5.44401802 5.60195159 28.08550000 -1.16432225 -1.73639809 -2.65677459 +Si 6.75167934 6.65809557 6.92757169 28.08550000 0.34898740 0.63538026 2.71782929 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.8637403818507 stress="0.013036002691458262 -0.013556598094054184 0.015582053928492618 -0.013556598094054184 -0.0037672009468272473 -0.014584934691774512 0.015582053928492618 -0.014584934691774512 0.0030657284819537354" free_energy=-2459.8637403818507 pbc="T T T" +Si 0.26982146 0.20294220 -0.07897682 28.08550000 -4.28994983 -1.59737957 -0.65191322 +Si 1.22907469 1.25513193 1.40815982 28.08550000 4.73368135 -0.38629127 1.14706860 +Si 0.40402573 2.69394257 2.66229862 28.08550000 -3.19764418 2.79815107 2.98845692 +Si 1.33387292 4.35690007 4.24567543 28.08550000 -2.41150755 -5.43738971 1.09205600 +Si 2.88618536 -0.07750727 2.75148301 28.08550000 -1.48995066 -0.37851626 -0.66314175 +Si 4.14959372 1.19401441 4.14087603 28.08550000 0.10507121 1.39059706 0.41173208 +Si 2.77764631 2.79710896 5.28662561 28.08550000 0.31388438 -0.00425132 1.78938956 +Si 4.25857436 4.06052483 7.06162929 28.08550000 -0.25058280 -1.29159160 -1.13408993 +Si 2.47599039 2.94938925 0.36251793 28.08550000 1.37254483 0.69545126 -1.96274130 +Si 4.44405546 4.15752917 1.38632727 28.08550000 -1.86235643 0.35492767 0.34174588 +Si 2.67579622 5.33859546 3.18936476 28.08550000 5.95708549 4.71424690 -4.84123060 +Si 4.27881834 7.19099109 4.22971543 28.08550000 -1.13110694 -0.71262160 0.54390838 +Si 5.46407237 2.71119752 2.91106680 28.08550000 -0.17431436 -1.64216793 -2.24748968 +Si 6.73649627 4.18906969 3.86595831 28.08550000 1.81540295 0.61230538 2.68699148 +Si 5.34723740 5.29664233 5.44343525 28.08550000 0.75857029 1.73816495 -0.40461064 +Si 6.69025727 7.10504605 6.55536152 28.08550000 -0.24882802 -0.85363452 0.90386796 +16 +Lattice="5.5532188424135 5.5532188424135 -1.5724259366943e-17 5.5532188424135 -2.201396311372e-17 5.5532188424135 -1.2409869131016e-17 5.5532188424135 5.5532188424135" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2462.1823626366895 stress="0.02893941180673849 -0.013438155753781036 0.006119520914112503 -0.013438155753781036 0.020302302543564243 -0.011508188317702343 0.006119520914112503 -0.011508188317702343 0.01787285733144996" free_energy=-2462.1823626366895 pbc="T T T" +Si -0.06106797 -0.09221339 0.15683911 28.08550000 -0.19878715 0.69062658 -2.42619138 +Si 1.43889268 1.46020582 1.15936864 28.08550000 0.00200469 -1.87525952 0.59386311 +Si 0.28825540 2.45585069 2.84553118 28.08550000 -2.70552862 -1.68320171 -3.05801657 +Si 1.05842125 3.86917981 4.07858898 28.08550000 3.46187722 4.78854561 4.31398116 +Si 2.73503481 0.28467712 2.84472655 28.08550000 0.51466157 -1.24489342 -1.26649454 +Si 4.09334811 1.51020293 4.14392386 28.08550000 0.88636209 0.74820849 1.93023613 +Si 2.66585201 2.93399101 5.72572348 28.08550000 0.92811063 -0.59371785 -0.28986257 +Si 4.42013369 4.14464755 7.18522850 28.08550000 -1.35728277 0.63618347 -1.03024076 +Si 2.79305761 2.78658231 -0.09040835 28.08550000 0.10810640 1.72180065 1.89959783 +Si 4.14659018 4.11121310 1.40397358 28.08550000 -0.65240353 0.03517552 0.91207749 +Si 2.79833189 5.35552939 2.99960555 28.08550000 -0.94561342 0.76061612 -0.97527649 +Si 3.98206659 7.32637925 3.98632338 28.08550000 0.97941211 -3.57300879 -0.87307514 +Si 5.56858316 2.81946486 2.73372207 28.08550000 0.78587849 -0.83155106 0.29509270 +Si 7.32515088 4.03050741 3.91740422 28.08550000 -2.52924273 1.17589324 -0.41052701 +Si 5.26443562 5.64719485 5.46171801 28.08550000 1.58964338 -0.01428402 0.53693529 +Si 7.01510250 6.88877572 6.97991966 28.08550000 -0.86719863 -0.74113307 -0.15209952 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.428840134368 stress="0.004974578291472099 -0.01107665420973042 -0.0373974803229882 -0.01107665420973042 0.01961552060151531 0.0017904074692452188 -0.0373974803229882 0.0017904074692452188 0.0029307593035029426" free_energy=-2460.428840134368 pbc="T T T" +Si 0.31957421 0.04881529 0.04116242 28.08550000 -2.09703413 0.01952316 0.75280382 +Si 1.67684429 1.43903573 1.62804666 28.08550000 -3.47497597 2.19538808 -2.65361805 +Si 0.15078467 3.00607051 2.85049044 28.08550000 0.23499625 -3.80839019 -0.97429819 +Si 1.39589635 4.21014517 4.01548965 28.08550000 0.50861459 0.81643451 3.95997703 +Si 2.93590567 0.18630236 2.68615076 28.08550000 0.43180700 -5.76282143 -0.37512215 +Si 3.98687219 1.09525550 4.21050315 28.08550000 3.41875931 3.60752687 3.26687036 +Si 2.59527955 2.98439686 5.58405216 28.08550000 -0.10262867 -2.74442992 -1.24109590 +Si 4.14659278 3.54953560 7.03837195 28.08550000 -0.97732360 3.50431380 -0.97842507 +Si 2.73620037 2.82117451 0.11233307 28.08550000 0.76687881 0.76868630 -1.72779827 +Si 4.21230757 4.08653422 1.42778968 28.08550000 -0.03994466 1.30744090 -0.04295131 +Si 2.57536959 5.56534712 2.90297539 28.08550000 3.12209515 2.13530294 -3.57229248 +Si 4.04278354 7.24200051 3.79094286 28.08550000 -0.85152878 -1.27807788 2.51392462 +Si 5.60972477 2.75095287 2.70079872 28.08550000 -0.19784433 -0.67458110 0.89112814 +Si 6.98013981 4.23598673 4.03732134 28.08550000 -0.82431983 -0.19547994 0.84847277 +Si 5.15865104 5.32216821 5.61343554 28.08550000 1.39243643 0.89549953 -0.94082577 +Si 6.89859187 6.87779708 6.78165447 28.08550000 -1.30998732 -0.78633564 0.27325041 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.8957065463883 stress="-0.006121357229465574 -0.019035244949944546 0.017193420650813314 -0.019035244949944546 0.025385223440867598 -0.008774832914654642 0.017193420650813314 -0.008774832914654642 -0.01863033741459217" free_energy=-2459.8957065463883 pbc="T T T" +Si -0.31284592 0.06509852 -0.05997903 28.08550000 2.33791204 -1.05952331 0.92364077 +Si 1.23731527 1.61012505 1.34210715 28.08550000 0.19627441 -1.53526789 -0.40348964 +Si 0.17450427 2.66111274 3.19338158 28.08550000 -1.18085316 0.15677456 -2.54136446 +Si 1.56699630 4.12255045 4.08924637 28.08550000 0.12481034 2.92753746 0.77758257 +Si 2.56766064 -0.12392593 2.51364907 28.08550000 0.74740605 0.96465398 0.32439402 +Si 3.98193430 1.49612868 4.26058268 28.08550000 -0.41512877 -3.02698901 -2.03466379 +Si 2.65522171 2.63785677 5.50991631 28.08550000 4.88392454 5.38953916 -3.87022985 +Si 4.28036233 4.01926693 7.01412024 28.08550000 -0.08899925 -0.08788133 0.08304612 +Si 2.92032674 2.77722516 -0.05246936 28.08550000 -3.38798526 -1.64964316 -1.99154768 +Si 4.07302629 3.92698584 1.26670432 28.08550000 2.34666099 3.07026325 3.11090442 +Si 3.04547335 5.90348141 2.79167566 28.08550000 -4.55043369 -3.92125545 -5.04199673 +Si 4.18239298 6.78440815 4.18347847 28.08550000 3.79914168 1.85932896 4.83579426 +Si 5.38527416 2.44514802 2.82264254 28.08550000 0.54729632 3.05945022 -0.39830115 +Si 6.92439156 4.17285128 4.11008705 28.08550000 0.40289597 -1.58313104 -0.76632140 +Si 5.74527874 5.39231976 5.58810693 28.08550000 -1.15010379 1.39646252 1.05753482 +Si 6.99420554 7.53088544 6.84826828 28.08550000 -4.61281868 -5.96031943 5.93501823 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2458.203874019089 stress="0.004137218490471259 0.0006950453611377593 0.002871079054528102 0.0006950453611377593 0.006889855204726216 -0.0159309538455763 0.002871079054528102 -0.0159309538455763 -0.03090335107684901" free_energy=-2458.203874019089 pbc="T T T" +Si 0.19096097 -0.11251436 0.00386049 28.08550000 -1.20837861 1.32229365 -2.10014465 +Si 1.01624645 1.35617400 1.36961050 28.08550000 3.84339885 -1.34568683 0.33046157 +Si -0.05580010 2.66282262 2.64625743 28.08550000 -1.22382812 3.77841241 1.98026748 +Si 1.37098285 4.29232465 4.11348330 28.08550000 2.01729111 -1.97730223 -1.93324612 +Si 2.97635898 -0.09057459 2.71335674 28.08550000 -5.81949214 -2.45697237 -1.67436354 +Si 4.35199814 0.93835279 3.75398167 28.08550000 3.37607051 4.66470380 3.23131921 +Si 2.64915156 2.73209883 5.42369452 28.08550000 0.67087177 -0.37556232 0.82741518 +Si 4.20395633 4.23854220 6.83674182 28.08550000 -0.21847769 -1.83855650 -1.24707809 +Si 2.71659802 2.46471283 0.17102221 28.08550000 -2.16549926 2.80811178 2.20627233 +Si 4.41378213 4.24159200 1.22428084 28.08550000 -5.11630443 1.77369297 -4.94451258 +Si 3.12452104 5.70563651 2.94295172 28.08550000 -1.15784358 -1.37296881 -0.52938473 +Si 4.05496485 7.35078951 4.25542440 28.08550000 3.24666072 -2.73294481 -1.69720574 +Si 5.01076373 3.40300943 2.84977058 28.08550000 3.20501939 -5.20026355 7.59401249 +Si 6.77709568 3.91244880 4.40516035 28.08550000 0.76217447 1.00239263 -1.20225116 +Si 5.62199802 5.58785324 5.56357794 28.08550000 -0.17239658 0.81078014 0.09801071 +Si 6.99793961 6.73824980 7.14834374 28.08550000 -0.03926589 1.13987003 -0.93957261 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2458.0351027603106 stress="-0.014520663654416992 0.019392408286117057 0.06062044243561349 0.019392408286117057 0.013242588168678867 0.0020851360834132776 0.06062044243561349 0.0020851360834132776 -0.019856996070444277" free_energy=-2458.0351027603106 pbc="T T T" +Si 0.25396175 -0.42911259 -0.15149663 28.08550000 -14.36523110 8.21459065 13.33238813 +Si 1.37383673 1.20263152 1.31710369 28.08550000 -1.51462785 -1.11652441 2.73482865 +Si 0.09704673 2.80928478 3.13129144 28.08550000 -0.19349171 0.42785161 -2.19260820 +Si 1.43445279 4.57707193 4.27281276 28.08550000 13.17623655 -9.07688208 -11.47443059 +Si 2.88383917 0.03638896 2.86380068 28.08550000 -1.21539258 0.87840504 0.74668640 +Si 4.29095384 1.38789478 4.26192675 28.08550000 0.63023085 -0.95226383 -0.60073130 +Si 3.02498161 2.87132163 5.42250503 28.08550000 -1.38917190 0.75555773 1.37717205 +Si 4.10406711 4.33318533 7.04543423 28.08550000 1.56694311 -2.25473120 -0.16719755 +Si 2.29316189 2.58376465 -0.02151057 28.08550000 4.05192431 0.67346498 -1.02035461 +Si 4.19774400 4.10202326 1.21617980 28.08550000 -1.86295319 -1.13565548 0.29988113 +Si 2.48332521 5.37833069 2.56214688 28.08550000 3.13930123 0.83028505 -1.46524133 +Si 4.12500162 6.77011757 3.84516737 28.08550000 -1.04148625 0.03654309 1.76566290 +Si 5.39515593 2.81746767 2.76126026 28.08550000 2.09082929 0.07240843 0.08581160 +Si 7.07574814 4.18889845 4.25817112 28.08550000 -2.77040115 1.25551619 -1.10849512 +Si 5.31111691 5.77460258 5.73058979 28.08550000 1.51863106 -0.09944358 -1.41137775 +Si 7.07712485 7.01764705 6.90613566 28.08550000 -1.82134065 1.49087780 -0.90199388 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.108531615971 stress="-0.024920635656540367 0.05529237343867504 -0.025239236370298374 0.05529237343867504 -0.014655632832867783 0.007540828997390247 -0.025239236370298374 0.007540828997390247 0.020092962593314036" free_energy=-2457.108531615971 pbc="T T T" +Si -0.26982146 -0.20294220 0.07897682 28.08550000 2.05499788 1.83548275 -1.63697456 +Si 1.54200122 1.51594399 1.36291610 28.08550000 -1.63720750 -0.14534806 -0.35690177 +Si -0.40402573 2.84820925 2.87985321 28.08550000 1.75374738 -0.00154163 -0.86557395 +Si 1.43720300 3.95632767 4.06755231 28.08550000 -0.88247124 0.52025552 0.69145345 +Si 2.65596646 0.07750727 2.79066881 28.08550000 0.91224127 -0.28468154 0.57044371 +Si 4.16363402 1.57706150 4.17235171 28.08550000 0.06703843 -1.23350421 0.20901937 +Si 2.76450551 2.74504287 5.79767804 28.08550000 -0.72960450 -0.74880422 -2.03915808 +Si 4.05465338 4.25270291 6.79375027 28.08550000 1.10729852 1.53366250 1.54633829 +Si 3.06616143 2.59276258 -0.36251793 28.08550000 -2.61001780 2.32646189 3.89116583 +Si 3.86917228 4.15569857 1.38474864 28.08550000 2.29582308 -3.53380281 -1.40730846 +Si 2.86635561 5.74570819 2.35278707 28.08550000 12.29296210 -11.33463663 9.16768341 +Si 4.03440940 6.66438847 4.08351231 28.08550000 3.18591173 -1.93404419 -1.27407570 +Si 5.62023128 2.83095430 2.63108503 28.08550000 -0.27535486 0.57746976 1.87286170 +Si 7.11888330 4.12415805 4.44726943 28.08550000 -1.49328409 1.06511315 -2.16817809 +Si 5.73706626 5.78766132 5.64086841 28.08550000 -0.58868234 -1.65269146 -0.20372213 +Si 7.16512230 6.75033352 7.30001804 28.08550000 -15.45339831 13.01060866 -7.99707302 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.2933199032195 stress="-0.004669749942862144 -0.028364645101226944 -0.04601439011727865 -0.028364645101226944 0.0046725044158917525 -0.04628983742023946 -0.04601439011727865 -0.04628983742023946 -0.024421157880504783" free_energy=-2457.2933199032195 pbc="T T T" +Si 0.02706008 -0.15638191 -0.10574481 28.08550000 0.01718500 0.63626240 0.32501546 +Si 1.64692757 1.24643298 1.21270879 28.08550000 -1.02017387 0.59402484 0.50033153 +Si 0.06222873 2.93004444 2.97166013 28.08550000 -0.20053962 -1.93726192 -2.24464424 +Si 1.68780091 3.95018297 3.99094594 28.08550000 0.24408922 2.06000870 1.49812831 +Si 3.09412828 0.19573852 2.74249459 28.08550000 -0.63281713 -0.50814125 0.71424782 +Si 3.97377381 1.61548796 4.59105639 28.08550000 1.90834961 -1.89836242 -1.97997977 +Si 2.55386131 2.83506894 5.89189557 28.08550000 -0.62852596 -0.03833720 -0.37626397 +Si 4.27665127 4.00135420 6.90156778 28.08550000 0.02853744 1.64024398 0.94378022 +Si 2.92411364 3.12724626 0.07145938 28.08550000 -10.76368307 -10.45814449 -13.40946003 +Si 3.83208368 3.95868266 1.28455213 28.08550000 12.06535545 9.30644507 13.00665584 +Si 2.86286374 5.58071756 2.65602502 28.08550000 -0.71834719 0.37588216 0.44327103 +Si 4.13790767 7.14805351 4.17217993 28.08550000 -0.56098308 -0.37094050 -0.12580639 +Si 5.63343757 2.60267861 2.40585902 28.08550000 -2.77360295 3.29738602 3.55343241 +Si 6.73758320 4.00125038 4.28542526 28.08550000 -0.01445603 0.98476875 -1.31651124 +Si 5.36773434 5.69643291 5.54798250 28.08550000 -2.53854678 -3.81437572 -3.59603790 +Si 6.60336244 6.68852826 6.80145066 28.08550000 5.58815894 0.13054185 2.06384067 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2459.8428205423675 stress="-0.008436950889689392 -0.016871147306349175 0.020186614676320706 -0.016871147306349175 0.0015241417430497757 0.02931402013876518 0.020186614676320706 0.02931402013876518 -0.0013836636185397663" free_energy=-2459.8428205423675 pbc="T T T" +Si -0.01205304 -0.01650896 -0.00721027 28.08550000 0.70972988 0.59252974 -0.25628884 +Si 1.48723145 1.36443865 1.39597472 28.08550000 -1.61309390 -2.71246366 1.49476531 +Si -0.07829119 2.55529273 2.64016346 28.08550000 0.51036088 1.70042862 -0.84797038 +Si 1.41536777 3.91384351 4.07040307 28.08550000 -6.61123069 1.94942041 -2.01751402 +Si 2.59988889 -0.22312634 3.02057312 28.08550000 7.31302614 7.13201097 -5.82164647 +Si 4.12283388 1.50186189 4.35645601 28.08550000 1.18468204 -1.28136812 -2.62147257 +Si 2.76760696 3.01420483 5.21922731 28.08550000 3.63136331 -2.53154978 5.95063280 +Si 4.05055746 4.15759812 6.97575269 28.08550000 0.97433521 0.72112526 -0.49032453 +Si 2.54784367 2.63498109 0.03208785 28.08550000 2.94468492 2.18983630 -2.65819975 +Si 3.98754384 4.36805932 1.28163707 28.08550000 0.32086724 -2.33937705 -0.84426799 +Si 2.69933993 5.21424473 2.90863191 28.08550000 1.08202278 2.92944033 -0.94252707 +Si 4.17252375 6.80775124 3.86898104 28.08550000 -0.87035929 -0.87619492 3.49524037 +Si 5.55779395 3.01599299 2.56666698 28.08550000 -1.02937507 -0.78665008 1.23342064 +Si 6.99048744 4.22285537 4.03109167 28.08550000 -6.72152253 -5.59985848 6.81395703 +Si 5.96333095 5.82450411 5.87287172 28.08550000 -3.07296985 -2.49238237 -2.79461529 +Si 7.14951255 7.06552499 7.18820992 28.08550000 1.24747944 1.40505283 0.30681102 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.847700333888 stress="0.0011890141911141323 -0.0007776795520260002 -0.02601324329161822 -0.0007776795520260002 0.008802377644950725 -0.007844739188323666 -0.02601324329161822 -0.007844739188323666 -0.0025221791374444185" free_energy=-2460.847700333888 pbc="T T T" +Si 0.31284592 -0.06509852 0.05997903 28.08550000 -3.80692569 1.88203951 0.92292163 +Si 1.53376065 1.16095086 1.42896876 28.08550000 0.20897052 2.38104949 1.11697744 +Si -0.17450427 2.88103909 2.34877025 28.08550000 1.86497433 -1.93895834 2.70472026 +Si 1.20407961 4.19067729 4.22398137 28.08550000 1.05344111 -4.53328803 -1.68801636 +Si 2.97449118 0.12392593 3.02850275 28.08550000 -3.48739028 -3.27791222 -2.59436235 +Si 4.33129344 1.27494723 4.05264506 28.08550000 3.53805027 4.19668693 3.16092420 +Si 2.88693012 2.90429505 5.57438734 28.08550000 -1.85247466 -2.63262705 -1.50104137 +Si 4.03286541 4.29396080 6.84125932 28.08550000 -0.27159565 1.75639150 0.48953906 +Si 2.62182509 2.76492667 0.05246936 28.08550000 1.79857842 0.00283721 0.43388316 +Si 4.24020145 4.38624190 1.50437159 28.08550000 -0.36681697 -1.28270458 -1.44267913 +Si 2.49667847 5.18082225 2.75047617 28.08550000 3.31883519 0.69985196 2.03463346 +Si 4.13083476 7.07097142 4.12974927 28.08550000 -1.25768466 0.46938933 -1.38417239 +Si 5.69902950 3.09700381 2.71950929 28.08550000 -0.85860780 -3.20018341 -0.83640093 +Si 6.93098801 4.14037646 4.20314069 28.08550000 0.49007128 1.90772355 1.11379647 +Si 5.33902491 5.69198389 5.49619673 28.08550000 0.67788496 -1.24246424 -0.82500143 +Si 6.86117402 6.32449413 7.00711128 28.08550000 -1.04931064 4.81216839 -1.70572226 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.268810253723 stress="-0.0010724081661940591 0.011582559089501763 -0.007696915802401369 0.011582559089501763 -0.04559387390142517 0.0571580698373962 -0.007696915802401369 0.0571580698373962 0.005789902308236076" free_energy=-2455.268810253723 pbc="T T T" +Si 0.16542546 -0.01996001 -0.07897744 28.08550000 -0.32638277 0.38428761 0.47217100 +Si 1.69195890 1.37994326 1.70287676 28.08550000 -6.65953992 10.46285475 -7.69194298 +Si -0.43440054 2.83773837 2.60982195 28.08550000 3.97572632 -2.81712684 2.68735478 +Si 1.63252603 3.88351832 3.98649684 28.08550000 -2.81266494 0.86531170 -0.34941780 +Si 2.49213528 -0.02120702 2.54949058 28.08550000 5.68515020 -9.27232577 7.41771761 +Si 3.78734106 1.39590106 4.50983851 28.08550000 2.25283964 -2.22886487 -2.26378096 +Si 2.76299442 2.91900867 5.71057955 28.08550000 -0.62667939 0.52501617 -0.31285440 +Si 4.21385124 4.21184607 6.83171482 28.08550000 -6.99332438 -2.72939231 3.57224440 +Si 2.93357798 2.88645228 -0.37658316 28.08550000 -0.29612115 0.07176386 2.08697289 +Si 4.17951892 4.45715281 1.56761726 28.08550000 1.73292376 -1.95309092 -2.37970532 +Si 2.57874158 5.48551008 2.64479538 28.08550000 1.26046325 0.59226029 2.52412238 +Si 4.55588708 6.91626820 4.35073968 28.08550000 -1.75662985 -0.07574753 -0.96848647 +Si 5.62188067 2.78442978 2.51253621 28.08550000 -0.59208957 -0.03696346 0.99779344 +Si 6.63812941 4.15316027 4.26583602 28.08550000 0.71266556 -0.55056162 -0.95984525 +Si 5.41196410 5.41962352 5.99275431 28.08550000 6.04462641 5.49353617 -5.49300729 +Si 7.18998667 6.73213259 6.64198100 28.08550000 -1.60096344 1.26904276 0.66066372 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.4721498498907 stress="-0.0019354763821379083 -0.030167906777943662 0.019002191273589254 -0.030167906777943662 0.004715657826688945 0.03289575323493215 0.019002191273589254 0.03289575323493215 0.005042521959535765" free_energy=-2457.4721498498907 pbc="T T T" +Si 0.16965673 -0.16427368 -0.03861262 28.08550000 -0.56014464 2.48538074 0.04072396 +Si 1.44574383 1.84050848 1.47600745 28.08550000 -3.46964915 -3.75072292 4.33704139 +Si -0.27062013 2.72807136 2.92541396 28.08550000 5.49442783 -0.11462312 1.23691683 +Si 1.22762734 4.16294114 3.79441099 28.08550000 -0.52947524 -0.58694556 2.10610755 +Si 2.74867446 0.08595733 2.84600177 28.08550000 1.00752044 -0.26200209 0.32738473 +Si 4.27905557 1.64256430 4.26616431 28.08550000 -0.28521967 -0.41886175 -0.47360671 +Si 2.47276519 2.97934675 5.40562349 28.08550000 1.77199219 -1.76612107 1.40132962 +Si 4.45107857 3.80422153 7.04733158 28.08550000 -5.19509615 5.32709838 -5.92718305 +Si 2.69731793 2.30092718 0.00736613 28.08550000 5.07859638 1.34129102 -3.67241560 +Si 3.99627283 4.42734159 1.17699630 28.08550000 0.02687368 -1.65417241 0.93310860 +Si 2.73210909 5.51097526 3.02956333 28.08550000 -0.69256391 -0.33396753 -4.05588535 +Si 4.17719948 6.84270473 3.77565663 28.08550000 -1.10636084 -3.06629655 5.62391501 +Si 5.55884394 2.95251352 2.63363191 28.08550000 -0.19198247 -0.19204109 0.56424966 +Si 7.37960801 4.03766386 4.53616490 28.08550000 -2.30298077 2.41123424 -1.93194128 +Si 5.41388544 5.39767578 5.52074471 28.08550000 1.73492562 -0.06209934 0.41715480 +Si 6.94229999 6.87237914 7.01905342 28.08550000 -0.78086382 0.64284931 -0.92690016 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2450.097025055428 stress="-0.016795858376873224 -0.032354958363452445 0.021711674577047018 -0.032354958363452445 -0.08788697095570337 -0.028540931375121856 0.021711674577047018 -0.028540931375121856 0.00667225183538718" free_energy=-2450.097025055428 pbc="T T T" +Si -0.13439612 -0.49924402 -0.17281561 28.08550000 1.01188206 1.67156053 -0.51410570 +Si 1.33024559 1.44332241 0.99636962 28.08550000 -0.05024244 -0.68770349 0.88577742 +Si -0.01300942 2.81240864 2.94657914 28.08550000 1.37145443 -0.22240813 -0.49446170 +Si 1.99354967 4.34106050 3.69209011 28.08550000 -15.82735703 -17.34732300 6.23161426 +Si 2.72892451 0.03272529 2.63086648 28.08550000 0.36497554 0.80298584 0.00543531 +Si 4.25722985 1.50783099 4.33704362 28.08550000 -1.86113336 -1.56497365 1.08399276 +Si 2.52516804 2.65303530 5.95307584 28.08550000 1.27061217 0.26710548 -1.08884212 +Si 4.57083099 4.41278839 7.13708648 28.08550000 -1.55317151 -0.08897945 -0.64692863 +Si 3.07548674 2.91632650 -0.31059704 28.08550000 -6.31331929 12.15834068 9.68051744 +Si 3.88422238 4.34414340 1.45898751 28.08550000 1.28409940 -1.17383842 0.54335405 +Si 3.08253106 5.56186405 3.30628941 28.08550000 11.21452909 10.79788826 -9.37161714 +Si 3.71051458 7.05536095 4.39232233 28.08550000 9.07512961 -7.00367076 -4.49348761 +Si 5.48652887 2.76569829 2.98214923 28.08550000 0.51469165 0.53959844 -2.07672936 +Si 7.05823473 4.14440125 4.21801799 28.08550000 -0.59661240 0.55307488 -2.20489448 +Si 5.39788542 5.49149451 5.11951642 28.08550000 -0.93634973 -0.54962240 0.50261081 +Si 6.52290645 6.49363689 6.78987181 28.08550000 1.03081232 1.84796520 1.95776493 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2461.3573730833973 stress="-0.004264842407509764 0.008307490657297814 0.004288714507099701 0.008307490657297814 0.02253434385522328 0.007850248134382884 0.004288714507099701 0.007850248134382884 0.012003075305355252" free_energy=-2461.3573730833973 pbc="T T T" +Si 0.16218632 -0.06058791 -0.05704986 28.08550000 -1.42581038 1.91557955 0.77074318 +Si 1.55113868 1.56853088 1.14387713 28.08550000 -2.14102879 -3.09303268 3.18259912 +Si 0.01434667 2.72084473 2.90559828 28.08550000 2.78842330 -3.04993405 -0.83360125 +Si 1.21073704 4.14262456 4.01305861 28.08550000 2.17661260 1.89343696 0.10528873 +Si 2.83817634 0.07413236 2.77345127 28.08550000 0.17324607 0.50121624 0.53892944 +Si 4.39382632 1.83183290 4.23747302 28.08550000 -0.37130534 -4.64664694 0.48184324 +Si 2.75305662 2.86728165 5.14648548 28.08550000 -1.35668653 0.00866230 3.36696881 +Si 3.92427781 3.55648862 7.47681713 28.08550000 -3.37957981 3.27560980 -3.37899874 +Si 2.74701542 2.78945529 -0.10270640 28.08550000 2.09640858 1.95884042 -1.74734945 +Si 4.14412836 4.16180638 1.20718433 28.08550000 0.52742761 0.15471459 1.68037273 +Si 2.66572909 5.63478082 2.69875406 28.08550000 1.84762864 -1.91131924 0.50627412 +Si 4.09183885 6.98967082 4.05498236 28.08550000 -0.16229086 -2.10782685 1.52884888 +Si 5.66139667 2.73677462 2.82638636 28.08550000 1.86347692 2.82272953 -2.66723178 +Si 6.97174395 4.37493646 4.37012993 28.08550000 -0.59968718 -0.38565750 -1.40687677 +Si 5.25224726 5.10753660 5.77284315 28.08550000 -0.02941573 1.63320275 0.26241450 +Si 7.03967286 6.92540948 6.95423342 28.08550000 -2.00741961 1.03042511 -2.39022447 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.0913519035203 stress="0.025839711490752912 0.008128449910373292 -0.0041858808473276676 0.008128449910373292 -0.005735731005320452 -0.029125797815075294 -0.0041858808473276676 -0.029125797815075294 -0.001823461145600515" free_energy=-2460.0913519035203 pbc="T T T" +Si -0.05357174 -0.04834620 -0.29587220 28.08550000 -2.74094017 2.77325585 2.91815088 +Si 1.24955876 1.48853491 1.33664853 28.08550000 0.85164140 -2.15547942 -1.49225720 +Si 0.25086543 3.12560240 2.46202359 28.08550000 -1.93445736 -0.07275939 0.98995081 +Si 1.29019553 4.17492177 4.27460321 28.08550000 3.08917654 -1.37543861 -1.50305043 +Si 2.69313938 0.02514508 2.54954002 28.08550000 -1.08211200 0.14770268 2.26183747 +Si 3.98446274 1.56561580 4.14037463 28.08550000 0.83835008 -1.47379076 -1.32816451 +Si 2.77893428 2.80456930 5.71735195 28.08550000 -3.43321225 -3.03936065 -3.58178242 +Si 3.88008590 4.15002180 6.73673576 28.08550000 4.55266721 3.99091023 3.06838892 +Si 3.14908182 2.45574923 0.21171178 28.08550000 -2.21371542 -1.32603486 -2.34014607 +Si 3.71034470 4.10134150 1.45004217 28.08550000 3.38881933 0.51864266 -2.02957918 +Si 3.12663681 5.39742508 2.99243802 28.08550000 -3.12799557 2.26176702 2.02014735 +Si 4.55085360 6.81795219 4.15737171 28.08550000 -1.61077528 3.80922400 -3.59977345 +Si 5.29936371 2.73361786 2.46684075 28.08550000 0.93729796 0.28889326 1.96452976 +Si 6.97997215 3.90669106 4.45981793 28.08550000 -0.34862461 0.81131750 -1.06873429 +Si 5.43015095 5.70823919 5.61866608 28.08550000 3.77981932 -3.72639951 3.51898142 +Si 7.10144422 7.01443729 7.14322435 28.08550000 -0.94593943 -1.43245025 0.20150095 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.354030812665 stress="0.005867945710741637 0.0010476179089275869 0.029605076122227094 0.0010476179089275869 0.020219668352676003 -0.024781075689706902 0.029605076122227094 -0.024781075689706902 -0.004995695918032428" free_energy=-2457.354030812665 pbc="T T T" +Si 0.37601203 -0.58667512 -0.17794879 28.08550000 -4.53181196 4.94433723 9.18929739 +Si 1.30311895 1.47022923 1.27241691 28.08550000 1.70152416 -1.38303468 -0.50145227 +Si -0.23317060 2.55228862 2.69167872 28.08550000 1.61849604 1.15033236 -1.18996643 +Si 1.24440627 4.33064453 3.80659624 28.08550000 1.32526868 -6.02522384 -6.14937470 +Si 2.94336198 -0.06371386 2.91867319 28.08550000 0.29220330 0.91975712 -1.64669873 +Si 4.12465418 1.07666887 4.78887381 28.08550000 -0.06506845 0.57103172 -1.33665943 +Si 2.62959913 2.96505364 5.43659964 28.08550000 0.36181643 -0.68603279 1.00136213 +Si 4.38226548 4.10516045 6.75622496 28.08550000 -1.94905506 1.04579105 0.05271944 +Si 3.10553456 2.90712911 -0.21910130 28.08550000 -3.00025006 1.45811089 2.29966534 +Si 3.97240029 4.55725009 1.28022024 28.08550000 1.67408715 -1.49397392 -1.22814063 +Si 2.99224657 5.28323034 3.17660503 28.08550000 -0.53941872 -1.16659228 -3.31909615 +Si 3.95095263 6.87302608 4.03179042 28.08550000 0.90677074 3.34615753 0.35515959 +Si 5.30985828 2.59436829 2.92043771 28.08550000 0.44370966 0.43371836 0.35688300 +Si 7.01783237 4.49889419 4.33978287 28.08550000 -0.59656072 -1.56913858 -0.58630381 +Si 5.33874784 5.84783841 5.31536779 28.08550000 3.06973618 -1.84322100 3.27089954 +Si 6.96369830 7.01012539 7.08330084 28.08550000 -0.71144737 0.29798057 -0.56829478 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.4016290163454 stress="-0.020522660385932888 0.009209121495656176 -0.0514691648735791 0.009209121495656176 -0.00975634347087164 0.020618148784292634 -0.0514691648735791 0.020618148784292634 -0.0157932301940959" free_energy=-2455.4016290163454 pbc="T T T" +Si -0.37601203 0.58667512 0.17794879 28.08550000 -0.22084747 -1.46655311 -0.36960764 +Si 1.46795697 1.30084669 1.49865901 28.08550000 -5.39716660 1.63664906 -0.98695958 +Si 0.23317060 2.98986321 2.85047311 28.08550000 -1.13557757 -0.75647407 0.24870975 +Si 1.52666964 3.98258321 4.50663150 28.08550000 -0.97254212 2.03688163 -1.03578843 +Si 2.59878985 0.06371386 2.62347864 28.08550000 2.15501996 -2.69102528 4.29496889 +Si 4.18857356 1.69440705 3.52435393 28.08550000 -1.53353831 -1.46523516 2.46279669 +Si 2.91255270 2.57709819 5.64770402 28.08550000 1.37737594 0.12488645 -0.60293782 +Si 3.93096226 4.20806729 7.09915461 28.08550000 2.61375052 -1.57065887 -1.07171471 +Si 2.43661727 2.63502271 0.21910130 28.08550000 3.73966358 1.93578097 -2.83210454 +Si 4.34082745 3.75597765 1.49085567 28.08550000 -5.42112516 4.04371580 -4.38559359 +Si 2.54990525 5.80107331 2.36554679 28.08550000 6.12703001 -4.79088531 5.94313212 +Si 4.36227511 6.98235348 4.28143732 28.08550000 -0.74206433 -0.30405094 -0.15004701 +Si 5.77444537 2.94778353 2.62171412 28.08550000 0.17412513 -5.31630746 -3.19865489 +Si 6.83754719 3.81433355 3.97344487 28.08550000 5.06067785 5.07768929 6.73064223 +Si 5.74555581 5.23646524 5.76893586 28.08550000 -2.27011488 -0.53478868 -2.01983753 +Si 6.89168127 6.84525418 6.77207873 28.08550000 -3.55466654 4.04037568 -3.02700367 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2460.9132333725947 stress="-0.0027232556686058048 -0.006504228980581094 -0.021281976784428166 -0.006504228980581094 0.014226853197925469 -0.006801712067778758 -0.021281976784428166 -0.006801712067778758 0.0121573257950133" free_energy=-2460.9132333725947 pbc="T T T" +Si -0.16218632 0.06058791 0.05704986 28.08550000 1.48778039 -1.57007575 0.02400613 +Si 1.21993723 1.20254504 1.62719878 28.08550000 0.38576985 1.49982627 -1.95939861 +Si -0.01434667 2.82130710 2.63655355 28.08550000 -0.44415884 1.42683239 1.17582588 +Si 1.56033887 4.17060318 4.30016913 28.08550000 -1.40808648 -0.91229475 0.37925494 +Si 2.70397548 -0.07413236 2.76870056 28.08550000 -1.21387152 -2.88086191 -3.33899238 +Si 3.91940142 0.93924301 4.07575472 28.08550000 2.48829432 4.70919622 3.07092942 +Si 2.78909520 2.67487018 5.93781817 28.08550000 1.79269317 1.63531080 -2.96808350 +Si 4.38894993 4.75673911 6.37856244 28.08550000 -2.56762288 -3.14693637 3.20057550 +Si 2.79513641 2.75269654 0.10270640 28.08550000 -0.77775998 -0.74072452 0.14511589 +Si 4.16909938 4.15142136 1.56389158 28.08550000 -0.82140111 0.57260935 -2.84675571 +Si 2.87642273 5.44952283 2.84339777 28.08550000 -1.35739667 1.19223620 0.74692397 +Si 4.22138889 6.86570875 4.25824538 28.08550000 -2.40482911 2.67861303 -2.29107682 +Si 5.42290698 2.80537721 2.71576546 28.08550000 -0.36669561 -3.25547858 0.93075450 +Si 6.88363562 3.93829128 3.94309781 28.08550000 1.51927255 1.23759792 2.24100948 +Si 5.83205640 5.97676705 5.31146050 28.08550000 2.09829423 -3.05520353 -2.67033125 +Si 6.81570671 6.92997009 6.90114615 28.08550000 1.58971743 0.60935324 4.16024257 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.8960183562835 stress="-0.02384639117499324 -0.0039278785402210485 0.023856490909435136 -0.0039278785402210485 0.014281024500841092 -0.028531749798356498 0.023856490909435136 -0.028531749798356498 -0.010749790076883599" free_energy=-2455.8960183562835 pbc="T T T" +Si -0.07548551 -0.47607942 -0.22694797 28.08550000 -7.61930340 3.91223165 5.60905943 +Si 1.35096257 1.63737192 1.25135817 28.08550000 -1.24716088 -1.95074427 1.46878508 +Si -0.04259887 2.63570131 3.18675994 28.08550000 1.02854846 1.79281632 -2.32440938 +Si 1.42948664 4.70799891 4.22626553 28.08550000 5.45210644 -4.52072511 -3.54733709 +Si 2.57847962 0.02724806 2.70389417 28.08550000 0.61496596 -0.39693076 0.04349972 +Si 4.16245763 1.50370658 4.06643289 28.08550000 2.68894603 -3.05745119 -2.55228779 +Si 2.76587841 2.58683250 5.15224441 28.08550000 -2.22052190 2.97262921 2.97667921 +Si 4.12480351 3.92939968 6.82350976 28.08550000 -0.19099028 0.81728863 0.49991732 +Si 2.93589879 2.66469945 0.00884278 28.08550000 -0.51359893 0.42325860 -0.40560052 +Si 3.82190235 4.23152525 1.45338858 28.08550000 3.49377022 -2.50630129 -2.15011584 +Si 3.04507632 5.44823434 2.98404633 28.08550000 -4.52430897 -2.28341468 -4.03476219 +Si 4.05104612 6.67458375 4.08399383 28.08550000 1.29905679 6.45601988 2.24195513 +Si 5.61785583 2.94256029 2.75873457 28.08550000 0.38827642 -0.56047143 0.02108305 +Si 6.88347023 4.10170599 4.55186669 28.08550000 -0.65069966 1.19503922 -1.85875329 +Si 5.41673960 5.96921261 5.43679916 28.08550000 4.08525943 -3.71928270 4.42383617 +Si 7.35554502 6.83681705 6.96032942 28.08550000 -2.08434548 1.42603792 -0.41154902 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.4892590072354 stress="-0.00172338195885809 0.01757721055960537 0.001458034390339183 0.01757721055960537 -0.01180199877419387 -0.0030335929632749757 0.001458034390339183 -0.0030335929632749757 0.0010191550209549707" free_energy=-2457.4892590072354 pbc="T T T" +Si -0.22559696 0.13725215 -0.06746261 28.08550000 1.12314166 -0.67983283 0.41142226 +Si 1.46300499 1.28068764 1.41781499 28.08550000 -1.29990372 0.39194616 -0.65898633 +Si -0.16967645 2.63249494 2.82705283 28.08550000 1.47872857 -1.58115283 0.32246390 +Si 1.56269631 4.08428805 3.68562464 28.08550000 -3.95986287 -2.32180151 2.86494241 +Si 2.90922549 -0.04831372 2.74886385 28.08550000 -2.54930942 -0.11611693 0.64528775 +Si 4.09861680 1.44713273 3.96453196 28.08550000 2.39289842 -2.65036226 -0.34941394 +Si 3.12286123 2.98328324 4.94916014 28.08550000 -1.59318971 2.78899743 3.78296712 +Si 4.14882028 4.05260085 7.29290463 28.08550000 0.32699315 0.06146453 -3.61408139 +Si 2.63679809 2.86275853 0.13807031 28.08550000 0.31636678 0.67828014 -0.60859734 +Si 3.95988761 4.53226399 1.62813755 28.08550000 4.64715396 -4.98325422 -5.90116709 +Si 2.83505534 5.52717149 2.91178532 28.08550000 -1.15389283 0.82149959 3.35069167 +Si 4.27725433 6.45718366 4.11497562 28.08550000 1.72751236 3.86830743 2.22798067 +Si 5.54929286 2.85917555 2.86475125 28.08550000 0.36786058 0.62908363 -0.96004399 +Si 6.79837496 4.33618637 4.18425160 28.08550000 1.08692356 0.09397845 1.34624631 +Si 5.64647478 5.92207232 5.81087487 28.08550000 1.17239551 -2.09745836 1.31884580 +Si 7.34776471 6.89461655 7.48951739 28.08550000 -4.08381601 5.09642235 -4.17855731 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2456.9691301475777 stress="-0.017705752634320407 0.0009420297761259457 0.018595447422883802 0.0009420297761259457 0.005652178656755675 -0.011033500798933227 0.018595447422883802 -0.011033500798933227 0.020035118659692267" free_energy=-2456.9691301475777 pbc="T T T" +Si -0.14419640 -0.10559783 0.44605519 28.08550000 1.66009521 0.68188329 -3.96750394 +Si 0.93347271 1.55015526 1.39486478 28.08550000 3.14209884 -1.18360938 -0.94115204 +Si 0.01227910 2.72102582 2.92305308 28.08550000 -2.26638961 0.96070965 -0.32260634 +Si 1.14449936 4.19301409 4.01434044 28.08550000 -0.95409600 2.25897789 2.11333569 +Si 2.78223429 -0.00496091 2.62144271 28.08550000 -3.26552182 3.27899080 0.50072825 +Si 4.56483132 0.92415902 3.72281703 28.08550000 0.52460557 1.23819750 1.24383773 +Si 2.71793814 2.83810331 4.80397768 28.08550000 1.73717302 -1.46915018 1.57467905 +Si 4.16445969 4.29000646 7.30265270 28.08550000 3.02349900 -2.16523187 -3.53963047 +Si 2.56389342 2.48047420 -0.17901380 28.08550000 -2.96051289 2.01211316 2.51236884 +Si 3.85451338 4.22686349 1.08920404 28.08550000 -2.59522727 -2.44470898 3.04768588 +Si 3.02680384 5.21537750 3.41189900 28.08550000 1.29361325 1.16019717 -1.73722007 +Si 4.32258108 7.35708517 4.54847055 28.08550000 2.37088489 -2.80036890 -1.35768232 +Si 5.46844961 3.03377303 2.81410768 28.08550000 0.13286432 -0.74409807 -0.92446352 +Si 7.30176155 4.10333655 3.98526150 28.08550000 -2.70104719 0.28729249 0.76387294 +Si 5.52475378 5.63258614 5.44410440 28.08550000 1.45263213 -1.08127228 1.56164098 +Si 7.23857848 7.02145206 7.13361635 28.08550000 -0.59467147 0.01007770 -0.52789118 +16 +Lattice="5.5421518263784 5.5421518263784 8.5308753973365e-33 5.5421518263784 -3.86383412307e-33 5.5421518263784 -9.8764072084106e-18 5.5421518263784 5.5421518263784" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2458.38438154755 stress="-0.002011683469290397 0.005083839054979885 -0.013357357878245865 0.005083839054979885 0.020975312120465137 -0.014926489347445908 -0.013357357878245865 -0.014926489347445908 -0.0006436285312517426" free_energy=-2458.38438154755 pbc="T T T" +Si 0.07548551 0.47607942 0.22694797 28.08550000 -3.75115486 -4.53281341 -3.50248137 +Si 1.42011334 1.13370399 1.51971774 28.08550000 4.24191957 3.73609668 2.71562046 +Si 0.04259887 2.90645051 2.35539189 28.08550000 0.23367394 -2.21217327 1.65228034 +Si 1.34158927 3.60522883 4.08696221 28.08550000 0.78606104 2.22463206 0.62075942 +Si 2.96367220 -0.02724806 2.83825766 28.08550000 -1.09527733 1.48674861 0.52895305 +Si 4.15077011 1.26736933 4.24679485 28.08550000 -0.25305825 2.25427354 1.12037233 +Si 2.77627342 2.95531933 5.93205924 28.08550000 -1.22946192 -2.03047624 -1.71552279 +Si 4.18842423 4.38382806 7.03186980 28.08550000 -0.51453610 -1.12114880 -0.86967229 +Si 2.60625304 2.87745237 -0.00884278 28.08550000 0.96980441 -0.14473022 0.03980530 +Si 4.49132539 4.08170249 1.31768733 28.08550000 -2.10978911 1.28717675 -0.88224678 +Si 2.49707551 5.63606931 2.55810550 28.08550000 1.07137661 -0.83613919 1.14134893 +Si 4.26218162 7.18079582 4.22923391 28.08550000 -0.19819091 -0.77821686 -0.54276501 +Si 5.46644782 2.59959153 2.78341726 28.08550000 -1.33553560 2.04685648 2.46039451 +Si 6.97190933 4.21152175 3.76136105 28.08550000 -1.24706009 -1.90900807 2.33240679 +Si 5.66756405 5.11509104 5.64750450 28.08550000 1.35554676 2.75071807 -2.49058774 +Si 6.49983455 7.01856252 6.89505015 28.08550000 3.07568211 -2.22179665 -2.60866514 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2454.605752922207 stress="-0.023829864336815592 -0.0010063008134834665 0.047255739295955335 -0.0010063008134834665 0.028910948918765868 -0.01175517273269053 0.047255739295955335 -0.01175517273269053 -0.015260698741705015" free_energy=-2454.605752922207 pbc="T T T" +Si 0.04882583 -0.26249601 -0.04839546 28.08550000 -1.71475557 2.52009346 1.10105743 +Si 1.08741211 1.57171395 1.30849620 28.08550000 -1.28043507 -2.57578690 -0.73407822 +Si -0.10878459 2.11325763 3.01804356 28.08550000 5.30815398 3.63976156 -4.19865408 +Si 1.18333375 4.30639216 4.04003334 28.08550000 2.13908889 -1.60294396 -2.39408036 +Si 2.45760540 -0.02357352 2.24252713 28.08550000 -1.60309411 1.52487267 3.47859197 +Si 4.07113674 1.34648737 4.33493457 28.08550000 0.64651776 0.18341555 -1.12904543 +Si 2.51989750 2.83125507 5.32788845 28.08550000 0.90617321 0.57717074 0.66504230 +Si 4.01134129 4.48093723 7.04214773 28.08550000 3.44721654 -2.68822201 -2.65250579 +Si 2.60502342 2.52769841 0.13400344 28.08550000 1.30615278 2.72326666 -0.02368295 +Si 4.27190796 4.01873418 1.24729612 28.08550000 0.03029608 -0.06782750 1.73808396 +Si 3.55839088 5.43822393 3.20083729 28.08550000 -1.52485698 -0.45607487 -0.88158524 +Si 4.14131005 7.46541128 4.32212827 28.08550000 -4.63991656 -2.96404250 5.03366610 +Si 5.84117183 3.23681971 3.15251176 28.08550000 -6.27014661 -5.23639475 -5.30098600 +Si 7.20309688 4.08431424 4.24782905 28.08550000 4.57822629 4.59912961 3.31102572 +Si 5.79012997 5.73191791 5.40640237 28.08550000 -0.45433346 0.29498780 1.06052476 +Si 7.27905533 7.09376081 6.98417054 28.08550000 -0.87428690 -0.47140533 0.92662608 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.8442983600435 stress="-0.00014965970127536957 -0.004915816200173796 -0.020600703788438444 -0.004915816200173796 -0.020268330709532413 -0.022169835257638486 -0.020600703788438444 -0.022169835257638486 0.008109168599166036" free_energy=-2455.8442983600435 pbc="T T T" +Si 0.02081040 0.04382839 -0.51126462 28.08550000 -1.73386376 -2.87558112 0.08364236 +Si 0.82525636 1.50423319 0.75644712 28.08550000 1.93603165 2.80071780 3.16512436 +Si -0.20522704 2.90175259 3.16629776 28.08550000 -0.84157322 -0.77704676 -2.43629993 +Si 1.48725201 4.09814055 3.98469690 28.08550000 -1.72374595 0.92927689 -0.27220783 +Si 2.87274979 0.27635781 3.16492334 28.08550000 -3.61789587 -4.78252511 -4.38395528 +Si 3.97169729 1.54013006 4.28737596 28.08550000 6.47864045 0.03758233 -0.41100009 +Si 2.66745450 2.78925368 5.17735377 28.08550000 -1.02356695 1.79159479 6.17198215 +Si 4.22281357 4.24282190 7.04630675 28.08550000 -0.89134129 0.06992501 0.44819341 +Si 2.75289513 2.64257353 -0.00483921 28.08550000 0.65585061 0.64246493 -0.22557342 +Si 4.35103223 4.32730826 1.51183301 28.08550000 -0.54330186 -0.67629679 -0.83404811 +Si 2.67110314 5.69245366 3.04918785 28.08550000 3.89126944 -1.10987503 0.18076552 +Si 4.59208913 6.61467609 4.25191127 28.08550000 -1.90746027 1.01436343 0.18662789 +Si 5.83478492 2.58854288 2.90959834 28.08550000 -5.02848815 -2.60562507 -2.78841353 +Si 6.70539152 4.02438971 3.96530762 28.08550000 4.31514073 5.34643616 4.89717883 +Si 5.80175947 5.54365116 5.84952879 28.08550000 0.97684487 -0.63717849 0.37391861 +Si 7.38899195 7.13074091 7.35618968 28.08550000 -0.94254044 0.83176729 -4.15593468 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.436264481543 stress="-0.01931069225290535 -0.007240591437162972 0.052359777819819014 -0.007240591437162972 -0.015291916102707243 0.03676303336850181 0.052359777819819014 0.03676303336850181 -0.03874441763446653" free_energy=-2455.436264481543 pbc="T T T" +Si 0.22556733 -0.03076357 0.18488869 28.08550000 1.54118529 3.96290295 2.18206771 +Si 1.62849107 1.48669422 1.54053869 28.08550000 -4.44947264 4.33746408 -2.93531145 +Si -0.04722562 2.98124444 2.67273069 28.08550000 -0.06991061 -0.29804587 1.99301887 +Si 1.48931963 4.74767796 4.29640794 28.08550000 -0.36948809 -5.53778203 -0.32011828 +Si 2.56377280 0.18774210 2.72131791 28.08550000 3.46682840 -3.20334509 4.83243177 +Si 4.54539808 1.03439659 4.25210719 28.08550000 -3.31751055 0.96806918 -0.50281624 +Si 2.72718635 2.41506907 5.61956345 28.08550000 6.00879038 7.32700600 -5.67662160 +Si 3.74337223 4.17462102 7.17986014 28.08550000 1.76917966 -1.50249379 -2.37127647 +Si 2.72649569 2.80638543 0.04155929 28.08550000 -0.78148756 2.11090832 -0.85606524 +Si 4.43040026 4.15518988 0.89853574 28.08550000 -3.57387268 -3.71511931 4.19170593 +Si 2.66550788 5.42125219 2.78430571 28.08550000 4.08465368 2.12599015 -3.41170677 +Si 3.93512603 7.00351017 4.34195649 28.08550000 2.01895435 -1.34023095 -2.37903940 +Si 5.48404774 2.38868488 2.76105284 28.08550000 1.85237644 2.47159063 -1.97840574 +Si 6.65189785 4.55327177 4.06365411 28.08550000 2.76696333 -4.81856272 -3.19781233 +Si 5.47335132 5.37794723 5.46868117 28.08550000 -3.90750647 3.07749217 4.34053346 +Si 7.23414470 6.77392996 6.64969328 28.08550000 -7.03968292 -5.96584396 6.08941580 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.615646495436 stress="-0.012160998425719447 -0.05820660590400032 0.040246523593279446 -0.05820660590400032 -0.00688618257402007 0.03839735403273591 0.040246523593279446 0.03839735403273591 -0.005777048100764571" free_energy=-2457.615646495436 pbc="T T T" +Si 0.01415483 -0.01325108 0.31311929 28.08550000 5.03252144 6.10874278 -7.72505648 +Si 1.33264951 1.54093250 1.49807356 28.08550000 -1.69962000 -1.77303863 1.68555813 +Si -0.16368561 2.85921410 2.88656043 28.08550000 4.85345131 6.04819022 -5.31649001 +Si 1.42106632 3.96309514 4.15089181 28.08550000 -0.24405734 1.15223678 1.38328433 +Si 2.67863573 -0.17856736 2.49634621 28.08550000 0.25396611 1.98448666 0.90752844 +Si 4.00822363 1.34130898 3.94652208 28.08550000 0.97781674 0.07542305 1.28939639 +Si 2.82239662 2.76683998 5.60726496 28.08550000 -0.72110058 -1.95071676 -0.93136771 +Si 4.20064539 4.22797260 6.78015508 28.08550000 -0.09515935 -1.31408798 0.71372691 +Si 2.51506653 2.60415452 0.12129958 28.08550000 3.61421560 2.98758737 -2.92020107 +Si 4.53683779 4.40829702 1.39034900 28.08550000 -6.60833409 -7.60561357 6.88818864 +Si 2.42857802 5.74062525 3.04793039 28.08550000 1.20185933 0.33753879 -1.15251934 +Si 4.38096987 7.10666589 3.83662280 28.08550000 -6.48924033 -7.33876623 6.12662429 +Si 5.81371533 2.73514299 3.12329832 28.08550000 -1.04814901 -0.49804479 -1.85069340 +Si 7.08066867 4.38510059 4.21284343 28.08550000 0.26609040 -2.07308456 0.67169761 +Si 5.50689122 5.48068605 5.43351097 28.08550000 -2.05752707 0.44027827 -2.70158892 +Si 6.90003949 6.50863618 6.63206541 28.08550000 2.76326763 3.41886807 2.93191245 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2453.811897545403 stress="-0.021963249780417884 -0.009277983321396378 -0.010924240035425442 -0.009277983321396378 -0.018921393398054084 -0.013248097114738082 -0.010924240035425442 -0.013248097114738082 0.01130435731351135" free_energy=-2453.811897545403 pbc="T T T" +Si 0.14419640 0.10559783 -0.44605519 28.08550000 -0.60434370 0.91936580 2.04241027 +Si 1.84036996 1.22368740 1.37897788 28.08550000 -2.17175938 1.91932977 -2.02116216 +Si -0.01227910 2.82665952 2.62463225 28.08550000 0.71771495 -0.94006678 0.60076524 +Si 1.62934331 4.12851391 4.30718756 28.08550000 -0.06079168 -0.50026750 -1.51303942 +Si 2.76545105 0.00496091 2.92624262 28.08550000 0.70448328 -1.01117012 1.96029387 +Si 3.75669668 1.84968365 4.59871097 28.08550000 2.42429236 -2.86657043 -4.05603447 +Si 2.82974719 2.70958203 6.29139299 28.08550000 -7.38679315 -4.62940281 -0.26673112 +Si 4.15706831 4.03152154 6.56656064 28.08550000 5.53522044 5.95824943 3.90684107 +Si 2.98379191 3.06721114 0.17901380 28.08550000 -1.08804199 -0.99748568 -0.64328383 +Si 4.46701462 4.09466452 1.68463862 28.08550000 -1.05216893 2.21337603 -1.81108710 +Si 2.52088149 5.87999317 2.13578633 28.08550000 5.27791369 -4.62603184 3.79193025 +Si 3.99894693 6.51212816 3.77305745 28.08550000 1.02918995 1.57057660 0.70853200 +Si 5.62692106 2.51391230 2.73357765 28.08550000 -1.00562605 0.88109313 3.55271018 +Si 6.56745179 4.21819145 4.33626650 28.08550000 4.23943563 -2.96021361 -3.21142530 +Si 5.57061689 5.46278453 5.65126627 28.08550000 -4.33615204 0.36328556 -1.76736137 +Si 6.63063486 6.84776127 6.73559699 28.08550000 -2.22257312 4.70593272 -1.27335785 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.903475363804 stress="0.003859016714480848 0.02204680212898266 -0.05279682087385016 0.02204680212898266 -0.011766190624808963 0.033084893716298566 -0.05279682087385016 0.033084893716298566 -0.014113919803711539" free_energy=-2455.903475363804 pbc="T T T" +Si 0.02728066 0.36448079 0.11650738 28.08550000 0.85412174 -2.94122858 1.55688599 +Si 1.60202021 1.28225554 1.81722158 28.08550000 -8.42665781 10.60644084 -13.13847862 +Si 0.03102153 2.81580050 2.62787202 28.08550000 -2.19640521 -1.88052642 -5.86924736 +Si 0.87297718 3.79695347 4.11406662 28.08550000 4.19895078 4.39897746 6.68734100 +Si 2.45353868 0.24824644 2.93406288 28.08550000 10.30009081 -11.63444757 11.52049114 +Si 4.41057222 1.40598219 4.15262566 28.08550000 -2.78317156 0.75332267 -0.82750928 +Si 2.89644011 2.82540368 5.49543684 28.08550000 -1.27256132 -0.81162269 -0.04266591 +Si 4.16384334 4.21340547 6.87732858 28.08550000 -0.23929797 1.56839116 -0.67509712 +Si 2.90586223 2.55342388 -0.11502348 28.08550000 1.51325539 -0.24181302 2.31185879 +Si 4.19681532 4.23395138 1.40874003 28.08550000 -0.54421306 0.08859533 0.42689259 +Si 2.54900849 5.30748137 3.29538808 28.08550000 0.32129636 0.47409419 -2.55300924 +Si 4.24175189 7.00965173 3.73926538 28.08550000 -2.96527200 -0.58068750 0.60438021 +Si 5.60743923 2.94551492 2.99514466 28.08550000 -0.31933024 -0.68923073 -3.05770290 +Si 7.08972776 3.90789653 4.33995664 28.08550000 -0.22937222 2.16329686 -0.86903877 +Si 5.56857722 5.65787789 4.81293802 28.08550000 1.53702627 -1.19465612 3.75467188 +Si 6.85997728 6.90852755 6.86532243 28.08550000 0.25153976 -0.07890587 0.17022760 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2450.86980739266 stress="-0.03326117999019348 0.01123733180312422 -0.05182265557904545 0.01123733180312422 -0.022891507191395787 0.02569005178947755 -0.05182265557904545 0.02569005178947755 -0.02939389985662381" free_energy=-2450.86980739266 pbc="T T T" +Si -0.04882583 0.26249601 0.04839546 28.08550000 1.38128067 -1.62112911 0.94921476 +Si 1.71063061 1.22632876 1.48954652 28.08550000 0.07087734 1.17473162 -0.31003956 +Si 0.10878459 3.48282781 2.57804187 28.08550000 8.89071133 -4.13939941 7.78657809 +Si 1.61470897 4.08773599 4.35409481 28.08550000 -1.08581927 1.68160146 -0.13719458 +Si 3.13848004 0.02357352 3.35355830 28.08550000 -5.04564949 -4.75975182 -3.71222991 +Si 4.32299142 1.45155535 4.05919359 28.08550000 1.72746839 3.27826369 5.02001688 +Si 3.07618793 2.76483036 5.86428242 28.08550000 -3.55660412 -2.85401034 -3.35086599 +Si 4.38278686 3.91319092 6.94806586 28.08550000 -6.13145154 4.48686574 -3.17395687 +Si 2.99106201 3.06838703 -0.13400344 28.08550000 -0.77826469 -1.18923470 -0.00351290 +Si 4.12222019 4.37539398 1.55074659 28.08550000 -0.24595738 0.40865473 -0.86834303 +Si 2.03769455 5.75394694 2.39524815 28.08550000 9.85652642 -11.94256959 10.25187055 +Si 4.25281810 6.52480231 4.07199988 28.08550000 -1.35695932 1.48573508 -0.60317848 +Si 5.35099904 2.35926572 2.44357368 28.08550000 -2.12303312 6.06564467 1.28065335 +Si 6.78711671 4.30981392 4.14629911 28.08550000 1.00480484 -0.90949662 0.27969180 +Si 5.40204090 5.46025296 5.78576850 28.08550000 0.89346039 0.62473409 -1.91342677 +Si 6.71115826 6.89645278 7.00604305 28.08550000 -3.50139096 8.20936026 -11.49527761 +16 +Lattice="5.5476853343959 5.5476853343959 1.0671265915485e-32 5.5476853343959 7.9808909170545e-33 5.5476853343959 -1.1143138169713e-17 5.5476853343959 5.5476853343959" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2457.4832999863734 stress="0.020076435755136384 0.0029224958844141185 -0.012697202508816476 0.0029224958844141185 -0.01104451869105166 -0.001707773278356978 -0.012697202508816476 -0.001707773278356978 0.0030290021748922953" free_energy=-2457.4832999863734 pbc="T T T" +Si 0.13439612 0.49924402 0.17281561 28.08550000 -1.48401218 -1.97312187 -1.28208494 +Si 1.44359708 1.33052026 1.77747305 28.08550000 0.78644568 -0.64954369 0.07509575 +Si 0.01300942 2.73527669 2.60110619 28.08550000 -1.44418965 3.12281300 0.29685905 +Si 0.78029300 3.98046751 4.62943789 28.08550000 0.74663678 -0.19443890 -0.52277700 +Si 2.81876083 -0.03272529 2.91681885 28.08550000 -1.57047812 -3.69541669 -1.69723711 +Si 4.06429815 1.26601167 3.98448438 28.08550000 3.85380281 2.15781038 1.38097908 +Si 3.02251729 2.89465003 5.14229483 28.08550000 -3.86168376 -1.24278306 -2.82011317 +Si 3.75069701 3.90873961 6.73212686 28.08550000 3.52205929 3.21155077 4.69053876 +Si 2.47219860 2.63135884 0.31059704 28.08550000 2.05846321 1.85477014 -2.31278542 +Si 4.43730562 3.97738460 1.31485516 28.08550000 -2.98422977 2.89966413 -3.25971550 +Si 2.46515427 5.53350662 2.24139592 28.08550000 1.78269440 -3.73071717 1.97793755 +Si 4.61101342 6.81385239 3.92920567 28.08550000 -1.61225932 -1.68496009 2.02669980 +Si 5.60884180 2.78198705 2.56553610 28.08550000 0.61425736 -1.63910344 3.50970591 +Si 6.81097861 4.17712675 4.10351001 28.08550000 -0.08820092 -0.17310800 1.74784336 +Si 5.69748525 5.60387616 5.97585425 28.08550000 -0.17394824 -0.24540331 -1.09034158 +Si 7.34630688 7.37557645 7.07934153 28.08550000 -0.14535783 1.98198806 -2.72060428 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.6328484953465 stress="0.007839230242264449 -0.013030493745399047 -0.003967359320312097 -0.013030493745399047 0.018194212518237565 -0.012916642193508581 -0.003967359320312097 -0.012916642193508581 -0.01585107412771767" free_energy=-2455.6328484953465 pbc="T T T" +Si -0.39724897 0.40131563 0.12546665 28.08550000 2.40962910 -1.96963700 1.29258636 +Si 1.52028407 1.59053712 1.32424001 28.08550000 -4.34297447 -5.64237013 0.85434569 +Si 0.49910384 2.68706177 2.73591311 28.08550000 -4.32063904 2.42502255 1.77913368 +Si 1.06079481 4.07746631 4.34556316 28.08550000 1.60794681 1.31830407 1.41707146 +Si 2.61075849 0.39675181 2.82458799 28.08550000 -3.99143474 -5.42023762 -4.15277146 +Si 3.87269388 1.01323289 4.15231611 28.08550000 4.50661464 3.52322066 2.63028837 +Si 3.10093096 2.67644375 5.45688695 28.08550000 -1.86452696 2.02917269 1.10861981 +Si 4.10997295 4.16474518 7.08357720 28.08550000 0.92206340 -0.09568103 0.08395552 +Si 2.74093357 2.52478468 0.15646407 28.08550000 6.47271894 4.74893314 -5.35052730 +Si 3.88821420 4.42647172 1.26600365 28.08550000 -0.14870309 -1.39990111 1.18508828 +Si 2.47410563 5.41672030 2.89372020 28.08550000 0.33460927 1.48726977 -0.14362336 +Si 4.50964551 7.21770858 4.25220764 28.08550000 -0.13907945 -1.75541706 -0.01968848 +Si 5.21514457 2.63110550 2.73208095 28.08550000 0.22428478 1.25859920 0.04235712 +Si 7.20129708 3.76973348 4.10434869 28.08550000 -0.74799972 -0.29267844 -1.37990179 +Si 6.45387600 5.49672159 5.35768507 28.08550000 -1.47426924 1.78274968 0.93200534 +Si 7.10034775 7.47005403 7.14979289 28.08550000 0.55175976 -1.99734938 -0.27893949 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2453.159647895109 stress="-0.049759555279869035 0.009352354093195792 0.061099720742765304 0.009352354093195792 -0.023927189050528406 -0.030965785798853458 0.061099720742765304 -0.030965785798853458 0.003500017062955269" free_energy=-2453.159647895109 pbc="T T T" +Si 0.22559696 -0.13725215 0.06746261 28.08550000 -8.62529507 9.29131130 7.06364740 +Si 1.33503773 1.51735508 1.38022772 28.08550000 1.13187673 -0.74229444 0.28741385 +Si 0.16967645 2.96359050 2.76903260 28.08550000 -1.23906267 1.34894905 0.70580689 +Si 1.23534641 4.30984010 4.70850352 28.08550000 8.96169511 -9.36600031 -9.09243931 +Si 2.68685995 0.04831372 2.84722158 28.08550000 1.65057827 0.54797355 -0.43452620 +Si 4.29551135 1.35090999 4.42959620 28.08550000 -0.95423047 0.08069484 -0.84014548 +Si 2.47322421 2.61280219 6.24301073 28.08550000 10.64024107 7.88764507 -3.42573523 +Si 4.24530788 4.34152731 6.69730896 28.08550000 -3.06587541 -2.34648307 4.59004411 +Si 2.95928735 2.73332690 -0.13807031 28.08550000 -8.03058760 4.14538673 8.48648661 +Si 4.43424054 3.86186416 1.16990517 28.08550000 -0.74791307 2.32268622 1.18027363 +Si 2.76103010 5.66499938 2.68430012 28.08550000 0.23549248 0.15010126 0.42559007 +Si 4.11687383 7.53302993 4.27915253 28.08550000 8.15158269 -7.53065717 -9.31476079 +Si 5.64287801 2.73690988 2.73133418 28.08550000 0.35504826 -1.12444007 1.37991310 +Si 7.19183863 4.05794178 4.20987655 28.08550000 -1.22239807 0.48325837 -1.62153175 +Si 5.54569609 5.27009855 5.38129600 28.08550000 1.76395723 2.95989068 -2.59564507 +Si 6.64244887 7.09559704 6.50069619 28.08550000 -9.00510922 -8.10802177 3.20560818 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2454.9067746338646 stress="-0.025073049830845344 -0.007200192499395388 0.038548850049364355 -0.007200192499395388 -0.01160551303141516 -0.00912740546244447 0.038548850049364355 -0.00912740546244447 0.030923550545732804" free_energy=-2454.9067746338646 pbc="T T T" +Si -0.08466326 -0.28510385 -0.11325986 28.08550000 -0.05039028 1.46986752 -0.26507353 +Si 1.41013662 1.46329456 1.05014234 28.08550000 -2.06388361 -1.58388128 1.72283321 +Si 0.09634781 2.86489734 3.04008184 28.08550000 4.46420841 2.42628291 -4.60885738 +Si 1.72356655 4.11847650 4.04952190 28.08550000 -4.56519337 -4.21736502 5.41049622 +Si 3.06522040 0.22345001 2.42218716 28.08550000 -1.77651527 0.92591543 1.56338702 +Si 3.83582280 1.45460408 4.40098885 28.08550000 1.28626684 -0.16156092 -0.38131670 +Si 2.44798939 2.65589405 6.22455863 28.08550000 2.02596755 1.52276693 -2.06946959 +Si 4.36473184 4.26054172 7.07759241 28.08550000 0.49705825 -1.10038688 -1.30204493 +Si 3.06342664 2.71897357 0.41635318 28.08550000 -0.05802131 -0.43520111 -3.29674170 +Si 3.93737695 4.29968813 1.58817768 28.08550000 3.75499609 -0.41755409 -1.72119876 +Si 2.95338473 5.36044388 3.12764941 28.08550000 2.59158530 6.25292356 -0.94336396 +Si 4.14443530 7.48199685 3.82366408 28.08550000 -4.42074571 -3.49905615 3.84925582 +Si 5.42091819 2.73303341 2.74048988 28.08550000 0.30925331 -0.42250115 1.20331843 +Si 6.91419328 4.50956989 4.08684383 28.08550000 9.34590919 -8.00263328 -5.56958683 +Si 5.61461261 5.57799257 4.78764749 28.08550000 -9.18754595 7.25234040 6.39456332 +Si 7.05335450 6.52310163 7.23821554 28.08550000 -2.15294971 -0.00995660 0.01379937 +16 +Lattice="5.801917626543 5.801917626543 1.2245245509546e-18 5.801917626543 -2.0408742515911e-18 5.801917626543 9.037450752094e-18 5.801917626543 5.801917626543" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2427.518906585733 stress="-0.04926466829221613 0.08805683012586252 0.055700953604733545 0.08805683012586252 -0.05221929969530901 -0.09295061054179944 0.055700953604733545 -0.09295061054179944 -0.08249187644837777" free_energy=-2427.518906585733 pbc="T T T" +Si 0.01782461 -0.12827085 -0.01046386 28.08550000 0.42655295 0.42525634 -0.30109469 +Si 1.98716566 1.63993208 1.44885450 28.08550000 -0.77713597 -0.32679672 0.26802670 +Si -0.35297982 2.74158747 2.79261294 28.08550000 1.83569692 1.44369369 -1.54179490 +Si 1.88409239 4.10345329 4.33340428 28.08550000 -1.68812049 0.82431392 -0.73625569 +Si 2.47802514 0.12267405 3.46100108 28.08550000 0.88633844 -0.07132446 -1.07400994 +Si 4.71537095 1.94844878 4.22559328 28.08550000 -0.58558442 -1.40644791 0.76638928 +Si 2.85265130 2.70083143 5.98276297 28.08550000 1.14985542 0.12552203 -1.64563455 +Si 3.74951947 4.37812139 7.28858179 28.08550000 1.11193859 1.06534815 1.58314389 +Si 3.75727810 2.28780757 -0.60992138 28.08550000 -44.50520907 45.79640369 50.89731236 +Si 3.75711796 4.36571354 1.73488509 28.08550000 0.43232790 -0.36928548 -0.49823505 +Si 2.47604765 6.29123957 2.48873517 28.08550000 7.10144493 -5.82032492 7.29133272 +Si 4.46463367 7.35153698 4.38657226 28.08550000 42.67132683 -45.67464807 -48.73115592 +Si 6.39283844 2.78945219 2.56924080 28.08550000 -2.43456495 3.80518968 3.49333467 +Si 7.02367544 4.12681485 4.71914562 28.08550000 0.64402508 0.30800684 -0.36877383 +Si 5.68195963 6.16012052 6.12105411 28.08550000 -4.95046031 -4.59321325 -3.18763025 +Si 7.13395570 7.13971341 7.08711761 28.08550000 -1.31843160 4.46830674 -6.21495454 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2456.731889333647 stress="0.0001845496929837379 -0.03126785967443381 0.058515106883316424 -0.03126785967443381 0.0009144850458298655 0.02206149265180724 0.058515106883316424 0.02206149265180724 0.012682511985991901" free_energy=-2456.731889333647 pbc="T T T" +Si 0.18782353 -0.01362427 -0.12423230 28.08550000 -0.40075784 -0.12376879 -1.36050230 +Si 1.37725385 1.31030874 1.26171815 28.08550000 0.76491089 0.23980756 2.12999721 +Si -0.39756201 2.77680274 3.40945809 28.08550000 9.10820377 8.08384492 -8.14204004 +Si 1.69848934 4.07177312 3.72252937 28.08550000 -1.83190275 -0.91928224 2.33842600 +Si 2.99738063 -0.02986074 2.87380473 28.08550000 -1.56453887 -0.27252999 -0.38038134 +Si 3.96132282 1.51425201 4.51732510 28.08550000 3.66222606 -3.26313147 -3.38373626 +Si 2.64705981 2.65509129 5.66909396 28.08550000 2.13799386 6.88808451 -2.82166483 +Si 4.35758277 4.05131180 6.86392262 28.08550000 -1.38971723 -0.58415283 2.24452083 +Si 2.80718027 2.78449519 0.19419816 28.08550000 -0.91501061 2.13458432 0.47293205 +Si 4.66081610 4.49689307 1.59401553 28.08550000 -0.59884925 -1.40080820 -0.80634499 +Si 2.94938768 5.65495217 2.65822451 28.08550000 0.17365051 1.32195812 -0.05427264 +Si 4.01933070 7.27344051 4.27118975 28.08550000 -7.06410248 -9.01720652 5.22267200 +Si 5.46888265 2.42813469 2.46367355 28.08550000 -1.57608621 1.82860633 2.73197242 +Si 6.63267666 4.26986846 4.12584967 28.08550000 2.15697683 -1.20381671 -1.26510872 +Si 5.45164029 5.54487237 5.56544994 28.08550000 0.51429647 1.89294588 -0.09701801 +Si 7.14158923 7.17214320 6.89463352 28.08550000 -3.17729313 -5.60513490 3.17054861 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2455.490898953007 stress="0.0037396562165311663 0.038629647924899535 -0.019306101464522676 0.038629647924899535 -0.02395289746547142 -0.023648069116861462 -0.019306101464522676 -0.023648069116861462 0.006179201163087344" free_energy=-2455.490898953007 pbc="T T T" +Si -0.18782353 0.01362427 0.12423230 28.08550000 -2.38401449 1.47756591 1.55715929 +Si 1.42078887 1.48773398 1.53632457 28.08550000 6.32413952 -9.02373815 -6.93883654 +Si 0.39756201 2.81928269 2.18662735 28.08550000 -9.20714342 10.87942540 7.16110635 +Si 1.09955337 4.32235504 4.67159879 28.08550000 3.32318601 -2.58684599 -3.11748362 +Si 2.59870480 0.02986074 2.72228070 28.08550000 1.84380515 0.10397747 1.34277300 +Si 4.43280533 1.28379071 3.87680306 28.08550000 -0.67073447 0.84557025 1.43400423 +Si 2.94902562 2.94099415 5.52307691 28.08550000 -0.95423973 -0.92751954 0.20540157 +Si 4.03654539 4.34281635 7.12629096 28.08550000 1.96832805 -1.28321700 -1.91439942 +Si 2.78890516 2.81159024 -0.19419816 28.08550000 0.93783403 -7.57891035 -0.61971247 +Si 3.73331205 3.89723508 1.20402718 28.08550000 3.96959193 4.69659730 5.29778935 +Si 2.64669776 5.53721870 2.93786093 28.08550000 -0.20330792 -1.08403518 -0.29639343 +Si 4.37479745 6.71677307 4.12293841 28.08550000 -0.55450133 1.54430892 -0.97947176 +Si 5.72328822 3.16795074 3.13241188 28.08550000 -2.14970240 -2.08225389 -2.92472442 +Si 7.35753692 4.12425969 4.26827848 28.08550000 -2.98071019 4.30328435 -1.21122868 +Si 5.74053058 5.64729850 5.62672093 28.08550000 -0.97041351 -2.06715688 -0.44734623 +Si 6.84862436 6.81807039 7.09558007 28.08550000 1.70788276 2.78294711 1.45136277 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2456.109195871715 stress="0.008900620516340076 -0.04461787229126739 -0.015025650376511797 -0.04461787229126739 -0.03325291657110466 -0.011938804267997732 -0.015025650376511797 -0.011938804267997732 0.025328297664922356" free_energy=-2456.109195871715 pbc="T T T" +Si -0.04254541 -0.22441464 -0.13007026 28.08550000 3.41669009 2.00014416 -0.84604436 +Si 1.14236273 1.32086478 1.92800323 28.08550000 -0.54311674 0.09313513 -0.67266357 +Si -0.04306859 3.24341230 3.08023176 28.08550000 0.01136222 -1.05789246 -0.59105058 +Si 1.94900625 4.28319223 4.09753333 28.08550000 -2.00616286 -0.81077372 1.67641991 +Si 2.80758882 -0.07381559 3.16453588 28.08550000 -0.50808777 -0.06915676 -3.30975174 +Si 4.29370789 1.18123474 4.13026220 28.08550000 0.65268944 1.80355942 1.94807418 +Si 2.73649878 2.83812990 6.02314257 28.08550000 -5.45694037 -11.32186416 -7.43262049 +Si 3.56551767 4.28546506 6.66155571 28.08550000 8.23754392 12.51116648 6.36772589 +Si 2.49960920 3.03823030 -0.57375702 28.08550000 3.62931929 -3.04757352 2.79501355 +Si 4.33056721 4.09633058 1.06980275 28.08550000 -2.31051051 -2.31915584 1.27035017 +Si 3.13403685 5.48486900 2.55553902 28.08550000 -0.36379129 1.22514915 -0.43958381 +Si 4.52389560 6.66683647 4.05380003 28.08550000 0.16459637 1.60112953 -0.04783203 +Si 5.55889912 2.83191572 2.94506845 28.08550000 -1.62426689 -0.77493254 -1.82164482 +Si 6.75483392 4.34847125 4.04121248 28.08550000 -1.53367947 1.50169983 -0.14741060 +Si 5.84882028 5.51721777 5.77282241 28.08550000 -2.33623928 0.12898299 0.35697890 +Si 6.90112404 7.12291449 7.14117181 28.08550000 0.57059335 -1.46361716 0.89403966 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2456.0655022811948 stress="-0.010377936217886515 0.0057568486318807805 -0.03807875331897792 0.0057568486318807805 0.013916515903256295 -0.006615326059441949 -0.03807875331897792 -0.006615326059441949 -0.010420171471007173" free_energy=-2456.0655022811948 pbc="T T T" +Si 0.09197643 0.63643557 0.00215944 28.08550000 -6.01741951 -4.73644040 -8.23282826 +Si 1.15578948 1.06146065 1.46778145 28.08550000 5.46005398 5.26932004 6.55096738 +Si 0.19883126 2.69456369 3.05037240 28.08550000 -2.87752591 -1.20276024 -4.40923565 +Si 1.43769367 3.80694655 4.19339127 28.08550000 2.86363424 3.74603605 3.13024477 +Si 2.45502387 -0.05077321 2.80272576 28.08550000 1.53026761 -1.25071003 1.12808101 +Si 4.10952010 1.16750617 3.95340793 28.08550000 0.14196629 1.95876020 0.06150876 +Si 2.96338281 2.77424081 5.61254618 28.08550000 0.77426199 -0.31570832 0.98293735 +Si 4.34410155 4.51503629 7.41026410 28.08550000 0.30423709 -1.36049227 -1.52581755 +Si 2.51357646 3.00179707 0.12150420 28.08550000 0.59476686 -0.07358291 -0.45022664 +Si 4.69547243 4.12414812 1.03341673 28.08550000 -2.22881833 1.64509976 -1.10231007 +Si 2.59282641 5.18961519 2.65793072 28.08550000 1.87982451 -0.16896853 0.24404319 +Si 4.45439679 7.09313608 4.28216489 28.08550000 -3.83985844 -0.00344631 0.21373426 +Si 5.57429760 2.54365605 2.29668617 28.08550000 -2.65190466 1.31977011 3.71280249 +Si 6.49649511 4.51757131 4.16439230 28.08550000 1.60100637 -3.66638405 -1.41312096 +Si 5.64206700 5.83395094 5.60496281 28.08550000 -0.33690810 0.59281642 4.06936024 +Si 7.23540339 7.05156306 7.30714799 28.08550000 2.80241550 -1.75330978 -2.96014033 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2454.5137264724017 stress="-0.004353903702133758 0.02897430179844685 -0.025556918926379825 0.02897430179844685 -0.00934409067410697 0.03377626644673018 -0.025556918926379825 0.03377626644673018 0.01615222984562148" free_energy=-2454.5137264724017 pbc="T T T" +Si 0.08466326 0.28510385 0.11325986 28.08550000 0.01339493 -0.85939199 0.70435807 +Si 1.38790610 1.33474816 1.74790037 28.08550000 1.29307049 -0.24845521 -1.52000351 +Si -0.09634781 2.73118809 2.55600359 28.08550000 -1.21367354 1.11492030 2.55705230 +Si 1.07447616 4.27565165 4.34460625 28.08550000 1.36429031 -0.81750024 -2.05119522 +Si 2.53086503 -0.22345001 3.17389827 28.08550000 2.86934697 2.05414196 -2.42643229 +Si 4.55830535 1.34343864 3.99313931 28.08550000 -1.80711860 -1.29154300 0.15682983 +Si 3.14809605 2.94019139 4.96761224 28.08550000 -1.72840993 1.02252643 1.42544914 +Si 4.02939631 4.13358643 6.91262118 28.08550000 -1.47296569 -1.07891535 1.02746037 +Si 2.53265880 2.87711186 -0.41635318 28.08550000 14.66327029 -13.56705220 12.36090427 +Si 4.45675120 4.09444002 1.20986504 28.08550000 -1.85848152 0.71295275 0.04135799 +Si 2.64270071 5.83172699 2.46843603 28.08550000 0.74044556 -1.04166726 0.93520199 +Si 4.24969285 6.50821674 4.57046408 28.08550000 -1.03732132 1.22965449 -1.46967957 +Si 5.77125268 2.86305202 2.85559556 28.08550000 -1.10779295 0.45063082 -1.81463342 +Si 7.07602031 3.88455826 4.30728433 28.08550000 -13.43745317 12.03558696 -7.74577751 +Si 5.57755826 5.61417830 6.40452338 28.08550000 0.87365853 0.79355941 -1.73029301 +Si 6.93685909 7.46711196 6.75199804 28.08550000 1.84573965 -0.50944763 -0.45059945 +16 +Lattice="5.5960854350113 5.5960854350113 2.773929567943e-33 5.5960854350113 -4.9974918271642e-18 5.5960854350113 -1.2453714583215e-18 5.5960854350113 5.5960854350113" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2453.9615685899103 stress="0.00365151307958371 0.023755493565016172 -0.019190413597279132 0.023755493565016172 -0.048334574565885156 -0.009459778541350506 -0.019190413597279132 -0.009459778541350506 0.02204680212898266" free_energy=-2453.9615685899103 pbc="T T T" +Si -0.02081040 -0.04382839 0.51126462 28.08550000 1.20206784 1.20428233 -1.75051293 +Si 1.97278636 1.29380952 2.04159560 28.08550000 -6.20512058 12.92364418 -4.59914658 +Si 0.20522704 2.69433285 2.42978768 28.08550000 -0.96333295 0.94040719 2.43744818 +Si 1.31079070 4.29598760 4.40943125 28.08550000 0.71842766 -0.55526829 -0.52754202 +Si 2.72333565 -0.27635781 2.43116209 28.08550000 5.07314281 -11.11386886 5.87867611 +Si 4.42243086 1.25791266 4.10675219 28.08550000 -0.83565608 0.37363733 0.67141144 +Si 2.92863093 2.80683176 6.01481710 28.08550000 -3.74075784 -3.51479875 -4.01588053 +Si 4.17131458 4.15130625 6.94390684 28.08550000 4.65777956 1.31010817 0.21285314 +Si 2.84319030 2.95351191 0.00483921 28.08550000 -3.00830147 -2.29224205 1.40468491 +Si 4.04309593 4.06681989 1.28620971 28.08550000 1.73243602 1.66455247 1.05924486 +Si 2.92498230 5.49971721 2.54689759 28.08550000 -2.96060905 2.07551322 1.96861396 +Si 3.80203902 7.37553749 4.14221689 28.08550000 3.25015537 -3.36251592 -3.64643743 +Si 5.35738595 3.00754256 2.68648709 28.08550000 2.42686604 -2.12792182 1.60774755 +Si 7.28482207 4.36973844 4.42882053 28.08550000 -2.55513426 1.11941562 -2.35146432 +Si 5.39041140 5.64851971 5.34264208 28.08550000 -1.51330785 -0.91346255 -1.57591086 +Si 6.60122164 6.85947268 6.63402390 28.08550000 2.72134450 2.26851771 3.22621428 +16 +Lattice="5.7942903711489 5.7942903711489 -1.5315650115772e-18 5.7942903711489 -7.4018253850353e-33 5.7942903711489 -2.985959923497e-17 5.7942903711489 5.7942903711489" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2410.2912872044544 stress="-0.10191550209549706 0.08757020655729844 0.13051611371959376 0.08757020655729844 -0.056228894268741766 -0.08060414426541973 0.13051611371959376 -0.08060414426541973 -0.15919017795781334" free_energy=-2410.2912872044544 pbc="T T T" +Si 0.72889524 -0.29453960 -0.05030513 28.08550000 -1.45038884 0.59156866 2.07111072 +Si 1.26951372 1.81360294 1.96456360 28.08550000 1.45935479 -1.66568761 -0.78452070 +Si 0.15023416 3.61676154 2.63333057 28.08550000 -1.26046376 -0.84329817 0.10125775 +Si 1.46373635 3.56982003 4.16373634 28.08550000 0.99113608 -6.16388523 3.79615328 +Si 3.38449028 -0.48387252 2.69440925 28.08550000 -1.04558999 0.82229689 1.25029968 +Si 4.90628594 1.34909733 5.08652270 28.08550000 1.46118104 -0.95333367 -2.00655367 +Si 3.25168496 2.70275307 5.45444353 28.08550000 -1.42440553 0.34242363 1.56755966 +Si 4.72040496 4.17592639 6.92188339 28.08550000 -3.62258171 1.77305200 -4.41622417 +Si 3.46260228 2.68195140 -0.52319708 28.08550000 -71.47640682 45.35845895 86.39247106 +Si 4.03539032 4.56065933 1.90845890 28.08550000 0.20161459 -0.52486088 0.18328031 +Si 2.13673074 5.42732087 4.06575565 28.08550000 4.47483015 6.30798605 -1.90868051 +Si 4.13583356 8.04941296 4.45627387 28.08550000 70.30976415 -41.35751936 -86.98355790 +Si 5.50411680 2.83661843 2.97021515 28.08550000 0.46588414 0.12891922 0.40227454 +Si 7.02496120 4.65542400 4.30600409 28.08550000 0.08830634 -0.09969221 -0.57234915 +Si 4.61732793 6.16364153 5.14734872 28.08550000 1.20855216 -4.01410724 0.99097102 +Si 7.15069527 7.11832602 6.74346016 28.08550000 -0.38078706 0.29767923 -0.08349195 +16 +Lattice="5.801917626543 5.801917626543 1.2245245509546e-18 5.801917626543 -2.0408742515911e-18 5.801917626543 9.037450752094e-18 5.801917626543 5.801917626543" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2422.585318409383 stress="-0.061314569639074716 0.06729636690170682 0.15469855060419915 0.06729636690170682 0.010919649247042761 -0.09462992093218382 0.15469855060419915 -0.09462992093218382 -0.1511094722466199" free_energy=-2422.585318409383 pbc="T T T" +Si 0.54171368 -0.25541606 -0.21099336 28.08550000 -2.60978048 7.48569757 11.70391389 +Si 1.21911988 2.18865397 1.81318260 28.08550000 57.03639236 -29.41480347 -67.15921769 +Si 0.45498997 2.57826736 2.71407686 28.08550000 -57.68424915 29.32537228 67.66425254 +Si 1.03208130 4.79204697 4.05735124 28.08550000 4.37733160 -6.51643695 -13.07935070 +Si 2.45907195 0.14186595 2.33307852 28.08550000 0.75295783 -1.50407990 0.89792228 +Si 4.13511779 0.86651016 4.82675746 28.08550000 -0.19367966 0.73450297 -0.67396840 +Si 2.72918824 3.65813034 5.51532730 28.08550000 0.68091218 -0.66121547 0.86063563 +Si 4.55546974 4.41035740 7.68136415 28.08550000 -0.79176632 1.04667603 -0.88941116 +Si 2.96787698 2.50179570 0.31898498 28.08550000 1.18684974 1.14746301 -1.56827443 +Si 4.80588880 4.78942314 1.10438323 28.08550000 -2.08615965 -2.15721105 1.45476331 +Si 3.12232760 5.26122686 2.65951684 28.08550000 -0.28988519 1.42558104 0.54417320 +Si 4.73940090 7.21782160 4.40752161 28.08550000 -2.25458927 2.16608007 -1.35087095 +Si 5.33173025 2.94629738 3.24869098 28.08550000 0.53462027 -0.14528250 0.08098563 +Si 7.10861939 4.14015509 4.56027533 28.08550000 -0.22182629 0.13889408 -0.49449384 +Si 5.34946750 5.56129369 5.56806183 28.08550000 1.73163615 -3.08281923 2.32273045 +Si 7.46711228 7.22074671 7.42159668 28.08550000 -0.16876412 0.01158102 -0.31379028 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2330.0739724993714 stress="-0.3666736133860677 0.05089531632574408 -0.23138032527545704 0.05089531632574408 0.01909676151427246 0.028709872387604488 -0.23138032527545704 0.028709872387604488 -0.070450238520608" free_energy=-2330.0739724993714 pbc="T T T" +Si 0.10510432 -0.48532433 0.28134394 28.08550000 0.03386811 0.63478222 0.00156040 +Si 1.50794308 1.88406943 1.68355945 28.08550000 0.41201336 -0.84285697 -1.02341346 +Si 0.08697283 3.42990721 3.52533699 28.08550000 17.47936175 -13.84423665 11.30128942 +Si 1.03788501 4.99675670 4.37868693 28.08550000 2.51022557 4.35026431 2.16162101 +Si 3.54057166 -0.49867476 2.91412720 28.08550000 -0.36652952 -0.15188869 0.70224797 +Si 5.79287064 1.93285500 4.59303803 28.08550000 -0.60242437 -0.13311475 0.44348238 +Si 3.48618485 2.44935388 5.91236730 28.08550000 0.44514151 -0.18210121 -0.08680764 +Si 5.28253028 4.05966481 9.04248210 28.08550000 -19.83256619 11.00305329 -13.86390405 +Si 2.73025766 2.68374585 -0.57833881 28.08550000 -1.58524191 0.91404516 0.72661457 +Si 4.68531341 4.85087361 1.90512678 28.08550000 0.54187669 0.10019949 -0.59797585 +Si 2.91540679 6.50597407 3.02180506 28.08550000 -0.63739678 -0.10800022 0.13796745 +Si 4.93612842 7.78274351 5.41550135 28.08550000 -282.32864872 28.90605390 -142.22994158 +Si 6.83993747 3.43927535 2.83831104 28.08550000 -1.71021578 2.45361245 2.38675297 +Si 7.90259727 5.03515122 5.38852772 28.08550000 1.19003611 -1.37555174 -1.14189863 +Si 5.63304032 7.71170200 5.76722205 28.08550000 282.54415705 -29.11051213 142.91291758 +Si 7.59193089 8.29660135 7.98557777 28.08550000 1.90634338 -2.61374821 -1.83051306 +16 +Lattice="5.7942903711489 5.7942903711489 -1.5315650115772e-18 5.7942903711489 -7.4018253850353e-33 5.7942903711489 -2.985959923497e-17 5.7942903711489 5.7942903711489" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2429.61079923984 stress="-0.0540831597786771 -0.05511241453407397 0.09405699054202533 -0.05511241453407397 -0.009635146657568885 0.0828086408467827 0.09405699054202533 0.0828086408467827 -0.09038619615123439" free_energy=-2429.61079923984 pbc="T T T" +Si -0.53278753 -0.43587921 -0.35009745 28.08550000 2.09582031 -2.51812554 2.68048942 +Si 1.08926742 1.09341624 0.94859053 28.08550000 0.31241037 0.16514915 1.22641722 +Si 0.12547535 2.50784893 3.24810337 28.08550000 1.72685776 0.53371601 -1.31596308 +Si 1.87158925 4.66157897 4.20613010 28.08550000 -1.10720211 -1.67403650 0.99807755 +Si 2.53244195 -0.20871052 3.05166425 28.08550000 0.21569293 0.27757269 0.03931448 +Si 4.36298886 1.02955188 4.25112417 28.08550000 -2.27899110 3.68674230 -2.17874199 +Si 2.88548053 2.67304762 5.92649498 28.08550000 0.97809031 0.63197406 -1.18173093 +Si 4.76998469 4.84846941 6.26108398 28.08550000 -46.65608955 -34.30038328 52.38430265 +Si 3.49653233 2.76720223 0.41202900 28.08550000 0.45812970 -0.68480149 4.19093511 +Si 3.79606165 5.10765932 2.14215373 28.08550000 1.79805906 -2.08205437 -1.64965396 +Si 2.62547435 6.69337562 3.18659125 28.08550000 -1.58073940 0.19428926 0.79931097 +Si 4.19202965 7.50550583 4.45010357 28.08550000 1.85019460 -0.36343880 -0.11935395 +Si 5.77072775 3.29227895 2.70875207 28.08550000 -0.45095375 -0.77483844 -0.02796203 +Si 8.11072683 4.04303959 5.02919623 28.08550000 -1.96468325 2.48690206 -2.72132856 +Si 5.54416654 5.41368039 5.37270837 28.08550000 45.77418627 33.40641407 -51.97283179 +Si 7.30274408 6.95083848 7.09827556 28.08550000 -1.17078240 1.01491930 -1.15128136 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2438.5888236379246 stress="0.03142945542550414 -0.00015333233198151362 -0.01275596460011478 -0.00015333233198151362 -0.009607601927272806 -0.0016949190708854735 -0.01275596460011478 -0.0016949190708854735 0.024362395789206476" free_energy=-2438.5888236379246 pbc="T T T" +Si 0.52622646 0.04228970 -0.02542838 28.08550000 0.41230004 0.63618681 0.19759107 +Si 1.66579848 3.17916905 2.08398419 28.08550000 -2.20627593 -5.79401122 -6.52177482 +Si -0.72604973 3.10083124 2.87483599 28.08550000 -0.10337531 -0.17989443 -0.63452485 +Si 2.12910392 4.38764943 3.48049899 28.08550000 -0.32251840 -4.85298439 8.45592545 +Si 3.30573154 -0.19119576 2.39666900 28.08550000 -3.51263568 1.92491112 1.47844446 +Si 4.72594319 2.80136011 5.17514420 28.08550000 0.47288166 0.26507250 -0.05758911 +Si 3.11125020 2.54155602 7.79983591 28.08550000 1.02235339 0.07221200 0.06024763 +Si 4.79716455 5.15445128 7.86047382 28.08550000 2.09197368 -2.91693732 -0.95840928 +Si 3.15516651 2.35663645 -0.63084587 28.08550000 -0.61323843 -0.33092334 0.16152724 +Si 4.53443505 5.12547030 2.13323729 28.08550000 0.70248451 -0.40785923 0.17286323 +Si 2.61753732 6.14071933 3.08095261 28.08550000 7.67279983 6.28635793 1.84734916 +Si 5.95281429 7.76564141 4.74755846 28.08550000 -0.81591849 0.24550590 -0.50426300 +Si 6.61389239 3.14420617 3.25675549 28.08550000 -0.60003788 0.30292146 1.03067888 +Si 7.71486281 5.08919377 4.76963849 28.08550000 -0.19181123 -0.60936815 -0.55738173 +Si 6.27548276 6.27689909 6.52626977 28.08550000 1.15539821 0.25043239 0.03781013 +Si 7.67531516 7.15979731 8.54509494 28.08550000 -5.16437969 5.10837798 -4.20849497 +16 +Lattice="6.1031963288446 6.1031963288446 -2.2059334076153e-16 6.1031963288446 -1.8048546062307e-16 6.1031963288446 9.506742391508e-18 6.1031963288446 6.1031963288446" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2427.3878901690937 stress="-0.08867658655752433 -0.09971192367181063 -0.03775464365916071 -0.09971192367181063 -0.03427298974973616 -0.00822577462408611 -0.03775464365916071 -0.00822577462408611 0.04515224005901134" free_energy=-2427.3878901690937 pbc="T T T" +Si -0.48578113 -0.21930742 -0.38574261 28.08550000 0.88971789 -0.22200756 1.02486433 +Si 1.45777183 1.14618362 1.57212115 28.08550000 0.11649051 0.54688520 -0.70132751 +Si -0.14560557 3.38736430 2.37564298 28.08550000 7.96002136 -3.99564595 6.38396497 +Si 1.52871448 4.59310519 4.76993630 28.08550000 -0.98708454 1.61073774 -1.29693281 +Si 3.51607046 -0.07359991 2.67770326 28.08550000 -0.88513542 -0.10264718 0.33653169 +Si 4.79619387 1.86457969 4.69393061 28.08550000 -0.60890741 -0.44056238 -0.55922341 +Si 2.85896014 3.05949978 5.92288511 28.08550000 0.72560078 -1.12891327 0.60229170 +Si 4.48850699 3.94601160 7.42841931 28.08550000 -7.20087977 4.38267770 -5.15753927 +Si 2.83280027 3.11845917 0.67240625 28.08550000 0.58849054 -0.58849491 0.24995236 +Si 4.75897532 3.94043995 2.33139289 28.08550000 -3.00578410 0.83180071 -1.90362804 +Si 2.79382366 6.18165879 3.14549404 28.08550000 1.30393186 -0.94470145 0.85694610 +Si 4.76902023 8.00238914 4.40844842 28.08550000 -0.57867998 -0.66258690 -0.03393805 +Si 6.52183768 3.51555009 3.63522937 28.08550000 -55.39500784 -50.78649421 -5.50659403 +Si 7.50300651 4.38765693 3.74587523 28.08550000 57.64853936 51.16910727 6.73347379 +Si 5.80610435 6.15582383 5.92744589 28.08550000 -0.17666255 0.09788241 -0.31649225 +Si 8.03156419 8.02614854 8.11077508 28.08550000 -0.39465070 0.23296277 -0.71234932 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2405.3479286448196 stress="-0.11614970055483481 -0.034073749533927854 -0.1095196839725683 -0.034073749533927854 -0.037037562513786086 -0.010203486259344675 -0.1095196839725683 -0.010203486259344675 -0.11054434793958247" free_energy=-2405.3479286448196 pbc="T T T" +Si -0.73206463 -0.71743781 0.29722836 28.08550000 3.73828649 23.04579409 -12.30685223 +Si 1.98146883 2.01274992 1.44822625 28.08550000 0.11539805 0.19073034 0.57421217 +Si -0.75488951 3.72737992 2.55799667 28.08550000 1.08431723 -1.37012080 1.19882285 +Si 1.47738631 4.86863076 4.73296201 28.08550000 0.04797858 0.00715795 -0.42154110 +Si 3.62312940 0.20868161 3.20580344 28.08550000 -0.13715730 0.28500601 -1.03776998 +Si 5.65260815 2.24930032 5.02556291 28.08550000 -0.32319100 -0.15002901 0.74812339 +Si 2.62295398 2.73162573 7.15121174 28.08550000 0.01768173 0.51517913 -0.20415664 +Si 4.69188596 5.23741966 7.52501440 28.08550000 -3.71286368 -1.85515195 2.04672484 +Si 4.15096075 4.26440213 0.51200833 28.08550000 -43.87578246 0.00354709 -15.70238702 +Si 5.53730832 4.22714728 1.03431721 28.08550000 40.09552939 -23.00878383 27.29030945 +Si 3.47509839 5.97958544 3.17220506 28.08550000 -0.72511896 -0.31233375 0.62782199 +Si 5.70831102 7.95795070 4.58900046 28.08550000 -0.33051145 0.16043555 -1.03685467 +Si 6.11848999 3.52009701 3.19713728 28.08550000 0.52826579 -0.15402373 -0.37897777 +Si 7.41749027 4.48765860 4.85746195 28.08550000 -0.25963565 -0.03425815 0.35378970 +Si 6.21582898 6.45581316 6.84058842 28.08550000 -31.99885390 -19.04380138 -58.74920521 +Si 6.88870868 6.86367049 7.92795042 28.08550000 35.73565738 21.72065294 56.99794022 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2439.0065191902327 stress="0.005910180963862292 0.0023596652286975443 -0.00982061450822916 0.0023596652286975443 0.021435309116409677 0.01782694944762316 -0.00982061450822916 0.01782694944762316 0.038199950132280676" free_energy=-2439.0065191902327 pbc="T T T" +Si 0.02349267 0.74208436 0.00375149 28.08550000 -0.28248376 -0.49391431 -0.41703935 +Si 2.13617596 1.51328062 0.65967981 28.08550000 -0.30032336 -1.77862023 1.49509389 +Si -0.31959234 2.26683092 3.18888896 28.08550000 0.91763005 0.66458311 -0.82427458 +Si 1.42363570 4.66349914 4.86604503 28.08550000 -7.99131683 -2.87041860 -0.28843818 +Si 2.64165646 0.28617829 3.41498194 28.08550000 -0.00822702 0.47912687 -0.51288982 +Si 5.79253994 1.94001614 4.32400978 28.08550000 0.16079653 -0.18154482 0.23283036 +Si 2.34726900 3.22124150 6.04484085 28.08550000 1.16065688 -3.09402796 2.00912348 +Si 5.15219795 4.94099246 7.91162079 28.08550000 0.07443601 -0.14605768 0.09236637 +Si 2.74097159 3.38513412 -0.30977992 28.08550000 11.54701541 -4.72609814 5.64644173 +Si 4.64535136 4.34242541 1.52456158 28.08550000 0.22880787 0.53166556 0.04296982 +Si 2.86316256 5.86502527 4.54013092 28.08550000 6.37349004 6.46772226 -2.01039747 +Si 4.43526327 8.03436143 4.59754601 28.08550000 -1.23137019 -0.72207349 1.00681956 +Si 6.88956441 3.60203504 2.99968819 28.08550000 0.11739554 -0.64483343 0.07015049 +Si 7.75961094 4.17215783 5.25078582 28.08550000 -10.73757738 6.02082725 -6.58536874 +Si 6.78759739 7.48441903 6.05374392 28.08550000 0.00635397 0.21634907 -0.59768120 +Si 8.75577804 7.61499332 9.00417972 28.08550000 -0.03528376 0.27731455 0.64029415 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2403.233017609338 stress="-0.09598787613578057 0.11502587555875472 -0.1267645214532676 0.11502587555875472 -0.05899713966349783 0.091740478724125 -0.1267645214532676 0.091740478724125 -0.05592222960477874" free_energy=-2403.233017609338 pbc="T T T" +Si 0.41465251 0.53168136 -0.39806273 28.08550000 -0.43687516 -0.64759943 -0.29582495 +Si 1.75362392 1.06221125 2.67435201 28.08550000 -28.38468766 0.75455757 -45.26765967 +Si 0.83806901 2.08618099 2.21717500 28.08550000 -32.43687448 37.01759808 -17.29018589 +Si 0.97790135 4.65150216 5.04175864 28.08550000 0.27619124 0.45743447 0.98463711 +Si 2.56197987 0.56765015 3.48864678 28.08550000 59.10045646 -37.45261767 60.90767379 +Si 4.44653478 1.38245637 4.28733871 28.08550000 2.51500088 1.20914917 2.03868063 +Si 3.10711610 3.11566608 6.73320962 28.08550000 -0.38074695 0.04239158 0.15936726 +Si 4.76888731 4.62959067 8.41028526 28.08550000 -0.46449163 -1.22364428 -0.29614351 +Si 2.73584669 3.25963879 0.12010081 28.08550000 0.10764643 0.05090476 -0.40345365 +Si 5.41366786 4.85548111 1.67208005 28.08550000 -0.03422035 0.04183673 0.02522972 +Si 3.19406565 7.03233127 3.51474403 28.08550000 -0.31917468 0.54470388 0.07109846 +Si 4.78302386 8.70360813 5.14857926 28.08550000 -1.02418864 0.05677304 -0.28905318 +Si 6.27768950 3.22685481 3.36563412 28.08550000 -1.31005417 -1.90845040 -1.36782275 +Si 7.68751029 4.84164594 3.88627974 28.08550000 0.97000265 -0.13660862 -0.17578915 +Si 7.48762164 6.10137768 5.72161322 28.08550000 0.46639888 0.69101019 1.05971897 +Si 7.62648454 8.02679815 8.19094037 28.08550000 1.35561721 0.50256093 0.13952708 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2402.9600543714973 stress="-0.0013047020583576696 -0.08412344263958227 -0.06461718280157476 -0.08412344263958227 -0.09984781100793796 -0.11213000624696016 -0.06461718280157476 -0.11213000624696016 -0.08242393278031411" free_energy=-2402.9600543714973 pbc="T T T" +Si 0.02392916 -0.57441802 -0.11741649 28.08550000 0.10702808 0.21961514 -0.55190091 +Si 0.51495349 2.57925770 1.11187053 28.08550000 0.57776775 0.31292588 -0.11559705 +Si -0.65927825 3.80163560 3.68669728 28.08550000 0.66291883 -0.09915151 -0.28979829 +Si 2.03314515 4.62799293 4.90930217 28.08550000 -1.18874439 -0.06717110 0.77356651 +Si 3.20576484 0.34518736 2.74820343 28.08550000 0.53465678 -0.33958436 0.36933639 +Si 5.73632811 1.21872342 4.64300238 28.08550000 -0.11604623 -0.47836093 0.25324183 +Si 3.35715493 3.13574704 7.06873178 28.08550000 4.30107937 8.75633931 -4.44881315 +Si 4.39074275 4.76325482 8.32476684 28.08550000 0.50107175 0.86780078 0.54611670 +Si 2.98045459 3.46088306 0.35607377 28.08550000 -1.00872834 0.80297659 0.22004735 +Si 4.69635309 5.07441965 2.00312669 28.08550000 2.49907110 -5.04071143 -6.99928060 +Si 3.98615960 6.18169169 3.43510925 28.08550000 -51.19443109 -74.59598460 -71.65680262 +Si 4.44703931 6.93148464 4.16515195 28.08550000 46.73129689 79.10264012 73.88454314 +Si 6.85773592 2.28328595 2.79406237 28.08550000 -0.01014789 0.09277440 -0.29906609 +Si 7.97132172 5.30005157 5.39121615 28.08550000 0.07370838 0.07297922 0.40101084 +Si 5.61518190 6.91763104 5.84600623 28.08550000 3.09521889 -0.64504966 4.07000559 +Si 8.91768859 8.02784646 7.70877058 28.08550000 -5.56572040 -8.96203784 3.84339036 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2360.9545105946117 stress="-0.14387898054389886 -0.11944313214056947 0.15430833359167137 -0.11944313214056947 -0.08067300609115993 0.12817297532907387 0.15430833359167137 0.12817297532907387 -0.09013186647483391" free_energy=-2360.9545105946117 pbc="T T T" +Si -0.27550681 -1.13794851 -0.23088378 28.08550000 -21.23581180 3.63777230 10.79107664 +Si 1.61888498 1.64729580 1.40069110 28.08550000 0.38961185 0.45955383 0.61040096 +Si 0.67925488 3.44719754 3.08056804 28.08550000 -0.05789276 -0.16436137 -0.05453644 +Si 1.20386283 4.99595953 5.48670772 28.08550000 21.41973669 -4.69104269 -10.21635847 +Si 2.66574943 -0.52780401 3.70755808 28.08550000 0.95816297 1.11772178 -1.94890954 +Si 5.53900601 2.35077465 4.27804853 28.08550000 -132.00691187 -130.02984618 130.53956763 +Si 3.91315335 3.48516956 6.01116969 28.08550000 -0.45580310 1.43465317 1.02275525 +Si 4.18974210 5.12157135 8.21493051 28.08550000 0.20243915 -0.83455513 -0.19013102 +Si 3.48531782 3.24931642 -0.30220206 28.08550000 -0.39301188 0.35473895 0.14997245 +Si 4.89685507 5.05262316 2.17151553 28.08550000 0.14851257 0.16729834 -0.76841685 +Si 3.70251256 6.48175460 3.98706245 28.08550000 1.13406165 -0.01878782 -0.13511018 +Si 5.32731875 8.51947307 3.81408253 28.08550000 -0.95868259 -0.44754575 0.69941075 +Si 6.06171102 2.86533646 3.76224988 28.08550000 132.05192571 129.61391214 -131.07969058 +Si 7.86029257 4.89876920 5.22372044 28.08550000 0.71879019 -1.31781839 0.98065858 +Si 5.86673712 5.45298827 6.24057726 28.08550000 -1.52054910 0.79934568 0.39004431 +Si 7.33978320 8.17219780 7.22887897 28.08550000 -0.39457743 -0.08103911 -0.79073325 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2434.4651224249383 stress="0.04350506518730574 0.006864146789783207 -0.003201615818081066 0.006864146789783207 0.04183585453136327 0.0007905337594975042 -0.003201615818081066 0.0007905337594975042 0.052216545222279406" free_energy=-2434.4651224249383 pbc="T T T" +Si -0.57955835 -0.36248760 0.57020284 28.08550000 1.04150117 0.65954760 -0.85380370 +Si 1.36791143 1.60356552 1.90951163 28.08550000 0.77722699 -0.15258314 0.20272171 +Si 0.50611592 3.60256839 2.83791322 28.08550000 -0.16800436 -0.40225448 0.22275729 +Si 0.76896246 6.50857869 5.22220664 28.08550000 1.15138214 -2.14119000 0.99329890 +Si 3.22772791 0.11240252 3.39815051 28.08550000 -0.90197537 -0.02727966 0.05411118 +Si 6.50142594 1.07084403 4.86209961 28.08550000 -1.74834164 1.65762592 -0.27855023 +Si 2.61405687 2.99234389 6.56159704 28.08550000 -0.59118377 -0.68603819 1.39726368 +Si 5.78816155 4.85672686 9.03302482 28.08550000 0.38197953 0.72066786 0.04563348 +Si 3.09542959 3.27391360 0.60274731 28.08550000 -0.01941106 0.22980237 -0.49929177 +Si 5.18365467 4.85802421 1.19377608 28.08550000 -0.32716824 -0.27635862 1.43857950 +Si 4.38409580 6.40594665 3.78886736 28.08550000 0.42408238 0.47777729 -0.57832517 +Si 5.34558456 9.43686999 5.06655119 28.08550000 -0.09290321 -0.52658146 -0.24870538 +Si 7.33256978 4.27998314 3.13253935 28.08550000 0.50202820 -0.13138851 0.14059435 +Si 8.34990029 5.22624845 5.31926532 28.08550000 -0.02522278 0.39294812 -0.45464611 +Si 7.23353788 7.22920178 7.61138349 28.08550000 0.38997052 -0.30679585 -0.24640655 +Si 9.23877775 9.26362392 9.24851766 28.08550000 -0.79396024 0.51210075 -1.33523144 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2434.6027819566198 stress="0.04089290659756079 -0.004034384830699226 -0.012519998077245026 -0.004034384830699226 0.04549471287235927 -0.003972868266371313 -0.012519998077245026 -0.003972868266371313 0.04350322887195267" free_energy=-2434.6027819566198 pbc="T T T" +Si 0.89865276 0.53668256 0.34196990 28.08550000 -0.09759959 0.61078766 -0.17308640 +Si 1.57635407 2.74836976 1.89599867 28.08550000 -0.06856901 -0.18107019 -0.89771325 +Si -0.01398592 4.16059445 3.37746397 28.08550000 2.25615867 0.04985703 2.29048547 +Si 1.28659602 5.42030637 5.09657648 28.08550000 1.06771408 0.13626615 -0.15426156 +Si 3.02005006 -0.52759389 3.79964038 28.08550000 -0.47137422 -0.74631513 -0.14982255 +Si 6.23313639 2.39030390 4.93403871 28.08550000 1.07469102 0.70663813 0.11105777 +Si 2.98024188 3.15819547 6.59281994 28.08550000 0.06808204 0.25484260 -0.08484563 +Si 5.45868613 4.03469631 9.02011114 28.08550000 -2.17652312 0.55467462 -2.27262402 +Si 3.73536104 3.60104524 0.30194672 28.08550000 -1.90231035 -1.16743380 -2.04187188 +Si 4.81974431 4.91295216 1.57580555 28.08550000 1.31933148 1.44191037 2.14118254 +Si 3.25027698 6.73292289 3.74627242 28.08550000 -0.35127902 -0.24209738 -0.41534474 +Si 5.12251116 9.80149926 5.24488355 28.08550000 -0.17056441 0.03382929 0.07241538 +Si 7.72369924 3.60240249 2.62780150 28.08550000 -0.16634677 -0.51859613 0.40944663 +Si 8.45949760 4.51525978 6.37455945 28.08550000 -0.47836402 0.08393186 0.11354891 +Si 6.47312145 6.42959162 7.06854995 28.08550000 0.87460032 -1.45143708 0.26183086 +Si 9.33441088 8.84112569 8.35991572 28.08550000 -0.77764711 0.43421175 0.78960248 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2433.3553575804203 stress="0.04363452541969731 0.0015296506891089921 -0.002871079054528102 0.0015296506891089921 0.029171705698902095 -0.004208834789241067 -0.002871079054528102 -0.004208834789241067 0.048219804856318146" free_energy=-2433.3553575804203 pbc="T T T" +Si 0.57955835 0.36248760 -0.57020284 28.08550000 0.61038528 0.93194903 0.39515387 +Si 2.15000627 1.91435219 1.60840608 28.08550000 0.04034909 -0.82614146 -0.72905274 +Si -0.50611592 3.43326701 4.19792219 28.08550000 -0.42242170 -0.75537853 0.74769504 +Si 2.74895524 4.04517442 5.33154647 28.08550000 -1.84114946 2.06953155 -0.06874513 +Si 3.80810749 -0.11240252 3.63768490 28.08550000 -0.64353528 -0.14279007 -0.53199466 +Si 4.05232716 2.44707367 5.69165350 28.08550000 2.39272744 -1.85055096 0.43388985 +Si 4.42177854 4.04349151 7.51007377 28.08550000 -1.27061885 -4.23598778 -3.33189305 +Si 4.76559156 5.69702625 8.55656370 28.08550000 0.93398021 4.36912156 2.69997658 +Si 3.94040582 3.76192180 -0.60274731 28.08550000 -0.39765169 -0.02558222 -0.12586732 +Si 5.37009843 5.69572890 2.32414162 28.08550000 -0.30270471 -0.15030206 0.13264347 +Si 2.65173960 7.66572416 3.24696805 28.08550000 -0.23126970 0.02146074 -0.39695055 +Si 5.20816855 8.15271852 5.48720192 28.08550000 -0.21930327 1.65738295 -0.88925330 +Si 6.73910103 2.75585226 3.90329606 28.08550000 0.13093214 -0.28275475 0.06795348 +Si 9.23968822 5.32750466 5.23448779 28.08550000 0.65950261 -0.08924685 -0.09690282 +Si 6.83813293 6.84246904 6.46028732 28.08550000 0.76659471 -0.24142016 1.14394111 +Si 8.35081076 8.32596459 8.34107085 28.08550000 -0.20581706 -0.44929127 0.54940643 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2435.595583703481 stress="0.04294498900461878 0.01302039401095715 0.0004397975270607486 0.01302039401095715 0.04106276576771995 -0.002725091983958876 0.0004397975270607486 -0.002725091983958876 0.04061470482157038" free_energy=-2435.595583703481 pbc="T T T" +Si 0.70524047 0.38415180 0.08148722 28.08550000 -0.52084327 -1.24207189 -0.64256983 +Si 2.06730299 1.71760786 1.74438248 28.08550000 -0.19909980 -0.35327111 0.22275935 +Si -0.27191870 2.73423586 3.45658295 28.08550000 0.01410456 0.08885861 0.14668478 +Si 1.03655303 5.93083886 4.97384041 28.08550000 -0.14813719 0.59616888 1.20152662 +Si 3.49238049 -0.22301412 3.57262047 28.08550000 0.04025345 0.90754721 -0.29805693 +Si 4.71699484 1.32399937 5.14758958 28.08550000 0.30760549 0.61394934 0.10161180 +Si 4.28662304 3.88935947 6.52660624 28.08550000 1.05853910 -0.17901717 -1.03769876 +Si 5.29963531 5.89488800 9.14244180 28.08550000 0.27448120 -0.42291612 -0.24895169 +Si 4.25087817 3.26475396 0.10289339 28.08550000 -3.71218183 5.61091783 5.73332805 +Si 5.78460002 5.66783104 0.78613219 28.08550000 0.37066642 0.39587609 -0.17872355 +Si 4.62913479 6.72892719 4.01512826 28.08550000 0.75921333 -0.05270710 0.83245300 +Si 5.09565662 9.09273908 5.95134519 28.08550000 4.68706057 -6.27244415 -6.06895342 +Si 6.64999681 3.66447857 4.39156198 28.08550000 -0.81024047 0.62177681 1.00396229 +Si 8.16060346 5.48708347 5.44571217 28.08550000 -0.90468763 -0.32989053 -0.42518229 +Si 6.54196529 6.48956638 7.00961143 28.08550000 -0.02599642 0.60535363 0.28209321 +Si 7.91270743 8.31090727 8.01041830 28.08550000 -1.19073725 -0.58813007 -0.62428261 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2431.7415473004903 stress="0.028185604354302424 -0.005450183967917752 0.008415833263129065 -0.005450183967917752 0.04853106030866385 0.004946115403499483 0.008415833263129065 0.004946115403499483 0.0474715063499413" free_energy=-2431.7415473004903 pbc="T T T" +Si 0.07095469 0.29993400 -0.70555065 28.08550000 0.64416032 0.32649153 0.09885249 +Si 2.35113231 1.22796908 1.02987174 28.08550000 -0.63511955 0.22528314 -0.23460802 +Si 0.16021579 2.74231170 3.21537608 28.08550000 -0.12993764 -0.01882330 0.99554270 +Si 1.72738224 4.27914900 5.85990028 28.08550000 -0.39320446 0.00298659 0.04479453 +Si 4.97850558 -0.31660106 3.27040047 28.08550000 0.13191533 0.21176479 -0.42946935 +Si 5.11510831 1.93490388 5.76093768 28.08550000 0.72412677 -0.09620862 -0.31476319 +Si 3.24730229 2.88419540 8.24960590 28.08550000 8.84246766 2.53860283 -5.05298691 +Si 5.42056659 5.01486275 7.53115836 28.08550000 -0.03334361 0.47744434 0.31284823 +Si 4.41528032 3.86631733 -0.01846944 28.08550000 0.27236132 -0.72529842 0.07425526 +Si 5.64141722 5.27923865 2.25531945 28.08550000 -0.58598397 0.07737323 -1.42341951 +Si 2.25296412 6.90955081 3.25146680 28.08550000 -0.35953869 0.77998347 -0.01733669 +Si 5.41486710 9.14716701 5.32258721 28.08550000 0.96791517 0.50822584 0.44008492 +Si 6.02802337 4.28238157 4.18533432 28.08550000 0.66957002 -0.62148422 1.87020961 +Si 8.35946085 5.87552538 5.41700525 28.08550000 -1.68603018 0.11893794 0.22359855 +Si 6.55256017 7.41410449 6.74878269 28.08550000 0.14196629 -0.84893274 -0.63317117 +Si 8.62261310 9.51734408 8.98462792 28.08550000 -8.57132453 -2.95634641 4.04556854 +16 +Lattice="6.4074674897604 6.4074674897604 1.6278872974275e-33 6.4074674897604 -7.5277524854744e-17 6.4074674897604 -8.8052005833919e-17 6.4074674897604 6.4074674897604" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2442.672860585995 stress="0.03541242342631736 -0.01678024969637211 -0.01865329135650557 -0.01678024969637211 0.04417991107955971 -0.012890933778565575 -0.01865329135650557 -0.012890933778565575 0.041924915825987265" free_energy=-2442.672860585995 pbc="T T T" +Si 0.19227550 -1.39251812 -0.04612123 28.08550000 0.15469942 0.18248404 -1.21272558 +Si 1.51535816 1.45899574 2.02999565 28.08550000 0.79346916 0.05499795 0.39739690 +Si -0.69059021 4.01110276 3.52932286 28.08550000 0.04942226 -0.05903947 0.45433963 +Si 1.30811747 5.31003655 3.94190092 28.08550000 -0.35131142 -0.35433298 1.03711204 +Si 3.68801370 -0.37678289 3.42961395 28.08550000 -2.78330963 -1.66946971 -1.78196421 +Si 4.95451809 0.90951400 4.50630273 28.08550000 2.71730890 2.13991627 1.17571661 +Si 3.63665996 3.91975336 5.80912399 28.08550000 -0.33184122 0.47873606 -0.72868919 +Si 5.49893561 5.82990715 8.28487641 28.08550000 0.09922118 0.24296076 -0.07362765 +Si 3.53528313 3.42653287 -0.11314724 28.08550000 -0.35822614 -0.07773216 0.14069950 +Si 4.02822911 4.15531821 2.34104917 28.08550000 0.05875356 -0.31043525 -0.09633075 +Si 3.35739945 6.30166691 3.30540093 28.08550000 -5.15457453 -3.46698266 -3.92160255 +Si 4.67419479 7.27431442 4.34397319 28.08550000 2.49072735 4.45254048 2.23178616 +Si 6.16363905 3.25531143 3.41948118 28.08550000 0.30526682 -0.65685488 0.31415821 +Si 7.77815826 4.47683412 5.10408858 28.08550000 0.01244440 0.42255000 -0.44035129 +Si 6.29862432 6.95381404 5.61956440 28.08550000 2.90094377 -1.35044440 2.38161231 +Si 8.13585850 8.56087435 8.56924943 28.08550000 -0.60299336 -0.02889406 0.12246987 +16 +Lattice="7.0358354059119 7.0358354059119 -2.2429499964953e-16 7.0358354059119 -2.2429499964953e-16 7.0358354059119 1.5460404463316e-17 7.0358354059119 7.0358354059119" Properties=species:S:1:pos:R:3:masses:R:1:forces:R:3 energy=-2434.158186863315 stress="0.054138249239269264 0.002506570456943306 0.002386291801317089 0.002506570456943306 0.046410116075865676 -0.00369283017502783 0.002386291801317089 -0.00369283017502783 0.05608015272514293" free_energy=-2434.158186863315 pbc="T T T" +Si -0.89865276 -0.53668256 -0.34196990 28.08550000 -0.30945437 -0.20629066 0.46287235 +Si 1.94156363 0.76954794 1.62191903 28.08550000 0.60785763 0.00867259 0.79330384 +Si 0.01398592 2.87524096 3.65837143 28.08550000 0.17393281 -0.99717278 0.72276357 +Si 2.23132168 5.13344674 5.45717663 28.08550000 0.36811486 -0.18393415 0.46785695 +Si 4.01578535 0.52759389 3.23619503 28.08550000 -1.22233045 0.22070915 0.93234987 +Si 4.32061672 1.12761380 5.61971440 28.08550000 0.54818618 -0.12098583 -0.30880260 +Si 4.05559353 3.87763994 7.47885087 28.08550000 -0.53086800 0.85881452 -0.86845924 +Si 5.09506697 6.51905680 8.56947737 28.08550000 0.23944426 -0.63481770 -1.43443926 +Si 3.30047437 3.43479017 -0.30194672 28.08550000 0.40375369 -0.28069247 0.00711553 +Si 5.73400880 5.64080095 1.94211215 28.08550000 -0.65984122 0.44269048 0.06822654 +Si 3.78555843 7.33874793 3.28956299 28.08550000 0.51097975 -0.56528299 0.52900627 +Si 5.43124195 7.78808925 5.30886956 28.08550000 0.19819143 0.90569859 -0.37272433 +Si 6.34797157 3.43343292 4.40803391 28.08550000 0.01793344 -0.07730381 -0.74898831 +Si 9.13009092 6.03849333 4.17919365 28.08550000 0.36429163 0.91895159 -0.14345161 +Si 7.59854936 7.64207919 7.00312087 28.08550000 -0.61542336 0.04616364 0.13910619 +Si 8.25517763 8.74846282 9.22967279 28.08550000 -0.09476778 -0.33521991 -0.24573549 diff --git a/Examples/sscha_and_aiida/get_sgp.py b/Examples/sscha_and_aiida/get_sgp.py index e0bb4bd5..6de6d2c9 100644 --- a/Examples/sscha_and_aiida/get_sgp.py +++ b/Examples/sscha_and_aiida/get_sgp.py @@ -8,21 +8,21 @@ from ase.build import make_supercell # Define kernel. -sigma = 2.0 -power = 1.0 -dotprod_kernel = DotProduct(sigma, power) -normdotprod_kernel = NormalizedDotProduct(sigma, power) +sigma_ = 2.0 +power_ = 2.0 +dotprod_kernel_ = DotProduct(sigma_, power_) +normdotprod_kernel_ = NormalizedDotProduct(sigma_, power_) # Define remaining parameters for the SGP wrapper. -sigma_e = 0.005 -sigma_f = 0.01 -sigma_s = 0.001 -species_map = {6: 0, 8: 1} -single_atom_energies = {0: 0, 1: 0} -variance_type = "local" -max_iterations = 40 -opt_method = "L-BFGS-B" -bounds = [(None, None), (sigma_e, None), (None, None), (None, None)] +sigma_e_ = 0.01 +sigma_f_ = 0.1 +sigma_s_ = 0.005 +species_map_ = {6: 0, 8: 1} +single_atom_energies_ = {0: 0, 1: 0} +variance_type_ = "local" +max_iterations_ = 100 +opt_method_ = "L-BFGS-B" +bounds_ = [(None, None), (sigma_e_, None), (None, None), (None, None)] def get_atoms(a=2.0, sc_size=2, numbers=[6, 8]) -> Atoms: @@ -69,9 +69,9 @@ def get_empty_sgp( the_atom_energies=None, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: """Return an empty SGP model.""" if kernel_type == "NormalizedDotProduct": - kernel = normdotprod_kernel + kernel = normdotprod_kernel_ elif kernel_type == "DotProduct": - kernel = dotprod_kernel + kernel = dotprod_kernel_ kernel.power = power @@ -95,22 +95,22 @@ def get_empty_sgp( cutoff_matrix, ) - species_map = species_map if the_map is None else the_map - single_atom_energies = single_atom_energies if the_map is None else the_atom_energies + species_map = species_map_ if the_map is None else the_map + single_atom_energies = single_atom_energies_ if the_map is None else the_atom_energies empty_sgp = SGP_Wrapper( [kernel], [b2_calc], cutoff, - sigma_e, - sigma_f, - sigma_s, + sigma_e_, + sigma_f_, + sigma_s_, species_map, single_atom_energies=single_atom_energies, - variance_type=variance_type, - opt_method=opt_method, - bounds=bounds, - max_iterations=max_iterations, + variance_type=variance_type_, + opt_method=opt_method_, + bounds=bounds_, + max_iterations=max_iterations_, ) return empty_sgp diff --git a/Examples/sscha_and_aiida/log2 b/Examples/sscha_and_aiida/log2 new file mode 100644 index 00000000..ed873e6c --- /dev/null +++ b/Examples/sscha_and_aiida/log2 @@ -0,0 +1,3460 @@ +Number of symmetry inequivalent displacements: 1 +[BFFS USED] For structure with id=0 +[BFFS USED] For structure with id=1 +[BFFS USED] For structure with id=2 +[BFFS USED] For structure with id=3 +[BFFS USED] For structure with id=4 +[BFFS USED] For structure with id=5 +[BFFS USED] For structure with id=6 +[BFFS USED] For structure with id=7 +[BFFS USED] For structure with id=8 +[BFFS USED] For structure with id=9 +[BFFS USED] For structure with id=10 +[BFFS USED] For structure with id=11 +[BFFS USED] For structure with id=12 +[BFFS USED] For structure with id=13 +[BFFS USED] For structure with id=14 +[BFFS USED] For structure with id=15 +[BFFS USED] For structure with id=16 +[BFFS USED] For structure with id=17 +[BFFS USED] For structure with id=18 +[BFFS USED] For structure with id=19 +[BFFS USED] For structure with id=20 +[BFFS USED] For structure with id=21 +[BFFS USED] For structure with id=22 +[BFFS USED] For structure with id=23 +[BFFS USED] For structure with id=24 +[BFFS USED] For structure with id=25 +[BFFS USED] For structure with id=26 +[BFFS USED] For structure with id=27 +[BFFS USED] For structure with id=28 +[BFFS USED] For structure with id=29 +[BFFS USED] For structure with id=30 +[BFFS USED] For structure with id=31 +[BFFS USED] For structure with id=32 +[BFFS USED] For structure with id=33 +[BFFS USED] For structure with id=34 +[BFFS USED] For structure with id=35 +[BFFS USED] For structure with id=36 +[BFFS USED] For structure with id=37 +[BFFS USED] For structure with id=38 +[BFFS USED] For structure with id=39 +[BFFS USED] For structure with id=40 +[BFFS USED] For structure with id=41 +[BFFS USED] For structure with id=42 +[BFFS USED] For structure with id=43 +[BFFS USED] For structure with id=44 +[BFFS USED] For structure with id=45 +[BFFS USED] For structure with id=46 +[BFFS USED] For structure with id=47 +[BFFS USED] For structure with id=48 +[BFFS USED] For structure with id=49 +=============== SUMMARY AIIDA CALCULATIONS =============== + +Total structures included: 50 +Structures not included : 0 +Steps using OTF-ML model : 50 + +===================== END OF SUMMARY ===================== + + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 1 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 109.20798851 meV +Anharmonic contribution to free energy = -308482.51006196 +- 0.42441910 meV +Free energy = -308373.30207344 +- 0.42441910 meV +FC gradient modulus = 31144.73750721 +- 704.31850696 bohr^2 +Struct gradient modulus = 0.00000000 +- 3.17358501 meV/A +Kong-Liu effective sample size = 43.76599535119353 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 2 +Minimization step, force computed: 50 +Step too large (scalar = 4.381110719001629 | kl_ratio = 0.875319907023871), reducing to 0.1310370697125 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 110.39283626 meV +Anharmonic contribution to free energy = -308483.77130987 +- 0.36594577 meV +Free energy = -308373.37847360 +- 0.36594577 meV +FC gradient modulus = 26075.94026588 +- 593.75571302 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.95176137 meV/A +Kong-Liu effective sample size = 45.313870421619505 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 3 +Minimization step, force computed: 50 +Good step found with 0.1310370697125, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 110.39283626 meV +Anharmonic contribution to free energy = -308483.77130987 +- 0.36594577 meV +Free energy = -308373.37847360 +- 0.36594577 meV +FC gradient modulus = 26689.79824809 +- 607.50273104 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.97586506 meV/A +Kong-Liu effective sample size = 45.313870421619505 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 4 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.38513711 meV +Anharmonic contribution to free energy = -308471.42620652 +- 1.22689717 meV +Free energy = -308372.04106941 +- 1.22689717 meV +FC gradient modulus = 26689.79824809 +- 607.50273104 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.97586506 meV/A +Kong-Liu effective sample size = 25.963274509548036 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 5 +Minimization step, force computed: 50 +Step too large (scalar = 3.093449498731049 | kl_ratio = 0.5729652812256975), reducing to 0.17170713638838586 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.84589890 meV +Anharmonic contribution to free energy = -308473.15235601 +- 1.07801134 meV +Free energy = -308372.30645710 +- 1.07801134 meV +FC gradient modulus = 21523.46542630 +- 484.49959331 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.76078741 meV/A +Kong-Liu effective sample size = 28.67143837308559 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 6 +Minimization step, force computed: 50 +Step too large (scalar = 3.1877455555406184 | kl_ratio = 0.6327298486382722), reducing to 0.15000000000705774 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 102.10410432 meV +Anharmonic contribution to free energy = -308474.61672341 +- 0.95671077 meV +Free energy = -308372.51261910 +- 0.95671077 meV +FC gradient modulus = 22159.81799260 +- 500.87213043 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.78813811 meV/A +Kong-Liu effective sample size = 31.07644772874749 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 7 +Minimization step, force computed: 50 +Step too large (scalar = 3.270031012486098 | kl_ratio = 0.6858043120042278), reducing to 0.1310370697186655 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.19015077 meV +Anharmonic contribution to free energy = -308475.86409362 +- 0.85790359 meV +Free energy = -308372.67394284 +- 0.85790359 meV +FC gradient modulus = 22717.52226235 +- 514.92103584 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.81154988 meV/A +Kong-Liu effective sample size = 33.17360891486492 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 8 +Minimization step, force computed: 50 +Step too large (scalar = 3.3419776505101644 | kl_ratio = 0.7320850901987309), reducing to 0.11447142426430995 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 104.12924948 meV +Anharmonic contribution to free energy = -308476.93041631 +- 0.77724621 meV +Free energy = -308372.80116682 +- 0.77724621 meV +FC gradient modulus = 23206.94507914 +- 527.01647153 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.83179116 meV/A +Kong-Liu effective sample size = 34.978871606051854 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 9 +Minimization step, force computed: 50 +Step too large (scalar = 3.4049601262426026 | kl_ratio = 0.7719241653955746), reducing to 0.10000000000941031 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 104.94248026 meV +Anharmonic contribution to free energy = -308477.84477765 +- 0.71117756 meV +Free energy = -308372.90229739 +- 0.71117756 meV +FC gradient modulus = 23636.70824691 +- 537.46021666 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.84941532 meV/A +Kong-Liu effective sample size = 36.51943833285862 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 10 +Minimization step, force computed: 50 +Step too large (scalar = 3.4601321132000256 | kl_ratio = 0.8059218511477004), reducing to 0.08735804648322065 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 105.64758598 meV +Anharmonic contribution to free energy = -308478.63090432 +- 0.65683304 meV +Free energy = -308372.98331834 +- 0.65683304 meV +FC gradient modulus = 24014.14277249 +- 546.49949666 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.86483328 meV/A +Kong-Liu effective sample size = 37.82700826431796 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 11 +Minimization step, force computed: 50 +Step too large (scalar = 3.5084771483529145 | kl_ratio = 0.834777694166475), reducing to 0.076314282846464 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 106.25958315 meV +Anharmonic contribution to free energy = -308479.30830563 +- 0.61192953 meV +Free energy = -308373.04872247 +- 0.61192953 meV +FC gradient modulus = 24345.57999410 +- 554.33841680 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.87836124 meV/A +Kong-Liu effective sample size = 38.93350980933003 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 12 +Minimization step, force computed: 50 +Step too large (scalar = 3.5508432682297526 | kl_ratio = 0.8591963000969928), reducing to 0.06666666667607696 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 106.79123936 meV +Anharmonic contribution to free energy = -308479.89314257 +- 0.57465991 meV +Free energy = -308373.10190322 +- 0.57465991 meV +FC gradient modulus = 24636.54391658 +- 561.14693290 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.89025125 meV/A +Kong-Liu effective sample size = 39.868733744068535 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 13 +Minimization step, force computed: 50 +Step too large (scalar = 3.587967367509013 | kl_ratio = 0.8798351006681374), reducing to 0.058238697658220644 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 107.25345196 meV +Anharmonic contribution to free energy = -308480.39889301 +- 0.54358496 meV +Free energy = -308373.14544105 +- 0.54358496 meV +FC gradient modulus = 24891.88423006 +- 567.06774018 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.90071056 meV/A +Kong-Liu effective sample size = 40.65924286389403 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 14 +Minimization step, force computed: 50 +Step too large (scalar = 3.620493018116797 | kl_ratio = 0.8972802915659853), reducing to 0.050876188566703125 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 107.65555239 meV +Anharmonic contribution to free energy = -308480.83686492 +- 0.51756546 meV +Free energy = -308373.18131252 +- 0.51756546 meV +FC gradient modulus = 25115.87349327 +- 572.22153740 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.90991393 meV/A +Kong-Liu effective sample size = 41.328058235793904 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 15 +Minimization step, force computed: 50 +Good step found with 0.050876188566703125, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 107.65555239 meV +Anharmonic contribution to free energy = -308480.83686492 +- 0.51756546 meV +Free energy = -308373.18131252 +- 0.51756546 meV +FC gradient modulus = 25312.28219689 +- 576.71106767 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.91801149 meV/A +Kong-Liu effective sample size = 41.328058235793904 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 16 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.64345831 meV +Anharmonic contribution to free energy = -308476.37105162 +- 0.82501309 meV +Free energy = -308372.72759331 +- 0.82501309 meV +FC gradient modulus = 25312.28219689 +- 576.71106767 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.91801149 meV/A +Kong-Liu effective sample size = 33.91805705111914 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 17 +Minimization step, force computed: 50 +Step too large (scalar = 3.201860544739119 | kl_ratio = 0.8207028952970015), reducing to 0.06666666667921373 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 104.15951048 meV +Anharmonic contribution to free energy = -308476.95733139 +- 0.78023143 meV +Free energy = -308372.79782090 +- 0.78023143 meV +FC gradient modulus = 23424.59541316 +- 532.18786353 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.83669319 meV/A +Kong-Liu effective sample size = 34.927323397701485 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 18 +Minimization step, force computed: 50 +Step too large (scalar = 3.234388471252214 | kl_ratio = 0.8451237461587588), reducing to 0.05823869766096086 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 104.60816188 meV +Anharmonic contribution to free energy = -308477.46410353 +- 0.74250859 meV +Free energy = -308372.85594165 +- 0.74250859 meV +FC gradient modulus = 23660.36349702 +- 537.93182169 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.84695859 meV/A +Kong-Liu effective sample size = 35.79708984462944 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 19 +Minimization step, force computed: 50 +Step too large (scalar = 3.262847744116356 | kl_ratio = 0.8661691686648337), reducing to 0.050876188569096925 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 104.99846832 meV +Anharmonic contribution to free energy = -308477.90277819 +- 0.71062605 meV +Free energy = -308372.90430987 +- 0.71062605 meV +FC gradient modulus = 23866.90429496 +- 542.91833238 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.85590526 meV/A +Kong-Liu effective sample size = 36.545958676896745 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 20 +Minimization step, force computed: 50 +Step too large (scalar = 3.287748139384161 | kl_ratio = 0.884289275542217), reducing to 0.044444444454900325 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 105.33820603 meV +Anharmonic contribution to free energy = -308478.28297411 +- 0.68359192 meV +Free energy = -308372.94476808 +- 0.68359192 meV +FC gradient modulus = 24047.81248489 +- 547.25186283 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.86371340 meV/A +Kong-Liu effective sample size = 37.19060142387497 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 21 +Minimization step, force computed: 50 +Step too large (scalar = 3.3095340224566896 | kl_ratio = 0.8998874617260506), reducing to 0.038825798442467384 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 105.63406817 meV +Anharmonic contribution to free energy = -308478.61283663 +- 0.66060042 meV +Free energy = -308372.97876846 +- 0.66060042 meV +FC gradient modulus = 24206.23861019 +- 551.02119282 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.87053425 meV/A +Kong-Liu effective sample size = 37.745678304120766 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 22 +Minimization step, force computed: 50 +Good step found with 0.038825798442467384, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 105.63406817 meV +Anharmonic contribution to free energy = -308478.61283663 +- 0.66060042 meV +Free energy = -308372.97876846 +- 0.66060042 meV +FC gradient modulus = 24344.94775862 +- 554.30211652 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.87649628 meV/A +Kong-Liu effective sample size = 37.745678304120766 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 23 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 102.65297925 meV +Anharmonic contribution to free energy = -308475.22805680 +- 0.91979265 meV +Free energy = -308372.57507755 +- 0.91979265 meV +FC gradient modulus = 24344.94775862 +- 554.30211652 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.87649628 meV/A +Kong-Liu effective sample size = 31.881150917885115 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 24 +Minimization step, force computed: 50 +Step too large (scalar = 3.0220215157691372 | kl_ratio = 0.8446304941459905), reducing to 0.05087618857149072 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.03479187 meV +Anharmonic contribution to free energy = -308475.66872934 +- 0.88375387 meV +Free energy = -308372.63393747 +- 0.88375387 meV +FC gradient modulus = 22983.76519400 +- 521.14464346 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.81473407 meV/A +Kong-Liu effective sample size = 32.64647363290491 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 25 +Minimization step, force computed: 50 +Step too large (scalar = 3.0446505526024676 | kl_ratio = 0.8649062647614636), reducing to 0.0444444444569915 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.36713665 meV +Anharmonic contribution to free energy = -308476.05056478 +- 0.85303521 meV +Free energy = -308372.68342813 +- 0.85303521 meV +FC gradient modulus = 23154.66610689 +- 525.42100898 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.82266123 meV/A +Kong-Liu effective sample size = 33.31170718712266 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 26 +Minimization step, force computed: 50 +Step too large (scalar = 3.064430715166865 | kl_ratio = 0.8825303633101211), reducing to 0.03882579844429419 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.65656096 meV +Anharmonic contribution to free energy = -308476.38177594 +- 0.82678757 meV +Free energy = -308372.72521498 +- 0.82678757 meV +FC gradient modulus = 23304.19002244 +- 529.13503155 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.82954626 meV/A +Kong-Liu effective sample size = 33.88950717062663 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 27 +Minimization step, force computed: 50 +Step too large (scalar = 3.0817219258395125 | kl_ratio = 0.8978380755957126), reducing to 0.033917459049256346 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.90871159 meV +Anharmonic contribution to free energy = -308476.66934278 +- 0.80431040 meV +Free energy = -308372.76063119 +- 0.80431040 meV +FC gradient modulus = 23435.00329746 +- 532.36349498 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.83553437 meV/A +Kong-Liu effective sample size = 34.39119352782019 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 28 +Minimization step, force computed: 50 +Good step found with 0.033917459049256346, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 103.90871159 meV +Anharmonic contribution to free energy = -308476.66934278 +- 0.80431040 meV +Free energy = -308372.76063119 +- 0.80431040 meV +FC gradient modulus = 23549.43740078 +- 535.17195298 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.84074788 meV/A +Kong-Liu effective sample size = 34.39119352782019 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 29 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 101.35801288 meV +Anharmonic contribution to free energy = -308473.70976162 +- 1.05209352 meV +Free energy = -308372.35174875 +- 1.05209352 meV +FC gradient modulus = 23549.43740078 +- 535.17195298 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.84074788 meV/A +Kong-Liu effective sample size = 29.22290194347556 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 30 +Minimization step, force computed: 50 +Step too large (scalar = 2.8511705426148986 | kl_ratio = 0.8497204937024408), reducing to 0.044444444459082674 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 101.68414856 meV +Anharmonic contribution to free energy = -308474.09385506 +- 1.01844531 meV +Free energy = -308372.40970650 +- 1.01844531 meV +FC gradient modulus = 22415.72781283 +- 506.51233375 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.78573420 meV/A +Kong-Liu effective sample size = 29.880635163383793 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 31 +Minimization step, force computed: 50 +Step too large (scalar = 2.8694480562462523 | kl_ratio = 0.8688455414963236), reducing to 0.038825798446121 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 101.96816509 meV +Anharmonic contribution to free energy = -308474.42697273 +- 0.98958476 meV +Free energy = -308372.45880765 +- 0.98958476 meV +FC gradient modulus = 22558.55037517 +- 510.21289464 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.79288058 meV/A +Kong-Liu effective sample size = 30.455645608398775 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 32 +Minimization step, force computed: 50 +Step too large (scalar = 2.885412656382911 | kl_ratio = 0.885565241687881), reducing to 0.03391745905085221 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 102.21560397 meV +Anharmonic contribution to free energy = -308474.71615266 +- 0.96478794 meV +Free energy = -308372.50054868 +- 0.96478794 meV +FC gradient modulus = 22683.39778529 +- 513.42625793 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.79906980 meV/A +Kong-Liu effective sample size = 30.957809087182262 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 33 +Minimization step, force computed: 50 +Good step found with 0.03391745905085221, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 102.21560397 meV +Anharmonic contribution to free energy = -308474.71615266 +- 0.96478794 meV +Free energy = -308372.50054868 +- 0.96478794 meV +FC gradient modulus = 22792.53661986 +- 516.21893568 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.80443841 meV/A +Kong-Liu effective sample size = 30.957809087182262 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 34 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.71208641 meV +Anharmonic contribution to free energy = -308471.73550100 +- 1.23476700 meV +Free energy = -308372.02341460 +- 1.23476700 meV +FC gradient modulus = 22792.53661986 +- 516.21893568 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.80443841 meV/A +Kong-Liu effective sample size = 25.89532015605089 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 35 +Minimization step, force computed: 50 +Step too large (scalar = 2.672397350523524 | kl_ratio = 0.8364713434056468), reducing to 0.04444444446117385 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.03219460 meV +Anharmonic contribution to free energy = -308472.12252228 +- 1.19858906 meV +Free energy = -308372.09032769 +- 1.19858906 meV +FC gradient modulus = 21707.89430590 +- 487.54054040 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.74679707 meV/A +Kong-Liu effective sample size = 26.525672178566428 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 36 +Minimization step, force computed: 50 +Step too large (scalar = 2.6893774030383533 | kl_ratio = 0.8568329917619748), reducing to 0.03882579844794781 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.31096074 meV +Anharmonic contribution to free energy = -308472.45814212 +- 1.16744246 meV +Free energy = -308372.14718138 +- 1.16744246 meV +FC gradient modulus = 21844.99274959 +- 491.25669216 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.75439070 meV/A +Kong-Liu effective sample size = 27.079868396811126 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 37 +Minimization step, force computed: 50 +Step too large (scalar = 2.7041949542761916 | kl_ratio = 0.8747346532356272), reducing to 0.03391745905244808 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.55382446 meV +Anharmonic contribution to free energy = -308472.74946295 +- 1.14059364 meV +Free energy = -308372.19563850 +- 1.14059364 meV +FC gradient modulus = 21964.72188724 +- 494.48069990 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.76094300 meV/A +Kong-Liu effective sample size = 27.56630053150732 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 38 +Minimization step, force computed: 50 +Step too large (scalar = 2.7171289886786814 | kl_ratio = 0.8904473974200209), reducing to 0.029629629642176684 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.76548508 meV +Anharmonic contribution to free energy = -308473.00254039 +- 1.11742044 meV +Free energy = -308372.23705531 +- 1.11742044 meV +FC gradient modulus = 22069.30099286 +- 497.28034798 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.76660782 meV/A +Kong-Liu effective sample size = 27.9927172030087 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 39 +Minimization step, force computed: 50 +Good step found with 0.029629629642176684, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 100.76548508 meV +Anharmonic contribution to free energy = -308473.00254039 +- 1.11742044 meV +Free energy = -308372.23705531 +- 1.11742044 meV +FC gradient modulus = 22160.65818177 +- 499.71345013 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.77151329 meV/A +Kong-Liu effective sample size = 27.9927172030087 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 40 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 98.61709046 meV +Anharmonic contribution to free energy = -308470.38945538 +- 1.36599299 meV +Free energy = -308371.77236492 +- 1.36599299 meV +FC gradient modulus = 22160.65818177 +- 499.71345013 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.77151329 meV/A +Kong-Liu effective sample size = 23.734494184829853 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 41 +Minimization step, force computed: 50 +Step too large (scalar = 2.543073766840762 | kl_ratio = 0.8478810403685582), reducing to 0.03882579844977462 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 98.89139135 meV +Anharmonic contribution to free energy = -308470.72768409 +- 1.33321890 meV +Free energy = -308371.83629274 +- 1.33321890 meV +FC gradient modulus = 21245.54833898 +- 474.58859571 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.71855081 meV/A +Kong-Liu effective sample size = 24.259056123715467 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 42 +Minimization step, force computed: 50 +Step too large (scalar = 2.557025122052333 | kl_ratio = 0.8666202694002163), reducing to 0.03391745905404394 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.13036358 meV +Anharmonic contribution to free energy = -308471.02125346 +- 1.30488539 meV +Free energy = -308371.89088988 +- 1.30488539 meV +FC gradient modulus = 21361.50681947 +- 477.84101714 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.72554820 meV/A +Kong-Liu effective sample size = 24.721253169900066 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 43 +Minimization step, force computed: 50 +Step too large (scalar = 2.569193722788679 | kl_ratio = 0.8831316013596204), reducing to 0.0296296296435708 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.33863171 meV +Anharmonic contribution to free energy = -308471.27627015 +- 1.28036733 meV +Free energy = -308371.93763844 +- 1.28036733 meV +FC gradient modulus = 21462.71176710 +- 480.66374289 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.73158360 meV/A +Kong-Liu effective sample size = 25.127816330474158 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 44 +Minimization step, force computed: 50 +Step too large (scalar = 2.5798106789015445 | kl_ratio = 0.8976554918996352), reducing to 0.025883865634400954 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.52019683 meV +Anharmonic contribution to free energy = -308471.49795630 +- 1.25913302 meV +Free energy = -308371.97775947 +- 1.25913302 meV +FC gradient modulus = 21551.06082255 +- 483.11563212 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.73679890 meV/A +Kong-Liu effective sample size = 25.48496576060005 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 45 +Minimization step, force computed: 50 +Good step found with 0.025883865634400954, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 99.52019683 meV +Anharmonic contribution to free energy = -308471.49795630 +- 1.25913302 meV +Free energy = -308371.97775947 +- 1.25913302 meV +FC gradient modulus = 21628.20053757 +- 485.24698479 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.74131263 meV/A +Kong-Liu effective sample size = 25.48496576060005 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 46 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 97.67227411 meV +Anharmonic contribution to free energy = -308469.20637561 +- 1.48434985 meV +Free energy = -308371.53410149 +- 1.48434985 meV +FC gradient modulus = 21628.20053757 +- 485.24698479 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.74131263 meV/A +Kong-Liu effective sample size = 21.933354415360366 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 47 +Minimization step, force computed: 50 +Step too large (scalar = 2.4358961480626515 | kl_ratio = 0.8606389595103751), reducing to 0.03391745905563981 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 97.90791366 meV +Anharmonic contribution to free energy = -308469.50213767 +- 1.45501686 meV +Free energy = -308371.59422401 +- 1.45501686 meV +FC gradient modulus = 20850.51674727 +- 463.16235424 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.69254939 meV/A +Kong-Liu effective sample size = 22.368512583859964 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 48 +Minimization step, force computed: 50 +Step too large (scalar = 2.447478519554621 | kl_ratio = 0.8777140528256802), reducing to 0.02962962964496492 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 98.11327621 meV +Anharmonic contribution to free energy = -308469.75905456 +- 1.42957996 meV +Free energy = -308371.64577836 +- 1.42957996 meV +FC gradient modulus = 20949.23142544 +- 466.01643654 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.69898871 meV/A +Kong-Liu effective sample size = 22.752307952922393 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 49 +Minimization step, force computed: 50 +Step too large (scalar = 2.4575777623921335 | kl_ratio = 0.8927737304673028), reducing to 0.02588386563561883 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 98.29230744 meV +Anharmonic contribution to free energy = -308469.98238787 +- 1.40750539 meV +Free energy = -308371.69008043 +- 1.40750539 meV +FC gradient modulus = 21035.35110122 +- 468.49472804 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.70454501 meV/A +Kong-Liu effective sample size = 23.090253085933018 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 50 +Minimization step, force computed: 50 +Good step found with 0.02588386563561883, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 98.29230744 meV +Anharmonic contribution to free energy = -308469.98238787 +- 1.40750539 meV +Free energy = -308371.69008043 +- 1.40750539 meV +FC gradient modulus = 21110.50240823 +- 470.64836023 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.70934754 meV/A +Kong-Liu effective sample size = 23.090253085933018 + + +The gw gradient satisfy the convergence condition. +KL: 23.090253085933018 KL/N: 0.46180506171866037 KL RAT: 0.5 + According to your input criteria + you are out of the statistical sampling. +Check the stopping criteria: Running = False +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + +Restoring the last good dynamical matrix. +Updating the importance sampling... + + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 50 steps + +Free energy = -308371.69008043 +- 1.40750539 meV +FC gradient modulus = 21110.50240823 +- 470.64836023 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.70934754 meV/A +Kong-Liu effective sample size = 23.090253085933018 + +Total force on the centroids [eV/A]: + 0) 0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + 1) 0.000000 0.000000 0.000000 +- 0.000000 -0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + 0.86860231 0.00000000 0.00000000 0.02163903 0.00000000 0.00000000 + 0.00000000 0.86860231 0.00000000 +- 0.00000000 0.02163903 0.00000000 + -0.00000000 0.00000000 0.86860231 0.00000000 0.00000000 0.02163903 + + Ab initio average stress [GPa]: + 0.68720493 0.00000000 0.00000000 + 0.00000000 0.68720493 0.00000000 + 0.00000000 -0.00000000 0.68720493 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds +Average of 0.6527698040008545 s per call +Subroutine report: + Function: GoParallel + N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.6516294479370117 s per call + Subroutine report: + Function: compute + N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.6515698432922363 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.6517899036407471 s per call + + +Function: minimization_step +N = 50 calls took: 0 hours; 0 minutes; 1.76 seconds +Average of 0.03528819561004639 s per call +Subroutine report: + Function: get_fourier_gradient + N = 50 calls took: 0 hours; 0 minutes; 0.11 seconds + Average of 0.002203860282897949 s per call + Subroutine report: + Function: GoParallel + N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds + Average of 0.0010434627532958985 s per call + Subroutine report: + Function: compute + N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds + Average of 0.0009998083114624023 s per call + Subroutine report: + + + Function: fourier gradient upsilon q + N = 50 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.000511336326599121 s per call + + Function: fourier gradient Y * u + N = 50 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.0005041360855102539 s per call + + Function: fourier gradient julia + N = 50 calls took: 0 hours; 0 minutes; 0.06 seconds + Average of 0.0011458396911621094 s per call + + + Function: SymmetrizeFCQ + N = 50 calls took: 0 hours; 0 minutes; 0.48 seconds + Average of 0.009649415016174317 s per call + + Function: Symmetrize + N = 50 calls took: 0 hours; 0 minutes; 0.49 seconds + Average of 0.00971813678741455 s per call + + Function: update + N = 50 calls took: 0 hours; 0 minutes; 0.62 seconds + Average of 0.012317957878112793 s per call + Subroutine report: + Function: update_weights_fourier + N = 50 calls took: 0 hours; 0 minutes; 0.61 seconds + Average of 0.012276368141174316 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 50 calls took: 0 hours; 0 minutes; 0.41 seconds + Average of 0.008104453086853028 s per call + Subroutine report: + Function: DyagDinQ + N = 400 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.00020899832248687743 s per call + + Function: Manipulate polarization vectors + N = 400 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.00017248690128326415 s per call + + + Function: Time to get SSCHA energy and forces + N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds + Average of 0.0010889768600463867 s per call + + Function: get upsilon fourier + N = 50 calls took: 0 hours; 0 minutes; 0.04 seconds + Average of 0.0008661460876464844 s per call + + Function: get uYu + N = 50 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.0016811180114746093 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = 0.8686 +- 0.0216 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.0470 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0837169008e+02 eV + Gibbs Free energy = -3.0837169008e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.04698463143717 +[CELL] unit_cell: +Cell([[2.71548, 2.71548, 0.0], [2.71548, 0.0, 2.71548], [0.0, 2.71548, 2.71548]]) +[CELL] CURRENT STRAIN: +[[ 0.00000000e+00 4.39618027e-18 -4.39618027e-18] + [ 4.39618027e-18 0.00000000e+00 -4.39618027e-18] + [ 4.39618027e-18 -4.39618027e-18 0.00000000e+00]] +[CELL] NEW STRESS: +[[ 5.42138924e-03 1.24433616e-18 1.24433616e-18] + [ 1.86650424e-18 5.42138924e-03 0.00000000e+00] + [-6.22168079e-19 6.22168079e-19 5.42138924e-03]] +GRAD MAT: +[[-2.17110292e-01 -5.07863670e-17 -4.88774550e-17] + [-7.57023225e-17 -2.17110292e-01 9.54455980e-19] + [ 2.39614995e-17 -2.39614995e-17 -2.17110292e-01]] + +[CELL] New step: +[CELL] X_OLD = [ 0.00000000e+00 4.39618027e-18 -4.39618027e-18 4.39618027e-18 + 0.00000000e+00 -4.39618027e-18 4.39618027e-18 -4.39618027e-18 + 0.00000000e+00] | ALPHA = 0.013335807390121452 +[CELL] DIRECTION = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 + -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 + -2.17110292e-01] +[CELL] GRADIENT = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 + -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 + -2.17110292e-01] +[CELL] X_NEW = [ 2.89534103e-03 5.07345748e-18 -3.74435994e-18 5.40573186e-18 + 2.89534103e-03 -4.40890871e-18 4.07663433e-18 -4.07663433e-18 + 2.89534103e-03] +[CELL] Step number = 1 + +NEW STRAIN: +[[ 2.89534103e-03 5.07345748e-18 -3.74435994e-18] + [ 5.40573186e-18 2.89534103e-03 -4.40890871e-18] + [ 4.07663433e-18 -4.07663433e-18 2.89534103e-03]] +NEW VOLUME: -40.395841778473766 + + Currently estimated bulk modulus = 100.000 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72334224 2.72334224 -0.00000000) + v2 [A] = ( 2.72334224 0.00000000 2.72334224) + v3 [A] = ( 0.00000000 2.72334224 2.72334224) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. +[BFFS USED] For structure with id=0 +[BFFS USED] For structure with id=1 +[BFFS USED] For structure with id=2 +[BFFS USED] For structure with id=3 +[BFFS USED] For structure with id=4 +[BFFS USED] For structure with id=5 +[BFFS USED] For structure with id=6 +[BFFS USED] For structure with id=7 +[BFFS USED] For structure with id=8 +[BFFS USED] For structure with id=9 +[BFFS USED] For structure with id=10 +[BFFS USED] For structure with id=11 +[BFFS USED] For structure with id=12 +[BFFS USED] For structure with id=13 +[BFFS USED] For structure with id=14 +[BFFS USED] For structure with id=15 +[BFFS USED] For structure with id=16 +[BFFS USED] For structure with id=17 +[BFFS USED] For structure with id=18 +[BFFS USED] For structure with id=19 +[BFFS USED] For structure with id=20 +[BFFS USED] For structure with id=21 +[BFFS USED] For structure with id=22 +[BFFS USED] For structure with id=23 +[BFFS USED] For structure with id=24 +[BFFS USED] For structure with id=25 +[BFFS USED] For structure with id=26 +[BFFS USED] For structure with id=27 +[BFFS USED] For structure with id=28 +[BFFS USED] For structure with id=29 +[BFFS USED] For structure with id=30 +[BFFS USED] For structure with id=31 +[BFFS USED] For structure with id=32 +[BFFS USED] For structure with id=33 +[BFFS USED] For structure with id=34 +[BFFS USED] For structure with id=35 +[BFFS USED] For structure with id=36 +[BFFS USED] For structure with id=37 +[BFFS USED] For structure with id=38 +[BFFS USED] For structure with id=39 +[BFFS USED] For structure with id=40 +[BFFS USED] For structure with id=41 +[BFFS USED] For structure with id=42 +[BFFS USED] For structure with id=43 +[BFFS USED] For structure with id=44 +[BFFS USED] For structure with id=45 +[BFFS USED] For structure with id=46 +[BFFS USED] For structure with id=47 +[BFFS USED] For structure with id=48 +[BFFS USED] For structure with id=49 +=============== SUMMARY AIIDA CALCULATIONS =============== + +Total structures included: 50 +Structures not included : 0 +Steps using OTF-ML model : 50 + +===================== END OF SUMMARY ===================== + + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 51 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 90.88945656 meV +Anharmonic contribution to free energy = -308462.93607119 +- 0.91810859 meV +Free energy = -308372.04661463 +- 0.91810859 meV +FC gradient modulus = 22015.80640141 +- 485.62121751 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.44714794 meV/A +Kong-Liu effective sample size = 45.203949864959775 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 52 +Minimization step, force computed: 50 +Good step found with 0.15000000000000002, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 90.88945656 meV +Anharmonic contribution to free energy = -308462.93607119 +- 0.91810859 meV +Free energy = -308372.04661463 +- 0.91810859 meV +FC gradient modulus = 18271.01206509 +- 411.74840303 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.24762988 meV/A +Kong-Liu effective sample size = 45.203949864959775 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 53 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 80.68092225 meV +Anharmonic contribution to free energy = -308450.51056227 +- 1.46031226 meV +Free energy = -308369.82964002 +- 1.46031226 meV +FC gradient modulus = 18271.01206509 +- 411.74840303 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.24762988 meV/A +Kong-Liu effective sample size = 27.70751687783123 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 54 +Minimization step, force computed: 50 +Step too large (scalar = 1.3290557919573913 | kl_ratio = 0.6129445979964895), reducing to 0.19655560456875001 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.04461766 meV +Anharmonic contribution to free energy = -308452.18873596 +- 1.38810811 meV +Free energy = -308370.14411830 +- 1.38810811 meV +FC gradient modulus = 13520.42045673 +- 315.40643325 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.95707971 meV/A +Kong-Liu effective sample size = 30.10983237026976 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 55 +Minimization step, force computed: 50 +Step too large (scalar = 1.3906749879262446 | kl_ratio = 0.666088526781808), reducing to 0.17170713638838586 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 83.21680813 meV +Anharmonic contribution to free energy = -308453.62984556 +- 1.32456804 meV +Free energy = -308370.41303743 +- 1.32456804 meV +FC gradient modulus = 14131.91824415 +- 327.69156762 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.99660819 meV/A +Kong-Liu effective sample size = 32.23658084255212 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 56 +Minimization step, force computed: 50 +Step too large (scalar = 1.4441462505928628 | kl_ratio = 0.7131363727916303), reducing to 0.15000000000705774 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 84.22689177 meV +Anharmonic contribution to free energy = -308454.86941285 +- 1.26921767 meV +Free energy = -308370.64252107 +- 1.26921767 meV +FC gradient modulus = 14663.73883232 +- 338.43541311 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.03043645 meV/A +Kong-Liu effective sample size = 34.092738567753976 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 57 +Minimization step, force computed: 50 +Step too large (scalar = 1.4905661670685848 | kl_ratio = 0.7541982209431051), reducing to 0.1310370697186655 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.09906908 meV +Anharmonic contribution to free energy = -308455.93734975 +- 1.22129760 meV +Free energy = -308370.83828068 +- 1.22129760 meV +FC gradient modulus = 15126.40351807 +- 347.81520594 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.05945438 meV/A +Kong-Liu effective sample size = 35.696233361083124 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 58 +Minimization step, force computed: 50 +Step too large (scalar = 1.5308862825137615 | kl_ratio = 0.7896706696587451), reducing to 0.11447142426430995 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.85344973 meV +Anharmonic contribution to free energy = -308456.85883119 +- 1.17995897 meV +Free energy = -308371.00538146 +- 1.17995897 meV +FC gradient modulus = 15529.05602057 +- 355.99605325 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.08440368 meV/A +Kong-Liu effective sample size = 37.07176302247563 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 59 +Minimization step, force computed: 50 +Step too large (scalar = 1.565928274779367 | kl_ratio = 0.8201000826968026), reducing to 0.10000000000941031 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 86.50687293 meV +Anharmonic contribution to free energy = -308457.65506883 +- 1.14436548 meV +Free energy = -308371.14819590 +- 1.14436548 meV +FC gradient modulus = 15879.61745273 +- 363.12746366 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.10590093 meV/A +Kong-Liu effective sample size = 38.246421478782025 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 60 +Minimization step, force computed: 50 +Step too large (scalar = 1.5964002739416117 | kl_ratio = 0.8460858308408369), reducing to 0.08735804648322065 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 87.07352885 meV +Anharmonic contribution to free energy = -308458.34397179 +- 1.11374017 meV +Free energy = -308371.27044294 +- 1.11374017 meV +FC gradient modulus = 16184.94200835 +- 369.34260160 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.12445946 meV/A +Kong-Liu effective sample size = 39.246935776196175 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 61 +Minimization step, force computed: 50 +Step too large (scalar = 1.6229123216505097 | kl_ratio = 0.8682191687549581), reducing to 0.076314282846464 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 87.56543862 meV +Anharmonic contribution to free energy = -308458.94069943 +- 1.08738995 meV +Free energy = -308371.37526081 +- 1.08738995 meV +FC gradient modulus = 16450.96028557 +- 374.75890193 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.14050803 meV/A +Kong-Liu effective sample size = 40.098121775298054 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 62 +Minimization step, force computed: 50 +Step too large (scalar = 1.6459902117117944 | kl_ratio = 0.8870490719303371), reducing to 0.06666666667607696 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 87.99283091 meV +Anharmonic contribution to free energy = -308459.45811877 +- 1.06470698 meV +Free energy = -308371.46528785 +- 1.06470698 meV +FC gradient modulus = 16682.80614698 +- 379.47930456 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.15440637 meV/A +Kong-Liu effective sample size = 40.82216754010444 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 63 +Minimization step, force computed: 50 +Good step found with 0.06666666667607696, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 87.99283091 meV +Anharmonic contribution to free energy = -308459.45811877 +- 1.06470698 meV +Free energy = -308371.46528785 +- 1.06470698 meV +FC gradient modulus = 16884.92691674 +- 383.59371446 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.16645764 meV/A +Kong-Liu effective sample size = 40.82216754010444 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 64 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 83.80390395 meV +Anharmonic contribution to free energy = -308454.29049866 +- 1.30302428 meV +Free energy = -308370.48659471 +- 1.30302428 meV +FC gradient modulus = 16884.92691674 +- 383.59371446 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.16645764 meV/A +Kong-Liu effective sample size = 32.96307412623533 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 65 +Minimization step, force computed: 50 +Step too large (scalar = 1.3619576175073762 | kl_ratio = 0.8074797619173897), reducing to 0.08735804648733096 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 84.34547352 meV +Anharmonic contribution to free energy = -308454.96415899 +- 1.27176056 meV +Free energy = -308370.61868547 +- 1.27176056 meV +FC gradient modulus = 14941.22018823 +- 343.15164440 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.04280536 meV/A +Kong-Liu effective sample size = 34.01138081177903 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 66 +Minimization step, force computed: 50 +Step too large (scalar = 1.3848062655591078 | kl_ratio = 0.833159600806734), reducing to 0.07631428285005468 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 84.81561700 meV +Anharmonic contribution to free energy = -308455.54782480 +- 1.24462324 meV +Free energy = -308370.73220780 +- 1.24462324 meV +FC gradient modulus = 15189.43956752 +- 348.33166310 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.05910574 meV/A +Kong-Liu effective sample size = 34.920297786830076 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 67 +Minimization step, force computed: 50 +Step too large (scalar = 1.4046891680155689 | kl_ratio = 0.8554248804285991), reducing to 0.06666666667921371 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.22410624 meV +Anharmonic contribution to free energy = -308456.05401354 +- 1.22108458 meV +Free energy = -308370.82990731 +- 1.22108458 meV +FC gradient modulus = 15405.68008879 +- 352.84272573 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.07317830 meV/A +Kong-Liu effective sample size = 35.70701229252045 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 68 +Minimization step, force computed: 50 +Step too large (scalar = 1.421999503512891 | kl_ratio = 0.8746966279397398), reducing to 0.05823869766096085 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.57928752 meV +Anharmonic contribution to free energy = -308456.49339384 +- 1.20067074 meV +Free energy = -308370.91410632 +- 1.20067074 meV +FC gradient modulus = 15594.12801905 +- 356.77204032 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.08534693 meV/A +Kong-Liu effective sample size = 36.38732659028425 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 69 +Minimization step, force computed: 50 +Step too large (scalar = 1.4370765124905047 | kl_ratio = 0.8913619433494482), reducing to 0.05087618856909691 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.88831203 meV +Anharmonic contribution to free energy = -308456.87507996 +- 1.18296513 meV +Free energy = -308370.98676793 +- 1.18296513 meV +FC gradient modulus = 15758.40631607 +- 360.19543539 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.09588384 meV/A +Kong-Liu effective sample size = 36.975424642188614 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 70 +Minimization step, force computed: 50 +Good step found with 0.05087618856909691, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 85.88831203 meV +Anharmonic contribution to free energy = -308456.87507996 +- 1.18296513 meV +Free energy = -308370.98676793 +- 1.18296513 meV +FC gradient modulus = 15901.65372878 +- 363.17877623 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.10501876 meV/A +Kong-Liu effective sample size = 36.975424642188614 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 71 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.81916860 meV +Anharmonic contribution to free energy = -308453.02856106 +- 1.36575680 meV +Free energy = -308370.20939246 +- 1.36575680 meV +FC gradient modulus = 15901.65372878 +- 363.17877623 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.10501876 meV/A +Kong-Liu effective sample size = 30.868983704896838 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 72 +Minimization step, force computed: 50 +Step too large (scalar = 1.244881852950903 | kl_ratio = 0.8348513642132892), reducing to 0.06666666668235047 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 83.21374748 meV +Anharmonic contribution to free energy = -308453.52619883 +- 1.34226569 meV +Free energy = -308370.31245134 +- 1.34226569 meV +FC gradient modulus = 14496.99320427 +- 333.37906854 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.01068935 meV/A +Kong-Liu effective sample size = 31.65402156414764 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 73 +Minimization step, force computed: 50 +Step too large (scalar = 1.2603707938800812 | kl_ratio = 0.8560827054851642), reducing to 0.05823869766370106 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 83.55683736 meV +Anharmonic contribution to free energy = -308453.95823926 +- 1.32179006 meV +Free energy = -308370.40140191 +- 1.32179006 meV +FC gradient modulus = 14676.12237924 +- 337.19207944 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.02306400 meV/A +Kong-Liu effective sample size = 32.33920645444582 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 74 +Minimization step, force computed: 50 +Step too large (scalar = 1.2738586296460972 | kl_ratio = 0.874613524182413), reducing to 0.050876188571490705 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 83.85534458 meV +Anharmonic contribution to free energy = -308454.33360776 +- 1.30395380 meV +Free energy = -308370.47826318 +- 1.30395380 meV +FC gradient modulus = 14832.23247082 +- 340.51298051 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.03376377 meV/A +Kong-Liu effective sample size = 32.93648909132388 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 75 +Minimization step, force computed: 50 +Step too large (scalar = 1.2856085646942987 | kl_ratio = 0.8907670272904358), reducing to 0.044444444456991486 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 84.11520257 meV +Anharmonic contribution to free energy = -308454.65995357 +- 1.28842213 meV +Free energy = -308370.54475100 +- 1.28842213 meV +FC gradient modulus = 14968.32364691 +- 343.40608477 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.04302780 meV/A +Kong-Liu effective sample size = 33.45673356204702 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 76 +Minimization step, force computed: 50 +Good step found with 0.044444444456991486, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 84.11520257 meV +Anharmonic contribution to free energy = -308454.65995357 +- 1.28842213 meV +Free energy = -308370.54475100 +- 1.28842213 meV +FC gradient modulus = 15086.99508644 +- 345.92718500 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.05105814 meV/A +Kong-Liu effective sample size = 33.45673356204702 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 77 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 81.52101581 meV +Anharmonic contribution to free energy = -308451.36077216 +- 1.44684871 meV +Free energy = -308369.83975635 +- 1.44684871 meV +FC gradient modulus = 15086.99508644 +- 345.92718500 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.05105814 meV/A +Kong-Liu effective sample size = 28.18282131790501 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 78 +Minimization step, force computed: 50 +Step too large (scalar = 1.1337028678683456 | kl_ratio = 0.8423661941067468), reducing to 0.058238697666441276 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 81.85378637 meV +Anharmonic contribution to free energy = -308451.78613078 +- 1.42676964 meV +Free energy = -308369.93234440 +- 1.42676964 meV +FC gradient modulus = 13913.76744704 +- 320.57971974 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.96793982 meV/A +Kong-Liu effective sample size = 28.846111198773677 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 79 +Minimization step, force computed: 50 +Step too large (scalar = 1.145958078920399 | kl_ratio = 0.8621914971250036), reducing to 0.050876188573884505 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.14331714 meV +Anharmonic contribution to free energy = -308452.15576538 +- 1.40920960 meV +Free energy = -308370.01244824 +- 1.40920960 meV +FC gradient modulus = 14063.33749952 +- 323.82124967 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.97882645 meV/A +Kong-Liu effective sample size = 29.42779423860135 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 80 +Minimization step, force computed: 50 +Step too large (scalar = 1.156632600239579 | kl_ratio = 0.8795776247560504), reducing to 0.04444444445908266 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.39536239 meV +Anharmonic contribution to free energy = -308452.47717798 +- 1.39386481 meV +Free energy = -308370.08181559 +- 1.39386481 meV +FC gradient modulus = 14193.69850046 +- 326.64473153 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.98824464 meV/A +Kong-Liu effective sample size = 29.937194048596933 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 81 +Minimization step, force computed: 50 +Step too large (scalar = 1.165933710906406 | kl_ratio = 0.8948032536731972), reducing to 0.03882579844612099 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.61487711 meV +Anharmonic contribution to free energy = -308452.75681584 +- 1.38046507 meV +Free energy = -308370.14193873 +- 1.38046507 meV +FC gradient modulus = 14307.35113864 +- 329.10477327 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.99640260 meV/A +Kong-Liu effective sample size = 30.382836714684355 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 82 +Minimization step, force computed: 50 +Good step found with 0.03882579844612099, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 82.61487711 meV +Anharmonic contribution to free energy = -308452.75681584 +- 1.38046507 meV +Free energy = -308370.14193873 +- 1.38046507 meV +FC gradient modulus = 14406.46258673 +- 331.24873624 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.00347666 meV/A +Kong-Liu effective sample size = 30.382836714684355 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 83 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 80.41353288 meV +Anharmonic contribution to free energy = -308449.92260538 +- 1.51602935 meV +Free energy = -308369.50907250 +- 1.51602935 meV +FC gradient modulus = 14406.46258673 +- 331.24873624 bohr^2 +Struct gradient modulus = 0.00000000 +- 2.00347666 meV/A +Kong-Liu effective sample size = 25.923222599399196 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 84 +Minimization step, force computed: 50 +Step too large (scalar = 1.0442153142833297 | kl_ratio = 0.853219297553945), reducing to 0.0508761885762783 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 80.69536774 meV +Anharmonic contribution to free energy = -308450.28692005 +- 1.49901835 meV +Free energy = -308369.59155231 +- 1.49901835 meV +FC gradient modulus = 13419.90614291 +- 309.59138216 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.93022051 meV/A +Kong-Liu effective sample size = 26.477157756926804 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 85 +Minimization step, force computed: 50 +Step too large (scalar = 1.0540408477559233 | kl_ratio = 0.8714511421552058), reducing to 0.044444444461173835 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 80.94071455 meV +Anharmonic contribution to free energy = -308450.60376429 +- 1.48410504 meV +Free energy = -308369.66304974 +- 1.48410504 meV +FC gradient modulus = 13545.61703270 +- 312.35824621 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.93978826 meV/A +Kong-Liu effective sample size = 26.96419211872681 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 86 +Minimization step, force computed: 50 +Step too large (scalar = 1.062601358621769 | kl_ratio = 0.887481059518538), reducing to 0.0388257984479478 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 81.15439621 meV +Anharmonic contribution to free energy = -308450.87946993 +- 1.47104582 meV +Free energy = -308369.72507371 +- 1.47104582 meV +FC gradient modulus = 13655.19848057 +- 314.76885015 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.94807241 meV/A +Kong-Liu effective sample size = 27.39178974917923 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 87 +Minimization step, force computed: 50 +Good step found with 0.0388257984479478, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 81.15439621 meV +Anharmonic contribution to free energy = -308450.87946993 +- 1.47104582 meV +Free energy = -308369.72507371 +- 1.47104582 meV +FC gradient modulus = 13750.74636699 +- 316.86962713 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.95525321 meV/A +Kong-Liu effective sample size = 27.39178974917923 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 88 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.01237564 meV +Anharmonic contribution to free energy = -308448.08803035 +- 1.60153131 meV +Free energy = -308369.07565472 +- 1.60153131 meV +FC gradient modulus = 13750.74636699 +- 316.86962713 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.95525321 meV/A +Kong-Liu effective sample size = 23.17643383538277 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 89 +Minimization step, force computed: 50 +Step too large (scalar = 0.9505939811729262 | kl_ratio = 0.8461087810473293), reducing to 0.0508761885786721 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.28661103 meV +Anharmonic contribution to free energy = -308448.44657407 +- 1.58536571 meV +Free energy = -308369.15996305 +- 1.58536571 meV +FC gradient modulus = 12799.08935045 +- 295.64647986 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.88093833 meV/A +Kong-Liu effective sample size = 23.693091698983693 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 90 +Minimization step, force computed: 50 +Step too large (scalar = 0.9596411090234213 | kl_ratio = 0.8649705592783924), reducing to 0.04444444446326501 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.52534317 meV +Anharmonic contribution to free energy = -308448.75846799 +- 1.57114246 meV +Free energy = -308369.23312482 +- 1.57114246 meV +FC gradient modulus = 12920.41399714 +- 298.35756630 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.89065269 meV/A +Kong-Liu effective sample size = 24.148885177256624 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 91 +Minimization step, force computed: 50 +Step too large (scalar = 0.9675229148904957 | kl_ratio = 0.8816103437702615), reducing to 0.03882579844977461 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.73326463 meV +Anharmonic contribution to free energy = -308449.02991702 +- 1.55864588 meV +Free energy = -308369.29665239 +- 1.55864588 meV +FC gradient modulus = 13026.15865305 +- 300.71970530 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.89906226 meV/A +Kong-Liu effective sample size = 24.550266893640543 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 92 +Minimization step, force computed: 50 +Step too large (scalar = 0.974391792325262 | kl_ratio = 0.8962637023152593), reducing to 0.03391745905404393 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.91442407 meV +Anharmonic contribution to free energy = -308449.26627103 +- 1.54768310 meV +Free energy = -308369.35184696 +- 1.54768310 meV +FC gradient modulus = 13118.35055820 +- 302.77832620 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.90635045 meV/A +Kong-Liu effective sample size = 24.90322452411642 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 93 +Minimization step, force computed: 50 +Good step found with 0.03391745905404393, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 79.91442407 meV +Anharmonic contribution to free energy = -308449.26627103 +- 1.54768310 meV +Free energy = -308369.35184696 +- 1.54768310 meV +FC gradient modulus = 13198.74702302 +- 304.57286038 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.91267305 meV/A +Kong-Liu effective sample size = 24.90322452411642 + + +The gw gradient satisfy the convergence condition. +KL: 24.90322452411642 KL/N: 0.4980644904823284 KL RAT: 0.5 + According to your input criteria + you are out of the statistical sampling. +Check the stopping criteria: Running = False +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + +Restoring the last good dynamical matrix. +Updating the importance sampling... + + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 93 steps + +Free energy = -308369.35184696 +- 1.54768310 meV +FC gradient modulus = 13198.74702302 +- 304.57286038 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.91267305 meV/A +Kong-Liu effective sample size = 24.90322452411642 + +Total force on the centroids [eV/A]: + 0) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + 1) -0.000000 -0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + -0.05949984 0.00000000 -0.00000000 0.02025963 0.00000000 0.00000000 + -0.00000000 -0.05949984 0.00000000 +- 0.00000000 0.02025963 0.00000000 + -0.00000000 0.00000000 -0.05949984 0.00000000 0.00000000 0.02025963 + + Ab initio average stress [GPa]: + -0.26474779 -0.00000000 -0.00000000 + 0.00000000 -0.26474779 -0.00000000 + -0.00000000 -0.00000000 -0.26474779 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds +Average of 0.3272523880004883 s per call +Subroutine report: + Function: GoParallel + N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.32612764835357666 s per call + Subroutine report: + Function: compute + N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.3260691165924072 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.3262568712234497 s per call + + +Function: minimization_step +N = 93 calls took: 0 hours; 0 minutes; 3.30 seconds +Average of 0.03547732804411201 s per call +Subroutine report: + Function: get_fourier_gradient + N = 93 calls took: 0 hours; 0 minutes; 0.19 seconds + Average of 0.0020199847477738574 s per call + Subroutine report: + Function: GoParallel + N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.0008597476508027764 s per call + Subroutine report: + Function: compute + N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.0008147788304154591 s per call + Subroutine report: + + + Function: fourier gradient upsilon q + N = 93 calls took: 0 hours; 0 minutes; 0.05 seconds + Average of 0.0005139689291677167 s per call + + Function: fourier gradient Y * u + N = 93 calls took: 0 hours; 0 minutes; 0.05 seconds + Average of 0.0004989049767935148 s per call + + Function: fourier gradient julia + N = 93 calls took: 0 hours; 0 minutes; 0.09 seconds + Average of 0.0009624394037390268 s per call + + + Function: SymmetrizeFCQ + N = 93 calls took: 0 hours; 0 minutes; 0.90 seconds + Average of 0.009680781313168105 s per call + + Function: Symmetrize + N = 93 calls took: 0 hours; 0 minutes; 0.90 seconds + Average of 0.009720243433470367 s per call + + Function: update + N = 93 calls took: 0 hours; 0 minutes; 1.17 seconds + Average of 0.01262080797585108 s per call + Subroutine report: + Function: update_weights_fourier + N = 93 calls took: 0 hours; 0 minutes; 1.17 seconds + Average of 0.01257582890090122 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 93 calls took: 0 hours; 0 minutes; 0.76 seconds + Average of 0.008174468112248246 s per call + Subroutine report: + Function: DyagDinQ + N = 744 calls took: 0 hours; 0 minutes; 0.16 seconds + Average of 0.00021266104072652838 s per call + + Function: Manipulate polarization vectors + N = 744 calls took: 0 hours; 0 minutes; 0.13 seconds + Average of 0.00017434070187230264 s per call + + + Function: Time to get SSCHA energy and forces + N = 93 calls took: 0 hours; 0 minutes; 0.10 seconds + Average of 0.0011204622125112883 s per call + + Function: get upsilon fourier + N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.0008682435558688256 s per call + + Function: get uYu + N = 93 calls took: 0 hours; 0 minutes; 0.17 seconds + Average of 0.0018578780594692436 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = -0.0595 +- 0.0203 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.3958 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0836935185e+02 eV + Gibbs Free energy = -3.0836935185e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.395841778473766 +[CELL] unit_cell: +Cell([[2.723342240665962, 2.723342240665962, -4.322490091947834e-34], [2.723342240665962, 2.7068533300035466e-18, 2.723342240665962], [3.609137773338063e-18, 2.723342240665962, 2.723342240665962]]) +[CELL] CURRENT STRAIN: +[[ 2.89534103e-03 -4.42102081e-18 5.75011834e-18] + [-5.08556957e-18 2.89534103e-03 5.08556957e-18] + [-5.08556957e-18 5.08556957e-18 2.89534103e-03]] +[CELL] NEW STRESS: +[[-3.71368768e-04 3.88855050e-20 -1.16656515e-19] + [-3.88855050e-20 -3.71368768e-04 3.88855050e-20] + [-3.88855050e-20 3.88855050e-20 -3.71368768e-04]] +GRAD MAT: +[[ 1.50451892e-02 -1.64168381e-18 4.81234409e-18] + [ 1.49906828e-18 1.50451892e-02 -1.49906828e-18] + [ 1.49906828e-18 -1.49906828e-18 1.50451892e-02]] + +[CELL] y0 = 0.14141063624887285 | y1 = -0.009799396237494347 +[CELL] grad = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 + 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 + 1.50451892e-02] +[CELL] lastgrad = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 + -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 + -2.17110292e-01] +[CELL] GRADIENT DOT DIRECTION = 0.935193478393189 +[CELL] New step: +[CELL] X_OLD = [ 2.89534103e-03 -4.42102081e-18 5.75011834e-18 -5.08556957e-18 + 2.89534103e-03 5.08556957e-18 -5.08556957e-18 5.08556957e-18 + 2.89534103e-03] | ALPHA = 0.012471560100349277 +[CELL] DIRECTION = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 + 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 + 1.50451892e-02] +[CELL] GRADIENT = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 + 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 + 1.50451892e-02] +[CELL] X_NEW = [ 2.70770405e-03 -4.40054645e-18 5.69010090e-18 -5.10426529e-18 + 2.70770405e-03 5.10426529e-18 -5.10426529e-18 5.10426529e-18 + 2.70770405e-03] +[CELL] Step number = 2 + +NEW STRAIN: +[[ 2.70770405e-03 -4.40054645e-18 5.69010090e-18] + [-5.10426529e-18 2.70770405e-03 5.10426529e-18] + [-5.10426529e-18 5.10426529e-18 2.70770405e-03]] +NEW VOLUME: -40.373172406770884 + + Currently estimated bulk modulus = 99.136 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72283272 2.72283272 0.00000000) + v2 [A] = ( 2.72283272 0.00000000 2.72283272) + v3 [A] = ( 0.00000000 2.72283272 2.72283272) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. +[BFFS USED] For structure with id=0 +[BFFS USED] For structure with id=1 +[BFFS USED] For structure with id=2 +[BFFS USED] For structure with id=3 +[BFFS USED] For structure with id=4 +[BFFS USED] For structure with id=5 +[BFFS USED] For structure with id=6 +[BFFS USED] For structure with id=7 +[BFFS USED] For structure with id=8 +[BFFS USED] For structure with id=9 +[BFFS USED] For structure with id=10 +[BFFS USED] For structure with id=11 +[BFFS USED] For structure with id=12 +[BFFS USED] For structure with id=13 +[BFFS USED] For structure with id=14 +[BFFS USED] For structure with id=15 +[BFFS USED] For structure with id=16 +[BFFS USED] For structure with id=17 +[BFFS USED] For structure with id=18 +[BFFS USED] For structure with id=19 +[BFFS USED] For structure with id=20 +[BFFS USED] For structure with id=21 +[BFFS USED] For structure with id=22 +[BFFS USED] For structure with id=23 +[BFFS USED] For structure with id=24 +[BFFS USED] For structure with id=25 +[BFFS USED] For structure with id=26 +[BFFS USED] For structure with id=27 +[BFFS USED] For structure with id=28 +[BFFS USED] For structure with id=29 +[BFFS USED] For structure with id=30 +[BFFS USED] For structure with id=31 +[BFFS USED] For structure with id=32 +[BFFS USED] For structure with id=33 +[BFFS USED] For structure with id=34 +[BFFS USED] For structure with id=35 +[BFFS USED] For structure with id=36 +[BFFS USED] For structure with id=37 +[BFFS USED] For structure with id=38 +[BFFS USED] For structure with id=39 +[BFFS USED] For structure with id=40 +[BFFS USED] For structure with id=41 +[BFFS USED] For structure with id=42 +[BFFS USED] For structure with id=43 +[BFFS USED] For structure with id=44 +[BFFS USED] For structure with id=45 +[BFFS USED] For structure with id=46 +[BFFS USED] For structure with id=47 +[BFFS USED] For structure with id=48 +[BFFS USED] For structure with id=49 +=============== SUMMARY AIIDA CALCULATIONS =============== + +Total structures included: 50 +Structures not included : 0 +Steps using OTF-ML model : 50 + +===================== END OF SUMMARY ===================== + + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 94 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 74.00679849 meV +Anharmonic contribution to free energy = -308439.92916277 +- 1.20852972 meV +Free energy = -308365.92236428 +- 1.20852972 meV +FC gradient modulus = 13846.33536607 +- 310.51878255 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.37202425 meV/A +Kong-Liu effective sample size = 46.32075694267749 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 95 +Minimization step, force computed: 50 +Good step found with 0.15000000000000002, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 74.00679849 meV +Anharmonic contribution to free energy = -308439.92916277 +- 1.20852972 meV +Free energy = -308365.92236428 +- 1.20852972 meV +FC gradient modulus = 11422.48334105 +- 267.26801062 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.28302890 meV/A +Kong-Liu effective sample size = 46.32075694267749 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 96 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 65.92441896 meV +Anharmonic contribution to free energy = -308429.74078228 +- 1.40842512 meV +Free energy = -308363.81636331 +- 1.40842512 meV +FC gradient modulus = 11422.48334105 +- 267.26801062 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.28302890 meV/A +Kong-Liu effective sample size = 34.9459103862496 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 97 +Minimization step, force computed: 50 +Step too large (scalar = 0.5185671645618921 | kl_ratio = 0.7544330596647113), reducing to 0.19655560456875001 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 67.00119973 meV +Anharmonic contribution to free energy = -308431.05762978 +- 1.37647909 meV +Free energy = -308364.05643005 +- 1.37647909 meV +FC gradient modulus = 8408.87200984 +- 219.73668185 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22451081 meV/A +Kong-Liu effective sample size = 36.55518939004113 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 98 +Minimization step, force computed: 50 +Step too large (scalar = 0.5420016319160825 | kl_ratio = 0.7891751301749802), reducing to 0.17170713638838586 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 67.92756883 meV +Anharmonic contribution to free energy = -308432.20195236 +- 1.35034221 meV +Free energy = -308364.27438353 +- 1.35034221 meV +FC gradient modulus = 8787.29642952 +- 225.20548477 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22700703 meV/A +Kong-Liu effective sample size = 37.94459031264566 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 99 +Minimization step, force computed: 50 +Step too large (scalar = 0.5625325282378661 | kl_ratio = 0.8191703421341442), reducing to 0.15000000000705774 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 68.72638781 meV +Anharmonic contribution to free energy = -308433.19675967 +- 1.32882128 meV +Free energy = -308364.47037186 +- 1.32882128 meV +FC gradient modulus = 9119.05892036 +- 230.13759241 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23061947 meV/A +Kong-Liu effective sample size = 39.138667185990535 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 100 +Minimization step, force computed: 50 +Step too large (scalar = 0.5805011444072077 | kl_ratio = 0.8449487825603782), reducing to 0.1310370697186655 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 69.41654228 meV +Anharmonic contribution to free energy = -308434.06193355 +- 1.31098400 meV +Free energy = -308364.64539127 +- 1.31098400 meV +FC gradient modulus = 9409.57213877 +- 234.55466854 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23475972 meV/A +Kong-Liu effective sample size = 40.16159215936871 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 101 +Minimization step, force computed: 50 +Step too large (scalar = 0.5962160350058028 | kl_ratio = 0.8670322941628344), reducing to 0.11447142426430995 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 70.01376948 meV +Anharmonic contribution to free energy = -308434.81465982 +- 1.29610567 meV +Free energy = -308364.80089034 +- 1.29610567 meV +FC gradient modulus = 9663.75486880 +- 238.49006835 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23906447 meV/A +Kong-Liu effective sample size = 41.036097581614406 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 102 +Minimization step, force computed: 50 +Step too large (scalar = 0.6099531173240186 | kl_ratio = 0.8859116363835997), reducing to 0.10000000000941031 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 70.53127720 meV +Anharmonic contribution to free energy = -308435.46979905 +- 1.28362227 meV +Free energy = -308364.93852185 +- 1.28362227 meV +FC gradient modulus = 9886.02205286 +- 241.98262527 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24331211 meV/A +Kong-Liu effective sample size = 41.78288673064152 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 103 +Minimization step, force computed: 50 +Good step found with 0.10000000000941031, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 70.53127720 meV +Anharmonic contribution to free energy = -308435.46979905 +- 1.28362227 meV +Free energy = -308364.93852185 +- 1.28362227 meV +FC gradient modulus = 10080.30311094 +- 245.07286347 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24737147 meV/A +Kong-Liu effective sample size = 41.78288673064152 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 104 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 65.63486973 meV +Anharmonic contribution to free energy = -308429.37972239 +- 1.42292339 meV +Free energy = -308363.74485266 +- 1.42292339 meV +FC gradient modulus = 10080.30311094 +- 245.07286347 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24737147 meV/A +Kong-Liu effective sample size = 34.44521947111946 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 105 +Minimization step, force computed: 50 +Step too large (scalar = 0.4525818850588065 | kl_ratio = 0.8243858231523056), reducing to 0.13103706972483098 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 66.27426460 meV +Anharmonic contribution to free energy = -308430.15944334 +- 1.40252898 meV +Free energy = -308363.88517874 +- 1.40252898 meV +FC gradient modulus = 8313.17004633 +- 218.58729330 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22269119 meV/A +Kong-Liu effective sample size = 35.41001281409925 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 106 +Minimization step, force computed: 50 +Step too large (scalar = 0.46469977136723006 | kl_ratio = 0.8474764571048959), reducing to 0.11447142426969599 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 66.82771284 meV +Anharmonic contribution to free energy = -308430.83838820 +- 1.38539775 meV +Free energy = -308364.01067536 +- 1.38539775 meV +FC gradient modulus = 8535.19837265 +- 221.72469715 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22386741 meV/A +Kong-Liu effective sample size = 36.24836496177069 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 107 +Minimization step, force computed: 50 +Step too large (scalar = 0.4753062244390673 | kl_ratio = 0.8675409431485718), reducing to 0.10000000001411545 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 67.30739214 meV +Anharmonic contribution to free energy = -308431.42978306 +- 1.37094948 meV +Free energy = -308364.12239092 +- 1.37094948 meV +FC gradient modulus = 8729.60545415 +- 224.52108259 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22542044 meV/A +Kong-Liu effective sample size = 36.97599035849552 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 108 +Minimization step, force computed: 50 +Step too large (scalar = 0.4845853217026519 | kl_ratio = 0.8849553789058606), reducing to 0.08735804648733098 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 67.72359349 meV +Anharmonic contribution to free energy = -308431.94507698 +- 1.35871828 meV +Free energy = -308364.22148349 +- 1.35871828 meV +FC gradient modulus = 8899.73469791 +- 227.00441120 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22715382 meV/A +Kong-Liu effective sample size = 37.60707570817453 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 109 +Minimization step, force computed: 50 +Good step found with 0.08735804648733098, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 67.72359349 meV +Anharmonic contribution to free energy = -308431.94507698 +- 1.35871828 meV +Free energy = -308364.22148349 +- 1.35871828 meV +FC gradient modulus = 9048.55679011 +- 229.20339982 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22894054 meV/A +Kong-Liu effective sample size = 37.60707570817453 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 110 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 63.74038037 meV +Anharmonic contribution to free energy = -308427.09066847 +- 1.49246813 meV +Free energy = -308363.35028811 +- 1.49246813 meV +FC gradient modulus = 9048.55679011 +- 229.20339982 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22894054 meV/A +Kong-Liu effective sample size = 31.563557978236748 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 111 +Minimization step, force computed: 50 +Step too large (scalar = 0.37508079769239555 | kl_ratio = 0.8392983869090328), reducing to 0.11447142427508204 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 64.25786948 meV +Anharmonic contribution to free energy = -308427.71046372 +- 1.47360357 meV +Free energy = -308363.45259424 +- 1.47360357 meV +FC gradient modulus = 7674.79785242 +- 210.06257617 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22193601 meV/A +Kong-Liu effective sample size = 32.33535398602545 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 112 +Minimization step, force computed: 50 +Step too large (scalar = 0.3835214591947601 | kl_ratio = 0.8598210144533206), reducing to 0.1000000000188206 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 64.70647445 meV +Anharmonic contribution to free energy = -308428.25048569 +- 1.45758467 meV +Free energy = -308363.54401125 +- 1.45758467 meV +FC gradient modulus = 7847.12114019 +- 212.32953525 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22132286 meV/A +Kong-Liu effective sample size = 33.0094085770546 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 113 +Minimization step, force computed: 50 +Step too large (scalar = 0.3909114167647833 | kl_ratio = 0.8777446253253733), reducing to 0.08735804649144131 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 65.09578128 meV +Anharmonic contribution to free energy = -308428.72114873 +- 1.44394533 meV +Free energy = -308363.62536745 +- 1.44394533 meV +FC gradient modulus = 7998.04041870 +- 214.34909894 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22118438 meV/A +Kong-Liu effective sample size = 33.59759842143758 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 114 +Minimization step, force computed: 50 +Step too large (scalar = 0.39737866071968775 | kl_ratio = 0.8933850289809846), reducing to 0.0763142828536454 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 65.43393583 meV +Anharmonic contribution to free energy = -308429.13147387 +- 1.43230165 meV +Free energy = -308363.69753804 +- 1.43230165 meV +FC gradient modulus = 8130.15020412 +- 216.14221001 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22135096 meV/A +Kong-Liu effective sample size = 34.11057097684625 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 115 +Minimization step, force computed: 50 +Good step found with 0.0763142828536454, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 65.43393583 meV +Anharmonic contribution to free energy = -308429.13147387 +- 1.43230165 meV +Free energy = -308363.69753804 +- 1.43230165 meV +FC gradient modulus = 8245.75060406 +- 217.72998440 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22170625 meV/A +Kong-Liu effective sample size = 34.11057097684625 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 116 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 62.16343702 meV +Anharmonic contribution to free energy = -308425.21460867 +- 1.55709168 meV +Free energy = -308363.05117165 +- 1.55709168 meV +FC gradient modulus = 8245.75060406 +- 217.72998440 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22170625 meV/A +Kong-Liu effective sample size = 29.19821458706225 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 117 +Minimization step, force computed: 50 +Step too large (scalar = 0.319033127095163 | kl_ratio = 0.8559872717135566), reducing to 0.10000000002352576 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 62.58654686 meV +Anharmonic contribution to free energy = -308425.71394938 +- 1.53999757 meV +Free energy = -308363.12740252 +- 1.53999757 meV +FC gradient modulus = 7163.20626744 +- 203.67634117 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22578104 meV/A +Kong-Liu effective sample size = 29.81870737154356 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 118 +Minimization step, force computed: 50 +Step too large (scalar = 0.3250908334270587 | kl_ratio = 0.8741779019701564), reducing to 0.08735804649555164 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 62.95378497 meV +Anharmonic contribution to free energy = -308426.14917154 +- 1.52536773 meV +Free energy = -308363.19538658 +- 1.52536773 meV +FC gradient modulus = 7298.95515866 +- 205.34427718 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22411903 meV/A +Kong-Liu effective sample size = 30.361603938882922 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 119 +Minimization step, force computed: 50 +Step too large (scalar = 0.33039445255715855 | kl_ratio = 0.8900936885369619), reducing to 0.0763142828572361 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 63.27281222 meV +Anharmonic contribution to free energy = -308426.52861835 +- 1.51282308 meV +Free energy = -308363.25580612 +- 1.51282308 meV +FC gradient modulus = 7417.83620348 +- 206.82875825 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22296606 meV/A +Kong-Liu effective sample size = 30.836283465096415 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 120 +Minimization step, force computed: 50 +Good step found with 0.0763142828572361, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 63.27281222 meV +Anharmonic contribution to free energy = -308426.52861835 +- 1.51282308 meV +Free energy = -308363.25580612 +- 1.51282308 meV +FC gradient modulus = 7521.90168276 +- 208.14590624 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22217707 meV/A +Kong-Liu effective sample size = 30.836283465096415 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 121 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 60.18667295 meV +Anharmonic contribution to free energy = -308422.90144690 +- 1.64514280 meV +Free energy = -308362.71477395 +- 1.64514280 meV +FC gradient modulus = 7521.90168276 +- 208.14590624 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22217707 meV/A +Kong-Liu effective sample size = 26.312430497175804 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 122 +Minimization step, force computed: 50 +Step too large (scalar = 0.26601890477707346 | kl_ratio = 0.8532944810602368), reducing to 0.1000000000282309 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 60.58572020 meV +Anharmonic contribution to free energy = -308423.36395542 +- 1.62732155 meV +Free energy = -308362.77823522 +- 1.62732155 meV +FC gradient modulus = 6547.65853456 +- 196.56403259 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23731287 meV/A +Kong-Liu effective sample size = 26.879932664876105 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 123 +Minimization step, force computed: 50 +Step too large (scalar = 0.27098603624692286 | kl_ratio = 0.8716981959029368), reducing to 0.08735804649966196 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 60.93212609 meV +Anharmonic contribution to free energy = -308423.76703534 +- 1.61199825 meV +Free energy = -308362.83490925 +- 1.61199825 meV +FC gradient modulus = 6669.68194009 +- 197.92630473 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23421148 meV/A +Kong-Liu effective sample size = 27.377234159926388 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 124 +Minimization step, force computed: 50 +Step too large (scalar = 0.27533610374810813 | kl_ratio = 0.8878253499944206), reducing to 0.0763142828608268 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 61.23309522 meV +Anharmonic contribution to free energy = -308424.11843412 +- 1.59880400 meV +Free energy = -308362.88533890 +- 1.59880400 meV +FC gradient modulus = 6776.57285239 +- 199.14192938 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.23181136 meV/A +Kong-Liu effective sample size = 27.812681619985323 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 125 +Minimization step, force computed: 50 +Good step found with 0.0763142828608268, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 61.23309522 meV +Anharmonic contribution to free energy = -308424.11843412 +- 1.59880400 meV +Free energy = -308362.88533890 +- 1.59880400 meV +FC gradient modulus = 6870.16682546 +- 200.22288295 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22994052 meV/A +Kong-Liu effective sample size = 27.812681619985323 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 126 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 58.32032669 meV +Anharmonic contribution to free energy = -308420.75247121 +- 1.73581984 meV +Free energy = -308362.43214452 +- 1.73581984 meV +FC gradient modulus = 6870.16682546 +- 200.22288295 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.22994052 meV/A +Kong-Liu effective sample size = 23.66977053438384 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 127 +Minimization step, force computed: 50 +Step too large (scalar = 0.22240876907354018 | kl_ratio = 0.8510423718860494), reducing to 0.10000000003293603 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 58.69676058 meV +Anharmonic contribution to free energy = -308421.18191561 +- 1.71765362 meV +Free energy = -308362.48515503 +- 1.71765362 meV +FC gradient modulus = 5993.53225344 +- 190.78000686 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.25557256 meV/A +Kong-Liu effective sample size = 24.187106438106223 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 128 +Minimization step, force computed: 50 +Step too large (scalar = 0.22648777637025558 | kl_ratio = 0.8696430919025846), reducing to 0.08735804650377227 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 59.02358509 meV +Anharmonic contribution to free energy = -308421.55611144 +- 1.70196484 meV +Free energy = -308362.53252635 +- 1.70196484 meV +FC gradient modulus = 6103.25255342 +- 191.87950672 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.25110569 meV/A +Kong-Liu effective sample size = 24.640947669391444 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 129 +Minimization step, force computed: 50 +Step too large (scalar = 0.23006066781087356 | kl_ratio = 0.8859608723124788), reducing to 0.0763142828644175 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 59.30757756 meV +Anharmonic contribution to free energy = -308421.88228087 +- 1.68840482 meV +Free energy = -308362.57470331 +- 1.68840482 meV +FC gradient modulus = 6199.38087530 +- 192.86360150 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24752233 meV/A +Kong-Liu effective sample size = 25.03874107922509 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 130 +Minimization step, force computed: 50 +Good step found with 0.0763142828644175, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 59.30757756 meV +Anharmonic contribution to free energy = -308421.88228087 +- 1.68840482 meV +Free energy = -308362.57470331 +- 1.68840482 meV +FC gradient modulus = 6283.56362438 +- 193.74084284 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24462501 meV/A +Kong-Liu effective sample size = 25.03874107922509 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 131 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 56.55739302 meV +Anharmonic contribution to free energy = -308418.75052510 +- 1.82704981 meV +Free energy = -308362.19313208 +- 1.82704981 meV +FC gradient modulus = 6283.56362438 +- 193.74084284 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.24462501 meV/A +Kong-Liu effective sample size = 21.258373540677443 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 132 +Minimization step, force computed: 50 +Step too large (scalar = 0.1864746286905306 | kl_ratio = 0.849019264723167), reducing to 0.10000000003764119 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 56.91263586 meV +Anharmonic contribution to free energy = -308419.15039150 +- 1.80893861 meV +Free energy = -308362.23775564 +- 1.80893861 meV +FC gradient modulus = 5494.23528413 +- 186.13268972 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.28027060 meV/A +Kong-Liu effective sample size = 21.728592689449034 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 133 +Minimization step, force computed: 50 +Step too large (scalar = 0.18983226586604754 | kl_ratio = 0.8677989288957294), reducing to 0.0873580465078826 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 57.22110668 meV +Anharmonic contribution to free energy = -308419.49873591 +- 1.79323460 meV +Free energy = -308362.27762923 +- 1.79323460 meV +FC gradient modulus = 5592.99607839 +- 187.00798407 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.27450000 meV/A +Kong-Liu effective sample size = 22.14151629563222 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 134 +Minimization step, force computed: 50 +Step too large (scalar = 0.1927735295055105 | kl_ratio = 0.8842903173755516), reducing to 0.07631428286800819 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 57.48918398 meV +Anharmonic contribution to free energy = -308419.80231408 +- 1.77961210 meV +Free energy = -308362.31313011 +- 1.77961210 meV +FC gradient modulus = 5679.52738207 +- 187.79425313 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.26978714 meV/A +Kong-Liu effective sample size = 22.503769685579332 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 135 +Minimization step, force computed: 50 +Step too large (scalar = 0.19534899174865383 | kl_ratio = 0.8987580331764743), reducing to 0.06666666669489756 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 57.72232101 meV +Anharmonic contribution to free energy = -308420.06696593 +- 1.76779001 meV +Free energy = -308362.34464492 +- 1.76779001 meV +FC gradient modulus = 5755.31034244 +- 188.49722367 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.26591016 meV/A +Kong-Liu effective sample size = 22.82132312079843 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 136 +Minimization step, force computed: 50 +Good step found with 0.06666666669489756, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 57.72232101 meV +Anharmonic contribution to free energy = -308420.06696593 +- 1.76779001 meV +Free energy = -308362.34464492 +- 1.76779001 meV +FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A +Kong-Liu effective sample size = 22.82132312079843 + + +The gw gradient satisfy the convergence condition. +KL: 22.82132312079843 KL/N: 0.45642646241596857 KL RAT: 0.5 + According to your input criteria + you are out of the statistical sampling. +Check the stopping criteria: Running = False +ROOT NAME: ./minim_t0 +SAVE NAME: ./minim_t0 +FNAME NAME: None + +Restoring the last good dynamical matrix. +Updating the importance sampling... + + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 136 steps + +Free energy = -308362.34464492 +- 1.76779001 meV +FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A +Kong-Liu effective sample size = 22.82132312079843 + +Total force on the centroids [eV/A]: + 0) -0.000000 0.000000 0.000000 +- -0.000000 0.000000 0.000000 + 1) 0.000000 -0.000000 0.000000 +- 0.000000 -0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + 0.09021141 0.00000000 0.00000000 0.01405083 0.00000000 0.00000000 + 0.00000000 0.09021141 -0.00000000 +- 0.00000000 0.01405083 0.00000000 + -0.00000000 -0.00000000 0.09021141 0.00000000 0.00000000 0.01405083 + + Ab initio average stress [GPa]: + -0.15675322 -0.00000000 -0.00000000 + -0.00000000 -0.15675322 0.00000000 + -0.00000000 -0.00000000 -0.15675322 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 3 calls took: 0 hours; 0 minutes; 0.66 seconds +Average of 0.21869913736979166 s per call +Subroutine report: + Function: GoParallel + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21760932604471842 s per call + Subroutine report: + Function: compute + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21755274136861166 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21772448221842447 s per call + + +Function: minimization_step +N = 136 calls took: 0 hours; 0 minutes; 4.82 seconds +Average of 0.03541784426745247 s per call +Subroutine report: + Function: get_fourier_gradient + N = 136 calls took: 0 hours; 0 minutes; 0.29 seconds + Average of 0.00213162338032442 s per call + Subroutine report: + Function: GoParallel + N = 136 calls took: 0 hours; 0 minutes; 0.14 seconds + Average of 0.0009944105849546544 s per call + Subroutine report: + Function: compute + N = 136 calls took: 0 hours; 0 minutes; 0.13 seconds + Average of 0.0009495317935943604 s per call + Subroutine report: + + + Function: fourier gradient upsilon q + N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.0005079016965978286 s per call + + Function: fourier gradient Y * u + N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.0004844542811898624 s per call + + Function: fourier gradient julia + N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds + Average of 0.0010951547061695771 s per call + + + Function: SymmetrizeFCQ + N = 136 calls took: 0 hours; 0 minutes; 1.31 seconds + Average of 0.009660698035184075 s per call + + Function: Symmetrize + N = 136 calls took: 0 hours; 0 minutes; 1.32 seconds + Average of 0.009690807146184584 s per call + + Function: update + N = 136 calls took: 0 hours; 0 minutes; 1.70 seconds + Average of 0.012504090281093823 s per call + Subroutine report: + Function: update_weights_fourier + N = 136 calls took: 0 hours; 0 minutes; 1.69 seconds + Average of 0.012458666282541612 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 136 calls took: 0 hours; 0 minutes; 1.11 seconds + Average of 0.008144212119719562 s per call + Subroutine report: + Function: DyagDinQ + N = 1088 calls took: 0 hours; 0 minutes; 0.23 seconds + Average of 0.00021121716674636393 s per call + + Function: Manipulate polarization vectors + N = 1088 calls took: 0 hours; 0 minutes; 0.19 seconds + Average of 0.00017375148394528558 s per call + + + Function: Time to get SSCHA energy and forces + N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds + Average of 0.0011188352809232823 s per call + + Function: get upsilon fourier + N = 136 calls took: 0 hours; 0 minutes; 0.12 seconds + Average of 0.0008731326636146096 s per call + + Function: get uYu + N = 136 calls took: 0 hours; 0 minutes; 0.24 seconds + Average of 0.00176697618821088 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = 0.0902 +- 0.0141 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.3732 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0836234464e+02 eV + Gibbs Free energy = -3.0836234464e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.373172406770884 +[CELL] unit_cell: +Cell([[2.7228327161963652, 2.7228327161963652, 1.5195328858278707e-34], [2.7228327161963652, 1.5195328858278707e-34, 2.7228327161963652], [3.501759329709108e-18, 2.7228327161963652, 2.7228327161963652]]) +[CELL] CURRENT STRAIN: +[[ 2.70770405e-03 5.78492681e-18 -4.49537236e-18] + [ 5.14014958e-18 2.70770405e-03 -5.14014958e-18] + [ 5.14014958e-18 -5.14014958e-18 2.70770405e-03]] +[CELL] NEW STRESS: +[[ 5.63055310e-04 0.00000000e+00 3.88855050e-20] + [ 3.88855050e-20 5.63055310e-04 -3.88855050e-20] + [-1.16656515e-19 -7.77710099e-20 5.63055310e-04]] +GRAD MAT: +[[-2.27938815e-02 -1.31504860e-19 -1.47199182e-18] + [-1.69102968e-18 -2.27938815e-02 1.69102968e-18] + [ 4.60569874e-18 3.26521178e-18 -2.27938815e-02]] + +[CELL] y0 = 0.000679073152958703 | y1 = -0.0010288147802553307 +[CELL] grad = [-2.27938815e-02 -1.31504860e-19 -1.47199182e-18 -1.69102968e-18 + -2.27938815e-02 1.69102968e-18 4.60569874e-18 3.26521178e-18 + -2.27938815e-02] +[CELL] lastgrad = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 + 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 + 1.50451892e-02] +[CELL] GRADIENT DOT DIRECTION = 0.3976099015353843 +[CELL] Step not good: +[CELL] X_START = [ 2.89534103e-03 -4.42102081e-18 5.75011834e-18 -5.08556957e-18 + 2.89534103e-03 5.08556957e-18 -5.08556957e-18 5.08556957e-18 + 2.89534103e-03] | ALPHA = 0.0062357800501746385 +[CELL] DIRECTION = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 + 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 + 1.50451892e-02] +[CELL] GRADIENT = [-2.27938815e-02 -1.31504860e-19 -1.47199182e-18 -1.69102968e-18 + -2.27938815e-02 1.69102968e-18 4.60569874e-18 3.26521178e-18 + -2.27938815e-02] +[CELL] X_NEW = [ 2.80152254e-03 -4.41078363e-18 5.72010962e-18 -5.09491743e-18 + 2.80152254e-03 5.09491743e-18 -5.09491743e-18 5.09491743e-18 + 2.80152254e-03] +[CELL] Step number = 3 + +NEW STRAIN: +[[ 2.80152254e-03 -4.41078363e-18 5.72010962e-18] + [-5.09491743e-18 2.80152254e-03 5.09491743e-18] + [-5.09491743e-18 5.09491743e-18 2.80152254e-03]] +NEW VOLUME: -40.384506032190046 + + Currently estimated bulk modulus = 106.066 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72308748 2.72308748 -0.00000000) + v2 [A] = ( 2.72308748 -0.00000000 2.72308748) + v3 [A] = ( 0.00000000 2.72308748 2.72308748) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 136 steps + +Free energy = -308362.34464492 +- 1.76779001 meV +FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 +Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A +Kong-Liu effective sample size = 22.82132312079843 + +Total force on the centroids [eV/A]: + 0) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + 1) 0.000000 -0.000000 0.000000 +- -0.000000 0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + 0.09021141 0.00000000 0.00000000 0.01405083 0.00000000 0.00000000 + 0.00000000 0.09021141 -0.00000000 +- 0.00000000 0.01405083 0.00000000 + -0.00000000 -0.00000000 0.09021141 0.00000000 0.00000000 0.01405083 + + Ab initio average stress [GPa]: + -0.15675322 -0.00000000 -0.00000000 + -0.00000000 -0.15675322 0.00000000 + -0.00000000 -0.00000000 -0.15675322 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 3 calls took: 0 hours; 0 minutes; 0.66 seconds +Average of 0.21869913736979166 s per call +Subroutine report: + Function: GoParallel + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21760932604471842 s per call + Subroutine report: + Function: compute + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21755274136861166 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds + Average of 0.21772448221842447 s per call + + +Function: minimization_step +N = 136 calls took: 0 hours; 0 minutes; 4.82 seconds +Average of 0.03541784426745247 s per call +Subroutine report: + Function: get_fourier_gradient + N = 136 calls took: 0 hours; 0 minutes; 0.29 seconds + Average of 0.00213162338032442 s per call + Subroutine report: + Function: GoParallel + N = 136 calls took: 0 hours; 0 minutes; 0.14 seconds + Average of 0.0009944105849546544 s per call + Subroutine report: + Function: compute + N = 136 calls took: 0 hours; 0 minutes; 0.13 seconds + Average of 0.0009495317935943604 s per call + Subroutine report: + + + Function: fourier gradient upsilon q + N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.0005079016965978286 s per call + + Function: fourier gradient Y * u + N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.0004844542811898624 s per call + + Function: fourier gradient julia + N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds + Average of 0.0010951547061695771 s per call + + + Function: SymmetrizeFCQ + N = 136 calls took: 0 hours; 0 minutes; 1.31 seconds + Average of 0.009660698035184075 s per call + + Function: Symmetrize + N = 136 calls took: 0 hours; 0 minutes; 1.32 seconds + Average of 0.009690807146184584 s per call + + Function: update + N = 136 calls took: 0 hours; 0 minutes; 1.70 seconds + Average of 0.012504090281093823 s per call + Subroutine report: + Function: update_weights_fourier + N = 136 calls took: 0 hours; 0 minutes; 1.69 seconds + Average of 0.012458666282541612 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 136 calls took: 0 hours; 0 minutes; 1.11 seconds + Average of 0.008144212119719562 s per call + Subroutine report: + Function: DyagDinQ + N = 1088 calls took: 0 hours; 0 minutes; 0.23 seconds + Average of 0.00021121716674636393 s per call + + Function: Manipulate polarization vectors + N = 1088 calls took: 0 hours; 0 minutes; 0.19 seconds + Average of 0.00017375148394528558 s per call + + + Function: Time to get SSCHA energy and forces + N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds + Average of 0.0011188352809232823 s per call + + Function: get upsilon fourier + N = 136 calls took: 0 hours; 0 minutes; 0.12 seconds + Average of 0.0008731326636146096 s per call + + Function: get uYu + N = 136 calls took: 0 hours; 0 minutes; 0.24 seconds + Average of 0.00176697618821088 s per call + + + + + + END OF TIMER REPORT +===================== + diff --git a/Examples/sscha_and_aiida/log3 b/Examples/sscha_and_aiida/log3 new file mode 100644 index 00000000..64bb1567 --- /dev/null +++ b/Examples/sscha_and_aiida/log3 @@ -0,0 +1,1273 @@ +Number of symmetry inequivalent displacements: 1 +Force computed shape: 50 +Computing configuration 1 out of 50 (nat = 16) +Computing configuration 2 out of 50 (nat = 16) +Computing configuration 3 out of 50 (nat = 16) +Computing configuration 4 out of 50 (nat = 16) +Computing configuration 5 out of 50 (nat = 16) +Computing configuration 6 out of 50 (nat = 16) +Computing configuration 7 out of 50 (nat = 16) +Computing configuration 8 out of 50 (nat = 16) +Computing configuration 9 out of 50 (nat = 16) +Computing configuration 10 out of 50 (nat = 16) +Computing configuration 11 out of 50 (nat = 16) +Computing configuration 12 out of 50 (nat = 16) +Computing configuration 13 out of 50 (nat = 16) +Computing configuration 14 out of 50 (nat = 16) +Computing configuration 15 out of 50 (nat = 16) +Computing configuration 16 out of 50 (nat = 16) +Computing configuration 17 out of 50 (nat = 16) +Computing configuration 18 out of 50 (nat = 16) +Computing configuration 19 out of 50 (nat = 16) +Computing configuration 20 out of 50 (nat = 16) +Computing configuration 21 out of 50 (nat = 16) +Computing configuration 22 out of 50 (nat = 16) +Computing configuration 23 out of 50 (nat = 16) +Computing configuration 24 out of 50 (nat = 16) +Computing configuration 25 out of 50 (nat = 16) +Computing configuration 26 out of 50 (nat = 16) +Computing configuration 27 out of 50 (nat = 16) +Computing configuration 28 out of 50 (nat = 16) +Computing configuration 29 out of 50 (nat = 16) +Computing configuration 30 out of 50 (nat = 16) +Computing configuration 31 out of 50 (nat = 16) +Computing configuration 32 out of 50 (nat = 16) +Computing configuration 33 out of 50 (nat = 16) +Computing configuration 34 out of 50 (nat = 16) +Computing configuration 35 out of 50 (nat = 16) +Computing configuration 36 out of 50 (nat = 16) +Computing configuration 37 out of 50 (nat = 16) +Computing configuration 38 out of 50 (nat = 16) +Computing configuration 39 out of 50 (nat = 16) +Computing configuration 40 out of 50 (nat = 16) +Computing configuration 41 out of 50 (nat = 16) +Computing configuration 42 out of 50 (nat = 16) +Computing configuration 43 out of 50 (nat = 16) +Computing configuration 44 out of 50 (nat = 16) +Computing configuration 45 out of 50 (nat = 16) +Computing configuration 46 out of 50 (nat = 16) +Computing configuration 47 out of 50 (nat = 16) +Computing configuration 48 out of 50 (nat = 16) +Computing configuration 49 out of 50 (nat = 16) +Computing configuration 50 out of 50 (nat = 16) +Force computed shape: 50 + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 1 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.20417178 meV +Anharmonic contribution to free energy = -308491.83663769 +- 0.18821541 meV +Free energy = -308373.63246591 +- 0.18821541 meV +FC gradient modulus = 182.75557442 +- 90.14152625 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43309923 meV/A +Kong-Liu effective sample size = 49.99931246175452 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 2 +Minimization step, force computed: 50 +Good step found with 0.15000000000000002, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.20417178 meV +Anharmonic contribution to free energy = -308491.83663769 +- 0.18821541 meV +Free energy = -308373.63246591 +- 0.18821541 meV +FC gradient modulus = 152.95855939 +- 90.10531616 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43327265 meV/A +Kong-Liu effective sample size = 49.99931246175452 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 3 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.15072753 meV +Anharmonic contribution to free energy = -308491.78549128 +- 0.18790604 meV +Free energy = -308373.63476375 +- 0.18790604 meV +FC gradient modulus = 152.95855939 +- 90.10531616 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43327265 meV/A +Kong-Liu effective sample size = 49.996444413429145 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 4 +Minimization step, force computed: 50 +Good step found with 0.22500000000000003, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.15072753 meV +Anharmonic contribution to free energy = -308491.78549128 +- 0.18790604 meV +Free energy = -308373.63476375 +- 0.18790604 meV +FC gradient modulus = 115.77849587 +- 90.06940684 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43351103 meV/A +Kong-Liu effective sample size = 49.996444413429145 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 5 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.08761323 meV +Anharmonic contribution to free energy = -308491.72512389 +- 0.18759715 meV +Free energy = -308373.63751066 +- 0.18759715 meV +FC gradient modulus = 115.77849587 +- 90.06940684 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43351103 meV/A +Kong-Liu effective sample size = 49.99031730556114 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 6 +Minimization step, force computed: 50 +Good step found with 0.3375, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.08761323 meV +Anharmonic contribution to free energy = -308491.72512389 +- 0.18759715 meV +Free energy = -308373.63751066 +- 0.18759715 meV +FC gradient modulus = 74.01158891 +- 90.04266371 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43382080 meV/A +Kong-Liu effective sample size = 49.99031730556114 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 7 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.02315360 meV +Anharmonic contribution to free energy = -308491.66360756 +- 0.18733845 meV +Free energy = -308373.64045397 +- 0.18733845 meV +FC gradient modulus = 74.01158891 +- 90.04266371 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43382080 meV/A +Kong-Liu effective sample size = 49.98128027174389 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 8 +Minimization step, force computed: 50 +Good step found with 0.5062500000000001, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 118.02315360 meV +Anharmonic contribution to free energy = -308491.66360756 +- 0.18733845 meV +Free energy = -308373.64045397 +- 0.18733845 meV +FC gradient modulus = 34.77896702 +- 90.03402519 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43418490 meV/A +Kong-Liu effective sample size = 49.98128027174389 + + +The gc gradient satisfy the convergence condition. + +The gw gradient satisfy the convergence condition. +The system satisfy the convergence criteria according to the input. +Check the stopping criteria: Running = False +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 8 steps + +Free energy = -308373.64045397 +- 0.18733845 meV +FC gradient modulus = 34.77896702 +- 90.03402519 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.43418490 meV/A +Kong-Liu effective sample size = 49.98128027174389 + +Total force on the centroids [eV/A]: + 0) 0.000000 -0.000000 0.000000 +- 0.000000 0.000000 -0.000000 + 1) 0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + 0.81636588 0.00000000 -0.00000000 0.01024800 0.00000000 0.00000000 + 0.00000000 0.81636588 -0.00000000 +- 0.00000000 0.01024800 0.00000000 + -0.00000000 -0.00000000 0.81636588 0.00000000 0.00000000 0.01024800 + + Ab initio average stress [GPa]: + 0.66256699 0.00000000 -0.00000000 + 0.00000000 0.66256699 0.00000000 + -0.00000000 0.00000000 0.66256699 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds +Average of 0.8426022529602051 s per call +Subroutine report: + Function: GoParallel + N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.8413608074188232 s per call + Subroutine report: + Function: compute + N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.8412981033325195 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.8415110111236572 s per call + + +Function: minimization_step +N = 8 calls took: 0 hours; 0 minutes; 0.28 seconds +Average of 0.035197049379348755 s per call +Subroutine report: + Function: get_fourier_gradient + N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0017607808113098145 s per call + Subroutine report: + Function: GoParallel + N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds + Average of 0.0006138086318969727 s per call + Subroutine report: + Function: compute + N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds + Average of 0.0005699694156646729 s per call + Subroutine report: + + + Function: fourier gradient upsilon q + N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds + Average of 0.0005290806293487549 s per call + + Function: fourier gradient Y * u + N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds + Average of 0.0004737973213195801 s per call + + Function: fourier gradient julia + N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0007123053073883057 s per call + + + Function: SymmetrizeFCQ + N = 8 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.009617865085601807 s per call + + Function: Symmetrize + N = 8 calls took: 0 hours; 0 minutes; 0.08 seconds + Average of 0.009717166423797607 s per call + + Function: update + N = 8 calls took: 0 hours; 0 minutes; 0.10 seconds + Average of 0.0125904381275177 s per call + Subroutine report: + Function: update_weights_fourier + N = 8 calls took: 0 hours; 0 minutes; 0.10 seconds + Average of 0.012545883655548096 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 8 calls took: 0 hours; 0 minutes; 0.07 seconds + Average of 0.008427917957305908 s per call + Subroutine report: + Function: DyagDinQ + N = 64 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0002085752785205841 s per call + + Function: Manipulate polarization vectors + N = 64 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.00017771124839782715 s per call + + + Function: Time to get SSCHA energy and forces + N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0011301040649414062 s per call + + Function: get upsilon fourier + N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0008168518543243408 s per call + + Function: get uYu + N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.001642853021621704 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = 0.8164 +- 0.0102 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.0470 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0837364045e+02 eV + Gibbs Free energy = -3.0837364045e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.04698463143717 +[CELL] unit_cell: +Cell([[2.71548, 2.71548, 0.0], [2.71548, 0.0, 2.71548], [0.0, 2.71548, 2.71548]]) +[CELL] CURRENT STRAIN: +[[ 0.00000000e+00 4.39618027e-18 -4.39618027e-18] + [ 4.39618027e-18 0.00000000e+00 -4.39618027e-18] + [ 4.39618027e-18 -4.39618027e-18 0.00000000e+00]] +[CELL] NEW STRESS: +[[ 5.09535512e-03 1.86650424e-18 -2.48867232e-18] + [ 1.24433616e-18 5.09535512e-03 -1.86650424e-18] + [-9.33252119e-19 -1.86650424e-18 5.09535512e-03]] +GRAD MAT: +[[-2.04053608e-01 -7.56449230e-17 1.00560878e-16] + [-5.07289675e-17 -2.04053608e-01 7.56449230e-17] + [ 3.64768768e-17 7.56449230e-17 -2.04053608e-01]] + +[CELL] New step: +[CELL] X_OLD = [ 0.00000000e+00 4.39618027e-18 -4.39618027e-18 4.39618027e-18 + 0.00000000e+00 -4.39618027e-18 4.39618027e-18 -4.39618027e-18 + 0.00000000e+00] | ALPHA = 0.013335807390121452 +[CELL] DIRECTION = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 + -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 + -2.04053608e-01] +[CELL] GRADIENT = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 + -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 + -2.04053608e-01] +[CELL] X_NEW = [ 2.72121961e-03 5.40496639e-18 -5.73724078e-18 5.07269201e-18 + 2.72121961e-03 -5.40496639e-18 3.90973167e-18 -5.40496639e-18 + 2.72121961e-03] +[CELL] Step number = 1 + +NEW STRAIN: +[[ 2.72121961e-03 5.40496639e-18 -5.73724078e-18] + [ 5.07269201e-18 2.72121961e-03 -5.40496639e-18] + [ 3.90973167e-18 -5.40496639e-18 2.72121961e-03]] +NEW VOLUME: -40.374805006719775 + + Currently estimated bulk modulus = 100.000 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72286942 2.72286942 -0.00000000) + v2 [A] = ( 2.72286942 -0.00000000 2.72286942) + v3 [A] = ( -0.00000000 2.72286942 2.72286942) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. +Force computed shape: 50 +Computing configuration 1 out of 50 (nat = 16) +Computing configuration 2 out of 50 (nat = 16) +Computing configuration 3 out of 50 (nat = 16) +Computing configuration 4 out of 50 (nat = 16) +Computing configuration 5 out of 50 (nat = 16) +Computing configuration 6 out of 50 (nat = 16) +Computing configuration 7 out of 50 (nat = 16) +Computing configuration 8 out of 50 (nat = 16) +Computing configuration 9 out of 50 (nat = 16) +Computing configuration 10 out of 50 (nat = 16) +Computing configuration 11 out of 50 (nat = 16) +Computing configuration 12 out of 50 (nat = 16) +Computing configuration 13 out of 50 (nat = 16) +Computing configuration 14 out of 50 (nat = 16) +Computing configuration 15 out of 50 (nat = 16) +Computing configuration 16 out of 50 (nat = 16) +Computing configuration 17 out of 50 (nat = 16) +Computing configuration 18 out of 50 (nat = 16) +Computing configuration 19 out of 50 (nat = 16) +Computing configuration 20 out of 50 (nat = 16) +Computing configuration 21 out of 50 (nat = 16) +Computing configuration 22 out of 50 (nat = 16) +Computing configuration 23 out of 50 (nat = 16) +Computing configuration 24 out of 50 (nat = 16) +Computing configuration 25 out of 50 (nat = 16) +Computing configuration 26 out of 50 (nat = 16) +Computing configuration 27 out of 50 (nat = 16) +Computing configuration 28 out of 50 (nat = 16) +Computing configuration 29 out of 50 (nat = 16) +Computing configuration 30 out of 50 (nat = 16) +Computing configuration 31 out of 50 (nat = 16) +Computing configuration 32 out of 50 (nat = 16) +Computing configuration 33 out of 50 (nat = 16) +Computing configuration 34 out of 50 (nat = 16) +Computing configuration 35 out of 50 (nat = 16) +Computing configuration 36 out of 50 (nat = 16) +Computing configuration 37 out of 50 (nat = 16) +Computing configuration 38 out of 50 (nat = 16) +Computing configuration 39 out of 50 (nat = 16) +Computing configuration 40 out of 50 (nat = 16) +Computing configuration 41 out of 50 (nat = 16) +Computing configuration 42 out of 50 (nat = 16) +Computing configuration 43 out of 50 (nat = 16) +Computing configuration 44 out of 50 (nat = 16) +Computing configuration 45 out of 50 (nat = 16) +Computing configuration 46 out of 50 (nat = 16) +Computing configuration 47 out of 50 (nat = 16) +Computing configuration 48 out of 50 (nat = 16) +Computing configuration 49 out of 50 (nat = 16) +Computing configuration 50 out of 50 (nat = 16) +Force computed shape: 50 + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 9 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.95071445 meV +Anharmonic contribution to free energy = -308492.27277791 +- 0.12630427 meV +Free energy = -308374.32206346 +- 0.12630427 meV +FC gradient modulus = 571.33305580 +- 87.20487894 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.37164914 meV/A +Kong-Liu effective sample size = 49.98834525233436 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 10 +Minimization step, force computed: 50 +Good step found with 0.15000000000000002, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.95071445 meV +Anharmonic contribution to free energy = -308492.27277791 +- 0.12630427 meV +Free energy = -308374.32206346 +- 0.12630427 meV +FC gradient modulus = 483.77196318 +- 87.04634377 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.37099603 meV/A +Kong-Liu effective sample size = 49.98834525233436 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 11 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.85765758 meV +Anharmonic contribution to free energy = -308492.18364013 +- 0.12392259 meV +Free energy = -308374.32598255 +- 0.12392259 meV +FC gradient modulus = 483.77196318 +- 87.04634377 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.37099603 meV/A +Kong-Liu effective sample size = 49.9409735529959 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 12 +Minimization step, force computed: 50 +Good step found with 0.22500000000000003, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.85765758 meV +Anharmonic contribution to free energy = -308492.18364013 +- 0.12392259 meV +Free energy = -308374.32598255 +- 0.12392259 meV +FC gradient modulus = 372.90564876 +- 86.90757818 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.37035883 meV/A +Kong-Liu effective sample size = 49.9409735529959 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 13 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.74854581 meV +Anharmonic contribution to free energy = -308492.07814773 +- 0.12199468 meV +Free energy = -308374.32960193 +- 0.12199468 meV +FC gradient modulus = 372.90564876 +- 86.90757818 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.37035883 meV/A +Kong-Liu effective sample size = 49.84283113117479 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 14 +Minimization step, force computed: 50 +Good step found with 0.3375, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.74854581 meV +Anharmonic contribution to free energy = -308492.07814773 +- 0.12199468 meV +Free energy = -308374.32960193 +- 0.12199468 meV +FC gradient modulus = 245.66216705 +- 86.83577615 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36990406 meV/A +Kong-Liu effective sample size = 49.84283113117479 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 15 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.63910565 meV +Anharmonic contribution to free energy = -308491.97199157 +- 0.12094287 meV +Free energy = -308374.33288592 +- 0.12094287 meV +FC gradient modulus = 245.66216705 +- 86.83577615 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36990406 meV/A +Kong-Liu effective sample size = 49.70170289869779 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 16 +Minimization step, force computed: 50 +Good step found with 0.5062500000000001, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.63910565 meV +Anharmonic contribution to free energy = -308491.97199157 +- 0.12094287 meV +Free energy = -308374.33288592 +- 0.12094287 meV +FC gradient modulus = 122.19204085 +- 86.86061801 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36977497 meV/A +Kong-Liu effective sample size = 49.70170289869779 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 17 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55684460 meV +Anharmonic contribution to free energy = -308491.89335796 +- 0.12068592 meV +Free energy = -308374.33651336 +- 0.12068592 meV +FC gradient modulus = 122.19204085 +- 86.86061801 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36977497 meV/A +Kong-Liu effective sample size = 49.56774596722804 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 18 +Minimization step, force computed: 50 +Good step found with 0.7593750000000001, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55684460 meV +Anharmonic contribution to free energy = -308491.89335796 +- 0.12068592 meV +Free energy = -308374.33651336 +- 0.12068592 meV +FC gradient modulus = 34.71806260 +- 86.94538150 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36991785 meV/A +Kong-Liu effective sample size = 49.56774596722804 + + +The gc gradient satisfy the convergence condition. + +The gw gradient satisfy the convergence condition. +The system satisfy the convergence criteria according to the input. +Check the stopping criteria: Running = False +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 18 steps + +Free energy = -308374.33651336 +- 0.12068592 meV +FC gradient modulus = 34.71806260 +- 86.94538150 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.36991785 meV/A +Kong-Liu effective sample size = 49.56774596722804 + +Total force on the centroids [eV/A]: + 0) 0.000000 -0.000000 -0.000000 +- -0.000000 0.000000 -0.000000 + 1) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + -0.07664727 0.00000000 0.00000000 0.01136236 0.00000000 0.00000000 + -0.00000000 -0.07664727 -0.00000000 +- 0.00000000 0.01136236 0.00000000 + -0.00000000 -0.00000000 -0.07664727 0.00000000 0.00000000 0.01136236 + + Ab initio average stress [GPa]: + -0.22722149 -0.00000000 -0.00000000 + -0.00000000 -0.22722149 0.00000000 + -0.00000000 0.00000000 -0.22722149 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds +Average of 0.4221266508102417 s per call +Subroutine report: + Function: GoParallel + N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.42097902297973633 s per call + Subroutine report: + Function: compute + N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.42092299461364746 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.42110109329223633 s per call + + +Function: minimization_step +N = 18 calls took: 0 hours; 0 minutes; 0.62 seconds +Average of 0.034615808063083224 s per call +Subroutine report: + Function: SymmetrizeFCQ + N = 18 calls took: 0 hours; 0 minutes; 0.17 seconds + Average of 0.009491642316182455 s per call + + Function: Symmetrize + N = 18 calls took: 0 hours; 0 minutes; 0.17 seconds + Average of 0.009512212541368272 s per call + + Function: update + N = 18 calls took: 0 hours; 0 minutes; 0.22 seconds + Average of 0.01243762175242106 s per call + Subroutine report: + Function: update_weights_fourier + N = 18 calls took: 0 hours; 0 minutes; 0.22 seconds + Average of 0.012397381994459365 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 18 calls took: 0 hours; 0 minutes; 0.15 seconds + Average of 0.00832959016164144 s per call + Subroutine report: + Function: DyagDinQ + N = 144 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.00020677347977956137 s per call + + Function: Manipulate polarization vectors + N = 144 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.00017636352115207247 s per call + + + Function: Time to get SSCHA energy and forces + N = 18 calls took: 0 hours; 0 minutes; 0.02 seconds + Average of 0.0010606580310397679 s per call + + Function: get upsilon fourier + N = 18 calls took: 0 hours; 0 minutes; 0.01 seconds + Average of 0.0008082522286309137 s per call + + Function: get uYu + N = 18 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.0016922023561265734 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = -0.0766 +- 0.0114 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.3748 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0837433651e+02 eV + Gibbs Free energy = -3.0837433651e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.374805006719775 +[CELL] unit_cell: +Cell([[2.7228694174377295, 2.7228694174377295, -4.060279995005321e-18], [2.7228694174377295, -9.022844433345156e-19, 2.7228694174377295], [-9.022844433345154e-19, 2.7228694174377295, 2.7228694174377295]]) +[CELL] CURRENT STRAIN: +[[ 2.72121961e-03 -2.90375764e-17 2.87053020e-17] + [-2.88714392e-17 2.72121961e-03 2.88714392e-17] + [-2.88714392e-17 2.88714392e-17 2.72121961e-03]] +[CELL] NEW STRESS: +[[-4.78394610e-04 0.00000000e+00 3.88855050e-20] + [-3.88855050e-20 -4.78394610e-04 -3.88855050e-20] + [-1.16656515e-19 -7.77710099e-20 -4.78394610e-04]] +GRAD MAT: +[[ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18] + [ 1.01661256e-18 1.93676497e-02 2.13192140e-18] + [ 4.16514652e-18 3.70618838e-18 1.93676497e-02]] + +[CELL] y0 = 0.12491362486531585 | y1 = -0.011856116393323065 +[CELL] grad = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 + 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 + 1.93676497e-02] +[CELL] lastgrad = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 + -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 + -2.04053608e-01] +[CELL] GRADIENT DOT DIRECTION = 0.9133133083077015 +[CELL] New step: +[CELL] X_OLD = [ 2.72121961e-03 -2.90375764e-17 2.87053020e-17 -2.88714392e-17 + 2.72121961e-03 2.88714392e-17 -2.88714392e-17 2.88714392e-17 + 2.72121961e-03] | ALPHA = 0.012179770366426118 +[CELL] DIRECTION = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 + 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 + 1.93676497e-02] +[CELL] GRADIENT = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 + 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 + 1.93676497e-02] +[CELL] X_NEW = [ 2.48532609e-03 -2.90307452e-17 2.87177232e-17 -2.88838213e-17 + 2.48532609e-03 2.88454728e-17 -2.89221697e-17 2.88262986e-17 + 2.48532609e-03] +[CELL] Step number = 2 + +NEW STRAIN: +[[ 2.48532609e-03 -2.90307452e-17 2.87177232e-17] + [-2.88838213e-17 2.48532609e-03 2.88454728e-17] + [-2.89221697e-17 2.88262986e-17 2.48532609e-03]] +NEW VOLUME: -40.34631678535821 + + Currently estimated bulk modulus = 99.188 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72222885 2.72222885 -0.00000000) + v2 [A] = ( 2.72222885 -0.00000000 2.72222885) + v3 [A] = ( -0.00000000 2.72222885 2.72222885) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. +Force computed shape: 50 +Computing configuration 1 out of 50 (nat = 16) +Computing configuration 2 out of 50 (nat = 16) +Computing configuration 3 out of 50 (nat = 16) +Computing configuration 4 out of 50 (nat = 16) +Computing configuration 5 out of 50 (nat = 16) +Computing configuration 6 out of 50 (nat = 16) +Computing configuration 7 out of 50 (nat = 16) +Computing configuration 8 out of 50 (nat = 16) +Computing configuration 9 out of 50 (nat = 16) +Computing configuration 10 out of 50 (nat = 16) +Computing configuration 11 out of 50 (nat = 16) +Computing configuration 12 out of 50 (nat = 16) +Computing configuration 13 out of 50 (nat = 16) +Computing configuration 14 out of 50 (nat = 16) +Computing configuration 15 out of 50 (nat = 16) +Computing configuration 16 out of 50 (nat = 16) +Computing configuration 17 out of 50 (nat = 16) +Computing configuration 18 out of 50 (nat = 16) +Computing configuration 19 out of 50 (nat = 16) +Computing configuration 20 out of 50 (nat = 16) +Computing configuration 21 out of 50 (nat = 16) +Computing configuration 22 out of 50 (nat = 16) +Computing configuration 23 out of 50 (nat = 16) +Computing configuration 24 out of 50 (nat = 16) +Computing configuration 25 out of 50 (nat = 16) +Computing configuration 26 out of 50 (nat = 16) +Computing configuration 27 out of 50 (nat = 16) +Computing configuration 28 out of 50 (nat = 16) +Computing configuration 29 out of 50 (nat = 16) +Computing configuration 30 out of 50 (nat = 16) +Computing configuration 31 out of 50 (nat = 16) +Computing configuration 32 out of 50 (nat = 16) +Computing configuration 33 out of 50 (nat = 16) +Computing configuration 34 out of 50 (nat = 16) +Computing configuration 35 out of 50 (nat = 16) +Computing configuration 36 out of 50 (nat = 16) +Computing configuration 37 out of 50 (nat = 16) +Computing configuration 38 out of 50 (nat = 16) +Computing configuration 39 out of 50 (nat = 16) +Computing configuration 40 out of 50 (nat = 16) +Computing configuration 41 out of 50 (nat = 16) +Computing configuration 42 out of 50 (nat = 16) +Computing configuration 43 out of 50 (nat = 16) +Computing configuration 44 out of 50 (nat = 16) +Computing configuration 45 out of 50 (nat = 16) +Computing configuration 46 out of 50 (nat = 16) +Computing configuration 47 out of 50 (nat = 16) +Computing configuration 48 out of 50 (nat = 16) +Computing configuration 49 out of 50 (nat = 16) +Computing configuration 50 out of 50 (nat = 16) +Force computed shape: 50 + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 19 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55589434 meV +Anharmonic contribution to free energy = -308491.91576859 +- 0.22448665 meV +Free energy = -308374.35987425 +- 0.22448665 meV +FC gradient modulus = 53.33262212 +- 85.36885845 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39036331 meV/A +Kong-Liu effective sample size = 49.9999692008167 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 20 +Minimization step, force computed: 50 +Good step found with 0.15000000000000002, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55589434 meV +Anharmonic contribution to free energy = -308491.91576859 +- 0.22448665 meV +Free energy = -308374.35987425 +- 0.22448665 meV +FC gradient modulus = 45.76513188 +- 85.37974344 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39041837 meV/A +Kong-Liu effective sample size = 49.9999692008167 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 21 +Minimization step, force computed: 50 + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55469315 meV +Anharmonic contribution to free energy = -308491.91442268 +- 0.22446124 meV +Free energy = -308374.35972953 +- 0.22446124 meV +FC gradient modulus = 45.76513188 +- 85.37974344 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39041837 meV/A +Kong-Liu effective sample size = 49.99983849028925 + + +The gw gradient satisfy the convergence condition. +Check the stopping criteria: Running = True + + # ---------------- NEW MINIMIZATION STEP -------------------- +Step ka = 22 +Minimization step, force computed: 50 +Good step found with 0.22500000000000003, try increment + + +Number of symmetries before the step: 24 +Harmonic contribution to free energy = 117.55469315 meV +Anharmonic contribution to free energy = -308491.91442268 +- 0.22446124 meV +Free energy = -308374.35972953 +- 0.22446124 meV +FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A +Kong-Liu effective sample size = 49.99983849028925 + + +The gc gradient satisfy the convergence condition. + +The gw gradient satisfy the convergence condition. +The system satisfy the convergence criteria according to the input. +Check the stopping criteria: Running = False +ROOT NAME: ./thermal_expansion/minim_t0 +SAVE NAME: ./thermal_expansion/minim_t0 +FNAME NAME: None + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 22 steps + +Free energy = -308374.35972953 +- 0.22446124 meV +FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A +Kong-Liu effective sample size = 49.99983849028925 + +Total force on the centroids [eV/A]: + 0) 0.000000 -0.000000 -0.000000 +- -0.000000 0.000000 -0.000000 + 1) -0.000000 0.000000 0.000000 +- -0.000000 0.000000 -0.000000 + + + ==== STRESS TENSOR [GPa] ==== + -0.00076058 0.00000000 0.00000000 0.00787638 0.00000000 0.00000000 + 0.00000000 -0.00076058 0.00000000 +- 0.00000000 0.00787638 0.00000000 + -0.00000000 0.00000000 -0.00076058 0.00000000 0.00000000 0.00787638 + + Ab initio average stress [GPa]: + -0.14847648 -0.00000000 0.00000000 + -0.00000000 -0.14847648 0.00000000 + 0.00000000 0.00000000 -0.14847648 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 3 calls took: 0 hours; 0 minutes; 0.85 seconds +Average of 0.281984806060791 s per call +Subroutine report: + Function: GoParallel + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.28085025151570636 s per call + Subroutine report: + Function: compute + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.2807942231496175 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.28096747398376465 s per call + + +Function: minimization_step +N = 22 calls took: 0 hours; 0 minutes; 0.76 seconds +Average of 0.034483660351146354 s per call +Subroutine report: + Function: SymmetrizeFCQ + N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds + Average of 0.00945215875452215 s per call + + Function: Symmetrize + N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds + Average of 0.009492018006064674 s per call + + Function: update + N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds + Average of 0.01239886067130349 s per call + Subroutine report: + Function: update_weights_fourier + N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds + Average of 0.01235907728021795 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 22 calls took: 0 hours; 0 minutes; 0.18 seconds + Average of 0.00831416520205411 s per call + Subroutine report: + Function: DyagDinQ + N = 176 calls took: 0 hours; 0 minutes; 0.04 seconds + Average of 0.00020634044300426137 s per call + + Function: Manipulate polarization vectors + N = 176 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.00017645413225347346 s per call + + + Function: Time to get SSCHA energy and forces + N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds + Average of 0.0010743899778886275 s per call + + Function: get upsilon fourier + N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds + Average of 0.000806494192643599 s per call + + Function: get uYu + N = 22 calls took: 0 hours; 0 minutes; 0.04 seconds + Average of 0.0016618641940030184 s per call + + + + + + END OF TIMER REPORT +===================== + + + ====================== + ENTHALPIC CONTRIBUTION + ====================== + + Current pressure P = -0.0008 +- 0.0079 GPa + Target pressure P = 0.0000 GPa + + For enthalpy we use the target pressure. + + P = 0.0000 GPa V = 40.3463 A^3 + + P V = 0.00000000e+00 eV + + Helmoltz Free energy = -3.0837435973e+02 eV + Gibbs Free energy = -3.0837435973e+02 eV <-- + Zero energy = 0.0000000000e+00 eV + + +[CELL] VOLUME: 40.34631678535821 +[CELL] unit_cell: +Cell([[2.722228853286519, 2.722228853286519, -2.6033592320191136e-19], [2.722228853286519, -1.0413436928075911e-19, 2.722228853286519], [-8.500049932564735e-19, 2.722228853286519, 2.722228853286519]]) +[CELL] CURRENT STRAIN: +[[ 2.48532609e-03 -6.36429382e-18 6.05127181e-18] + [-6.20778281e-18 2.48532609e-03 6.20778281e-18] + [-6.20778281e-18 6.20778281e-18 2.48532609e-03]] +[CELL] NEW STRESS: +[[-4.74714456e-06 3.03793008e-22 2.12655105e-21] + [ 6.07586015e-21 -4.74714456e-06 1.51896504e-21] + [-6.68344617e-21 6.37965316e-21 -4.74714456e-06]] +GRAD MAT: +[[ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20] + [-2.46936803e-19 1.92005812e-04 -6.02479815e-20] + [ 2.69133635e-19 -2.56846244e-19 1.92005812e-04]] + +[CELL] y0 = 0.0011253175631047963 | y1 = 1.1156103932368531e-05 +[CELL] grad = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 + 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 + 1.92005812e-04] +[CELL] lastgrad = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 + 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 + 1.93676497e-02] +[CELL] GRADIENT DOT DIRECTION = 1.0100130047045919 +[CELL] New step: +[CELL] X_OLD = [ 2.48532609e-03 -6.36429382e-18 6.05127181e-18 -6.20778281e-18 + 2.48532609e-03 6.20778281e-18 -6.20778281e-18 6.20778281e-18 + 2.48532609e-03] | ALPHA = 0.012301726464405992 +[CELL] DIRECTION = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 + 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 + 1.92005812e-04] +[CELL] GRADIENT = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 + 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 + 1.92005812e-04] +[CELL] X_NEW = [ 2.48296409e-03 -6.36412767e-18 6.05231565e-18 -6.20474507e-18 + 2.48296409e-03 6.20852397e-18 -6.21109362e-18 6.21094247e-18 + 2.48296409e-03] +[CELL] Step number = 3 + +NEW STRAIN: +[[ 2.48296409e-03 -6.36412767e-18 6.05231565e-18] + [-6.20474507e-18 2.48296409e-03 6.20852397e-18] + [-6.21109362e-18 6.21094247e-18 2.48296409e-03]] +NEW VOLUME: -40.34603160044756 + + Currently estimated bulk modulus = 108.679 GPa + (Note: this is just indicative, do not use it for computing bulk modulus) + + + New unit cell: + v1 [A] = ( 2.72222244 2.72222244 -0.00000000) + v2 [A] = ( 2.72222244 0.00000000 2.72222244) + v3 [A] = ( -0.00000000 2.72222244 2.72222244) + +Check the symmetries in the new cell: +Symmetries of the bravais lattice: 48 +Symmetries of the crystal: 24 +Symmetries of the small group of q: 24 +Forcing the symmetries in the dynamical matrix. + + * * * * * * * * + * * + * RESULTS * + * * + * * * * * * * * + + +Minimization ended after 22 steps + +Free energy = -308374.35972953 +- 0.22446124 meV +FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 +Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A +Kong-Liu effective sample size = 49.99983849028925 + +Total force on the centroids [eV/A]: + 0) 0.000000 0.000000 -0.000000 +- -0.000000 0.000000 0.000000 + 1) 0.000000 -0.000000 -0.000000 +- 0.000000 0.000000 0.000000 + + + ==== STRESS TENSOR [GPa] ==== + -0.00076058 0.00000000 0.00000000 0.00787638 0.00000000 0.00000000 + 0.00000000 -0.00076058 0.00000000 +- 0.00000000 0.00787638 0.00000000 + -0.00000000 0.00000000 -0.00076058 0.00000000 0.00000000 0.00787638 + + Ab initio average stress [GPa]: + -0.14847648 -0.00000000 0.00000000 + -0.00000000 -0.14847648 0.00000000 + 0.00000000 0.00000000 -0.14847648 + + + +======================== + TIMER REPORT +======================== + +Threshold for printing: 5 % + +Function: get_fourier_gradient +N = 3 calls took: 0 hours; 0 minutes; 0.85 seconds +Average of 0.281984806060791 s per call +Subroutine report: + Function: GoParallel + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.28085025151570636 s per call + Subroutine report: + Function: compute + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.2807942231496175 s per call + Subroutine report: + + + Function: fourier gradient julia + N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds + Average of 0.28096747398376465 s per call + + +Function: minimization_step +N = 22 calls took: 0 hours; 0 minutes; 0.76 seconds +Average of 0.034483660351146354 s per call +Subroutine report: + Function: SymmetrizeFCQ + N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds + Average of 0.00945215875452215 s per call + + Function: Symmetrize + N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds + Average of 0.009492018006064674 s per call + + Function: update + N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds + Average of 0.01239886067130349 s per call + Subroutine report: + Function: update_weights_fourier + N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds + Average of 0.01235907728021795 s per call + Subroutine report: + Function: DiagonalizeSupercell + N = 22 calls took: 0 hours; 0 minutes; 0.18 seconds + Average of 0.00831416520205411 s per call + Subroutine report: + Function: DyagDinQ + N = 176 calls took: 0 hours; 0 minutes; 0.04 seconds + Average of 0.00020634044300426137 s per call + + Function: Manipulate polarization vectors + N = 176 calls took: 0 hours; 0 minutes; 0.03 seconds + Average of 0.00017645413225347346 s per call + + + Function: Time to get SSCHA energy and forces + N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds + Average of 0.0010743899778886275 s per call + + Function: get upsilon fourier + N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds + Average of 0.000806494192643599 s per call + + Function: get uYu + N = 22 calls took: 0 hours; 0 minutes; 0.04 seconds + Average of 0.0016618641940030184 s per call + + + + + + END OF TIMER REPORT +===================== + diff --git a/Examples/sscha_and_aiida/model.ipynb b/Examples/sscha_and_aiida/model.ipynb new file mode 100644 index 00000000..e0ca4f27 --- /dev/null +++ b/Examples/sscha_and_aiida/model.ipynb @@ -0,0 +1,575 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "from aiida import load_profile\n", + "from aiida.orm import *\n", + "\n", + "from qe_tools import CONSTANTS as C\n", + "\n", + "from ase.io import write, read\n", + "from ase import units\n", + "from ase.calculators.singlepoint import SinglePointCalculator\n", + "\n", + "from flare.atoms import FLARE_Atoms\n", + "from flare.learners.utils import is_std_in_bound, get_env_indices\n", + "from flare.bffs.sgp.calculator import SGP_Calculator\n", + "from flare.bffs.sgp._C_flare import Structure\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "load_profile()\n", + "\n", + "\n", + "plt.rcParams.update({\n", + " 'text.usetex': False,\n", + " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", + " 'pdf.fonttype':42,\n", + " 'font.family':'sans-serif',\n", + " 'font.sans-serif':'Arial',\n", + " 'font.size':14,\n", + " 'mathtext.fontset': 'stixsans',\n", + "})" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "!export OMP_NUM_THREADS=1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluate a model" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of frames in the set: 91\n" + ] + } + ], + "source": [ + "flare_calc, _ = SGP_Calculator.from_file('./model.json')\n", + "\n", + "atoms_test = read(\"./dataset-sscha.xyz\", index=':')\n", + "atoms_flare = [FLARE_Atoms.from_ase_atoms(atoms) for atoms in atoms_test]\n", + "\n", + "for atoms in atoms_flare:\n", + " atoms.calc = flare_calc\n", + "\n", + "print(f\"Number of frames in the set: {len(atoms_test)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", + " -0.01507365])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "atoms_flare[0].get_stress(voigt=False)\n", + "at_fl = atoms_flare[0]\n", + "at_fl.stress" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.01628743, -0.01507365, -0.00761871],\n", + " [-0.01507365, -0.0065395 , 0.01573904],\n", + " [-0.00761871, 0.01573904, -0.00436347]])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "at = atoms_test[0]\n", + "at.calc = flare_calc\n", + "at.get_stress(voigt=False)\n", + "# at" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE energy: 0.3489 eV\n", + "MAE forces: 0.1379 eV ang-1\n", + "MAE stress: 0.0021 eV ang-3\n" + ] + } + ], + "source": [ + "ref_energy = np.array([atoms.get_potential_energy() for atoms in atoms_test])\n", + "ref_forces = np.array([atoms.get_forces() for atoms in atoms_test])\n", + "ref_stress = np.array([atoms.get_stress() for atoms in atoms_test])\n", + "\n", + "model_energy = np.array([atoms.get_potential_energy() for atoms in atoms_flare])\n", + "model_forces = np.array([atoms.get_forces() for atoms in atoms_flare])\n", + "model_stress = np.array([atoms.get_stress() for atoms in atoms_flare])\n", + "\n", + "mae_energy = np.abs(ref_energy-model_energy).mean()\n", + "mae_forces = np.abs(ref_forces-model_forces).mean()\n", + "mae_stress = np.abs(ref_stress-model_stress).mean()\n", + "\n", + "print(f'MAE energy: {mae_energy:.4f} eV')\n", + "print(f'MAE forces: {mae_forces:.4f} eV ang-1')\n", + "print(f'MAE stress: {mae_stress:.4f} eV ang-3')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", + " -0.01507365]),\n", + " array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", + " -0.01507365]))" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "index = 0\n", + "model_stress[index], ref_stress[index]\n", + "# model_forces[index]-ref_forces[index]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot statistics" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans.\n", + "findfont: Generic family 'sans-serif' not found because none of the following families were found: Arial\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(1,2)\n", + "\n", + "# --- Energies\n", + "axs[0].plot(model_energy, ref_energy, 'bo')\n", + "axs[0].plot([ref_energy.min()*1.01, ref_energy.max()*0.99], [ref_energy.min()*1.01, ref_energy.max()*0.99], ls='--', c='gray')\n", + "\n", + "axs[0].set_xlabel('E$_{SGP}}$ (eV)')\n", + "axs[0].set_ylabel('E$_{DFT}$ (eV)')\n", + "\n", + "# --- Forces\n", + "axs[1].plot(model_forces.flatten(), ref_forces.flatten(), 'bo')\n", + "# axs[1].plot([ref_energy.min()*1.01, ref_energy.max()*0.99], [ref_energy.min()*1.01, ref_energy.max()*0.99], ls='--', c='gray')\n", + "\n", + "axs[1].set_xlabel('|F$_{SGP}}$| (eV/Ang)')\n", + "axs[1].set_ylabel('|F$_{DFT}$| (eV/Ang)')\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Relax using model" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initial volume: 40.04698463143717\n", + " Step Time Energy fmax\n", + "BFGS: 0 09:14:25 -308.491702 0.0000\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.optimize import BFGS\n", + "from ase.constraints import ExpCellFilter\n", + "\n", + "vc_relax = False\n", + "filepath = './Si.pwi'\n", + "\n", + "atoms = read(filepath)\n", + "atoms.calc = flare_calc\n", + "print(\"Initial volume: \", atoms.get_volume())\n", + "\n", + "if vc_relax:\n", + " ecf = ExpCellFilter(atoms, scalar_pressure=0.1) # 0.05 -> 8 GPa\n", + " optimizer = BFGS(ecf)\n", + "else:\n", + " optimizer = BFGS(atoms=atoms)\n", + "\n", + "optimizer.run(fmax=0.001)\n", + "\n", + "# print(\"Final cell\")\n", + "# print(optimizer.atoms.atoms.cell)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## EOS" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Minimum at: 40.04698463143717\n" + ] + } + ], + "source": [ + "scale_factors = np.arange(0.8,1.325,0.025)\n", + "atoms = read(filepath)\n", + "\n", + "energies = []\n", + "volumes = []\n", + "for scale_factor in scale_factors:\n", + " scaled_atoms = atoms.copy()\n", + " scaled_atoms.calc = flare_calc\n", + " scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True)\n", + " energies.append(scaled_atoms.get_potential_energy())\n", + " volumes.append(scaled_atoms.get_volume())\n", + "\n", + "print(\"Minimum at: \", volumes[energies.index(min(energies))])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "np.savetxt('./e-v.dat', np.array([volumes, energies]).T)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1,1)\n", + "\n", + "# --- Energies\n", + "ax.plot(volumes, energies, 'bo')\n", + "\n", + "ax.set_xlabel('V (Ang^3)')\n", + "ax.set_ylabel('E (eV)')\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Phonons using Phonopy and FLARE" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def run_phonons(atoms, filename: str = None):\n", + " \"\"\"Run phonons using Phonopy.\"\"\"\n", + " from ase.atoms import Atoms\n", + " from phonopy import Phonopy\n", + " from phonopy.structure.atoms import PhonopyAtoms\n", + "\n", + " # ================================= INPUTS ======================================= #\n", + " supercell_size = 4\n", + " distance = 0.01 # in Angstrom\n", + " t_max = 300 # Kelvin\n", + " symmetrize = False\n", + " conventional = True\n", + " primitive_matrix = None\n", + " thermal_properties = True\n", + " # primitive_matrix = 'auto'\n", + " # ================================================================================ #\n", + "\n", + " supercell_matrix = [supercell_size]*3\n", + " if conventional:\n", + " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", + "\n", + " unitcell = PhonopyAtoms(\n", + " symbols=atoms.get_chemical_symbols(),\n", + " numbers=atoms.get_atomic_numbers(),\n", + " scaled_positions=atoms.get_scaled_positions(),\n", + " cell=atoms.get_cell(),\n", + " )\n", + "\n", + " ph = Phonopy(\n", + " unitcell=unitcell,\n", + " primitive_matrix=primitive_matrix,\n", + " supercell_matrix=supercell_matrix,\n", + " )\n", + "\n", + " ph.generate_displacements(distance=distance)\n", + " supercells = ph.get_supercells_with_displacements()\n", + "\n", + " sets_of_forces = []\n", + " for supercell in supercells:\n", + " cell, scaled_positions, numbers = supercell.totuple()\n", + " supercell_atoms = Atoms(\n", + " cell=cell,\n", + " scaled_positions=scaled_positions,\n", + " numbers=numbers,\n", + " calculator=flare_calc\n", + " )\n", + " sets_of_forces.append(supercell_atoms.get_forces())\n", + "\n", + " ph.set_forces(sets_of_forces=sets_of_forces)\n", + " ph.produce_force_constants()\n", + "\n", + " if symmetrize:\n", + " ph.symmetrize_force_constants()\n", + " ph.symmetrize_force_constants_by_space_group()\n", + " \n", + " if thermal_properties:\n", + " ph.run_mesh(mesh=300)\n", + " ph.run_thermal_properties()#t_max=t_max)\n", + " ph.thermal_properties.write_yaml(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "start_index = -energies.index(min(energies))\n", + "for scale_factor in scale_factors:\n", + " scaled_atoms = atoms.copy()\n", + " scaled_atoms.calc = flare_calc\n", + " scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True)\n", + " run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}')\n", + " start_index += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def run_phonons(atoms, filename: str = None):\n", + " \"\"\"Run phonons using Phonopy.\"\"\"\n", + " from ase.atoms import Atoms\n", + " from phonopy import Phonopy\n", + " from phonopy.structure.atoms import PhonopyAtoms\n", + "\n", + " # ================================= INPUTS ======================================= #\n", + " supercell_size = 4\n", + " distance = 0.01 # in Angstrom\n", + " symmetrize = False\n", + " conventional = True\n", + " primitive_matrix = None\n", + " # primitive_matrix = 'auto'\n", + " # ================================================================================ #\n", + "\n", + " supercell_matrix = [supercell_size]*3\n", + " if conventional:\n", + " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", + "\n", + " unitcell = PhonopyAtoms(\n", + " symbols=atoms.get_chemical_symbols(),\n", + " numbers=atoms.get_atomic_numbers(),\n", + " scaled_positions=atoms.get_scaled_positions(),\n", + " cell=atoms.get_cell(),\n", + " )\n", + "\n", + " ph = Phonopy(\n", + " unitcell=unitcell,\n", + " primitive_matrix=primitive_matrix,\n", + " supercell_matrix=supercell_matrix,\n", + " )\n", + "\n", + " ph.generate_displacements(distance=distance)\n", + " supercells = ph.get_supercells_with_displacements()\n", + "\n", + " sets_of_forces = []\n", + " for supercell in supercells:\n", + " cell, scaled_positions, numbers = supercell.totuple()\n", + " supercell_atoms = Atoms(\n", + " cell=cell,\n", + " scaled_positions=scaled_positions,\n", + " numbers=numbers,\n", + " calculator=flare_calc\n", + " )\n", + " sets_of_forces.append(supercell_atoms.get_forces())\n", + "\n", + " ph.set_forces(sets_of_forces=sets_of_forces)\n", + " ph.produce_force_constants()\n", + " return ph\n", + "\n", + "scaled_atoms = atoms.copy()\n", + "ph = run_phonons(atoms)\n", + "ph.auto_band_structure(plot=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.8.18 ('base')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.18" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "d4d1e4263499bec80672ea0156c357c1ee493ec2b1c70f0acce89fc37c4a6abe" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Examples/sscha_and_aiida/model.json b/Examples/sscha_and_aiida/model.json new file mode 100644 index 00000000..b69f825d --- /dev/null +++ b/Examples/sscha_and_aiida/model.json @@ -0,0 +1 @@ +{"results": {"energy": -2415.076078083993, "forces": [[-1.2391447946429253, 1.8763116548070684, 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a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py index 9b77a27d..19b1bc75 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py @@ -23,7 +23,9 @@ def main(): """Run with AiiDA-QuantumESPRESSO + FLARE some ensemble configuration for testing.""" # =========== GENERAL INPUTS =============== # np.random.seed(0) - number_of_configurations = 2 + number_of_configurations = 10 + batch_number = 3 + check_time = 3 temperature = 0.0 # =========== AiiDA ENSEMBLE =============== # @@ -59,13 +61,21 @@ def main(): 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate aiida-sscha\nexport OMP_NUM_THREADS=1', }, electronic_type=ElectronicType.INSULATOR, + batch_number=batch_number, + check_time=check_time, ) # =========== GENERATE & COMPUTE =============== # ensemble.generate(number_of_configurations) ensemble.compute_ensemble(**aiida_inputs) # this should include the training too + print() + print() + print("=============================================") print("First population has run.") + print("=============================================") + print() + print() ensemble.generate(number_of_configurations) # here hopefully the model is called ensemble.compute_ensemble(**aiida_inputs) diff --git a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py index 07bcbd63..c3a34341 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py @@ -1,10 +1,11 @@ """Test for an actual AiiDA-FLARE-powered ensemble computation.""" import numpy as np +from ase.io import read from ase.build import bulk, make_supercell from ase.calculators.lj import LennardJones -from cellconstructor.Phonons import compute_phonons_finite_displacements +from cellconstructor.Phonons import Phonons, compute_phonons_finite_displacements from cellconstructor.Structure import Structure from sscha.aiida_ensemble import AiiDAEnsemble from sscha.SchaMinimizer import SSCHA_Minimizer @@ -19,30 +20,44 @@ load_profile() -# PID: 1230420, 1292679 def main(): - """Run with AiiDA-QuantumESPRESSO + FLARE + SSCHA @ NVT.""" + """Run with AiiDA-QuantumESPRESSO + FLARE + SSCHA @ NPT.""" # =========== GENERAL INPUTS =============== # np.random.seed(0) - number_of_configurations = 4 - max_iterations = 20 - temperature = 0.0 - - # =========== AiiDA ENSEMBLE =============== # - atoms = bulk('Si') - matrix = [[-1,1,1],[1,-1,1],[1,1,-1]] # ==> 8 atoms cell | i.e. conventional cell - atoms = make_supercell(atoms, matrix) + number_of_configurations = 50 + batch_number = 1 + check_time = 3 + max_iterations = 3 + temperature = 0 + pressure = 0 + meaningful_factor = 0.5 + kong_liu_ratio = 0.5 + minimization_step = 0.1 + supercell = [2,2,2] + + atoms = read('./Si.pwi') # bulk('Si') structure = Structure() structure.generate_from_ase_atoms(atoms) - dyn = compute_phonons_finite_displacements(structure, LennardJones(), supercell=[1,1,1]) + # =========== FLARE MODEL =============== # + flare_calc, _ = SGP_Calculator.from_file('./model.json') + # flare_calc = SGP_Calculator(get_empty_sgp(n_types=1, the_map={14: 0}, the_atom_energies={0: -154.272015018195})) + + # =========== DYNAMICAL MATRIX =============== # + dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) dyn.Symmetrize() dyn.ForcePositiveDefinite() - + + # =========== AIIDA ENSEMBLE =============== # ensemble = AiiDAEnsemble(dyn, temperature) - flare_calc = SGP_Calculator(get_empty_sgp(n_types=1, the_map={14: 0}, the_atom_energies={0: 0})) - ensemble.set_otf(flare_calc, std_tolerance_factor=-0.001, max_atoms_added=-1) + ensemble.set_otf( + flare_calc, + std_tolerance_factor=-0.9, + max_atoms_added=-1, + update_threshold=0.5, + update_style="threshold", + ) # =========== AiiDA INPUTS =============== # pw_code_label = 'pw@localhost' @@ -50,19 +65,24 @@ def main(): pw_code=pw_code_label, protocol='fast', overrides={ + 'clean_workdir': True, 'meta_parameters':{'conv_thr_per_atom': 1e-8}, - 'kpoints_distance': 0.8, + 'kpoints_distance': 0.4, }, options={ - 'resources':{'num_machines': 1, 'num_mpiprocs_per_machine': 1,}, - 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate aiida-sscha\nexport OMP_NUM_THREADS=1', + 'resources':{'num_machines': 1, 'num_mpiprocs_per_machine': 4,}, + 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate base\nexport OMP_NUM_THREADS=1', }, electronic_type=ElectronicType.METAL, + batch_number=batch_number, + check_time=check_time, ) # =========== SSCHA SETTINGS & COMPUTE =============== # minim = SSCHA_Minimizer(ensemble) - minim.set_minimization_step(0.1) + minim.set_minimization_step(minimization_step) + minim.kong_liu_ratio = kong_liu_ratio # default 0.5 + minim.meaningful_factor = meaningful_factor relax = SSCHA( minimizer=minim, @@ -73,14 +93,14 @@ def main(): ) ioinfo = IOInfo() - ioinfo.SetupSaving('./minim_t0') - relax.setup_custom_functions( custom_function_post = ioinfo.CFP_SaveAll) - - # Run the NVT simulation + ioinfo.SetupSaving(f'./minim_t{temperature}') + relax.setup_custom_functions( custom_function_post = ioinfo.CFP_SaveAll ) + + # Run the NPT simulation relax.vc_relax( - target_press = 0.0, + target_press = pressure, restart_from_ens = False, - ensemble_loc = './ensembles_P0_T0', + ensemble_loc = f'./ensembles_P{pressure}_T{temperature}', ) # Print in standard output diff --git a/Examples/sscha_and_aiida/run_aiida_sscha.py b/Examples/sscha_and_aiida/run_aiida_sscha.py index 646e61d6..363bbad2 100644 --- a/Examples/sscha_and_aiida/run_aiida_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_sscha.py @@ -1,4 +1,10 @@ -"""Example of an actual AiiDA-powered SSCHA run.""" +start_index = -energies.index(min(energies)) +for scale_factor in scale_factors: + scaled_atoms = atoms.copy() + scaled_atoms.calc = flare_calc + scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True) + run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}') + start_index += 1"""Example of an actual AiiDA-powered SSCHA run.""" import os import numpy as np diff --git a/Examples/sscha_and_aiida/run_flare_sscha.py b/Examples/sscha_and_aiida/run_flare_sscha.py new file mode 100644 index 00000000..b1507b2f --- /dev/null +++ b/Examples/sscha_and_aiida/run_flare_sscha.py @@ -0,0 +1,105 @@ +"""Test for an actual FLARE-powered ensemble computation.""" +import os +import numpy as np +from ase.io import read + +from cellconstructor.Phonons import Phonons, compute_phonons_finite_displacements +from cellconstructor.Structure import Structure +from sscha.Ensemble import Ensemble +from sscha.SchaMinimizer import SSCHA_Minimizer +from sscha.Relax import SSCHA +from sscha.Utilities import IOInfo + +from flare.bffs.sgp.calculator import SGP_Calculator + + +def main(): + """Run with FLARE + SSCHA @ NPT.""" + # =========== GENERAL INPUTS =============== # + np.random.seed(0) + number_of_configurations = 50 + max_iterations = 3 + temperature_i = 0 + temperature_f = 0 + temperature_step = 10 + pressure = 0 + meaningful_factor = 0.5 + kong_liu_ratio = 0.5 + minimization_step = 0.1 + supercell = [2,2,2] + restart_from_previous_dyn = False + restart_from_ens = False + + atoms = read('./Si.pwi') + structure = Structure() + structure.generate_from_ase_atoms(atoms) + + # =========== FLARE MODEL =============== # + flare_calc, _ = SGP_Calculator.from_file('./model.json') + + # =========== DYNAMICAL MATRIX =============== # + dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) + dyn.Symmetrize() + dyn.ForcePositiveDefinite() + + if not os.path.exists("./thermal_expansion"): + os.makedirs("./thermal_expansion") + + # We cycle over several temperatures + temperature = temperature_i + volumes = [] + temperatures = [] + + while temperature <= temperature_f: + ensemble = Ensemble(dyn, temperature) + + minim = SSCHA_Minimizer(ensemble) + minim.set_minimization_step(minimization_step) + minim.kong_liu_ratio = kong_liu_ratio # default 0.5 + minim.meaningful_factor = meaningful_factor + + relax = SSCHA( + minimizer=minim, + ase_calculator=flare_calc, + N_configs=number_of_configurations, + max_pop=max_iterations, + save_ensemble=True, + ) + + ioinfo = IOInfo() + ioinfo.SetupSaving(f'./thermal_expansion/minim_t{temperature}') + relax.setup_custom_functions( custom_function_post = ioinfo.CFP_SaveAll) + + # Run the NVT simulation + relax.vc_relax( + target_press = pressure, + restart_from_ens = restart_from_ens, + ensemble_loc = f'./ensembles_P{pressure}_T{temperature}_flare', + ) + + # Print in standard output + relax.minim.finalize() + + # Save the volume and temperature + volumes.append(relax.minim.dyn.structure.get_volume()) + temperatures.append(temperature) + relax.minim.dyn.save_qe(f"./thermal_expansion/sscha_T{temperature}_dyn") + + # Start the next simulation from the converged value at this temperature + if restart_from_previous_dyn: + dyn = relax.minim.dyn + + # Increase temperature + temperature += temperature_step + + # Save thermal expension + np.savetxt( + "./thermal_expansion/thermal_expansion.dat", + np.transpose([temperatures, volumes]), + header = "Temperature [K]; Volume [A^3]", + ) + + +if __name__ == '__main__': + main() + diff --git a/Examples/sscha_and_aiida/submit.sh b/Examples/sscha_and_aiida/submit.sh new file mode 100755 index 00000000..e0e6c32d --- /dev/null +++ b/Examples/sscha_and_aiida/submit.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +eval "$(conda shell.bash hook)" +conda activate base +export OMP_NUM_THREADS=1 + +python run_aiida_flare_sscha.py > log2 + +python run_flare_sscha.py > log3 diff --git a/Examples/sscha_and_aiida/write_xyz.ipynb b/Examples/sscha_and_aiida/write_xyz.ipynb new file mode 100644 index 00000000..495bd69e --- /dev/null +++ b/Examples/sscha_and_aiida/write_xyz.ipynb @@ -0,0 +1,377 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "from datetime import datetime\n", + "\n", + "from aiida import load_profile\n", + "from aiida.orm import *\n", + "\n", + "from qe_tools import CONSTANTS as C\n", + "\n", + "from ase.io import write\n", + "from ase import units\n", + "from ase.calculators.singlepoint import SinglePointCalculator\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "91" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# group_label = 'CsPbI3/SSCHA/250K'\n", + "\n", + "qb = QueryBuilder()\n", + "# qb.append(Group, filters={'label': group_label}, tag='g')\n", + "# qb.append(WorkChainNode, filters={'attributes.exit_status': 0}, with_group='g', tag='wc')\n", + "qb.append(\n", + " WorkChainNode,\n", + " filters={\n", + " 'attributes.exit_status': 0,\n", + " 'attributes.process_label':'PwBaseWorkChain',\n", + " 'ctime': {'>=': datetime(2024, 4, 4)}, \n", + " },\n", + " tag='wc',\n", + ")\n", + "qb.append(\n", + " TrajectoryData,\n", + " # filters=(Node.fields.attributes.symbols == ['Si']),\n", + " filters={\n", + " 'attributes.symbols': {'contains': ['Si'], 'shorter': 17, 'longer': 15},\n", + " },\n", + " with_incoming='wc',\n", + ")\n", + "\n", + "qb.count()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "results = qb.all(flat=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'symbols': ['Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si',\n", + " 'Si'],\n", + " 'array|cells': [1, 3, 3],\n", + " 'array|steps': [1],\n", + " 'array|energy': [1],\n", + " 'array|forces': [1, 16, 3],\n", + " 'array|stress': [1, 3, 3],\n", + " 'array|energy_xc': [1],\n", + " 'array|positions': [1, 16, 3],\n", + " 'array|total_force': [1],\n", + " 'array|energy_ewald': [1],\n", + " 'array|fermi_energy': [1],\n", + " 'array|scf_accuracy': [9],\n", + " 'array|energy_hartree': [1],\n", + " 'array|scf_iterations': [1],\n", + " 'array|energy_accuracy': [1],\n", + " 'array|energy_smearing': [1],\n", + " 'array|energy_threshold': [1],\n", + " 'array|atomic_species_name': [16],\n", + " 'array|energy_one_electron': [1]}" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results[0].base.attributes.all" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(13.6056917253, 13.605693012183622)" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "C.ry_to_ev, units.Ry" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "stress_units = (-1 * units.Ry / units.Bohr**3)/(C.ry_si / C.bohr_si**3 / 10**9) # convention as in ASE (sign and eV/Ang^3)\n", + "\n", + "filename = './dataset-sscha.xyz'\n", + "\n", + "for res in results:\n", + " index = 0\n", + " atoms = res.get_step_structure(index).get_ase()\n", + " energy = res.get_array('energy')[index]\n", + " s = res.get_array('stress')[index]\n", + "\n", + " calc = SinglePointCalculator(atoms)\n", + "\n", + " calc.results = {\n", + " 'energy': energy,\n", + " 'free_energy': energy,\n", + " 'forces': res.get_array('forces')[index],\n", + " 'stress': stress_units*np.array([s[0,0],s[1,1],s[2,2],s[1,2],s[0,2],s[0,1]]),\n", + " }\n", + "\n", + " atoms.calc = calc\n", + "\n", + " write(filename, atoms, format='extxyz', append=True)\n", + " # break" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0.03541242, -0.01678025, -0.01865329],\n", + " [-0.01678025, 0.04417991, -0.01289093],\n", + " [-0.01865329, -0.01289093, 0.04192492]])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "s*stress_units" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "25.711031209285363" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from qe_tools import CONSTANTS as C\n", + "\n", + "C.ry_to_ev / C.bohr_to_ang" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-3.1342698352273604" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "-0.12190370*25.711031209285363" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 5.33819603e-01, -3.13426977e+00, 2.21529350e+00],\n", + " [-3.61151040e-01, 1.14138113e-01, 3.71801765e-02],\n", + " [-1.29917331e-01, -4.65262292e-02, 4.80323948e-04],\n", + " [ 6.49981407e-03, -5.67746845e-02, -5.44976344e-01],\n", + " [ 1.43491153e+00, -1.29718723e-02, -1.85130988e+00],\n", + " [ 6.30538141e+00, -2.56791248e+00, 7.08259788e+00],\n", + " [-5.78140040e-01, -2.29837349e-01, 4.43329029e-01],\n", + " [ 9.42794295e-01, -7.23102748e-02, 6.58932930e-02],\n", + " [ 1.03831906e-01, 5.36502991e-03, 1.89444206e-01],\n", + " [-6.22099867e+00, 2.91243849e+00, -7.01624532e+00],\n", + " [-1.35660162e+00, 2.46259856e+00, -9.54574037e-01],\n", + " [-1.32330763e-01, -8.08972545e-01, 7.27709766e-01],\n", + " [-6.03900509e-01, 3.05007627e+00, -2.38370475e+00],\n", + " [-1.99602495e-02, -5.40431055e-01, 9.21258153e-01],\n", + " [ 2.50064946e-01, 1.22705865e+00, -6.68718486e-01],\n", + " [-1.21055158e-01, 1.98872765e-01, -2.05141292e-01],\n", + " [-2.16071821e-02, -5.25956510e-04, -4.30194424e-01],\n", + " [-4.96366623e-01, -1.41303086e+00, 1.36288121e+00],\n", + " [ 5.04037476e-02, -1.06347767e-02, -5.79919891e-01],\n", + " [-2.44324855e-01, -2.32362169e-01, -1.03545247e-01],\n", + " [-1.08313545e+00, 9.28877717e-02, 1.51277910e+00],\n", + " [ 3.77004310e-01, 1.64521753e-01, 5.79563044e-01],\n", + " [-5.42713435e-01, 4.34002260e+00, 4.57724386e+00],\n", + " [-1.06650109e+00, 1.03115538e+00, -4.24849967e-01],\n", + " [-1.33975681e-01, -2.21176253e-01, 1.49455267e-02],\n", + " [ 1.03219990e-01, -8.91747205e-01, -1.18437023e+00],\n", + " [-4.17225200e-01, -1.63965976e-01, -2.14932401e-01],\n", + " [ 5.24900139e-01, 6.22992631e-02, 4.32876397e-01],\n", + " [-3.28301406e-01, -4.86468190e-02, -6.19020834e-01],\n", + " [-1.68918635e-01, -8.84100159e-03, -2.45400952e-01],\n", + " [ 2.99326150e-01, -1.12787613e+00, 1.56397993e-01],\n", + " [ 9.76087915e-02, -4.19825629e-01, -2.77368926e-01],\n", + " [ 9.28913145e-02, 1.35357295e+00, 1.34226993e+00],\n", + " [ 1.67503151e+00, -9.36859867e-01, -6.95805171e-01],\n", + " [ 3.88135986e-02, 2.37871501e-01, 6.43236830e-02],\n", + " [ 5.71888574e-01, -4.27585144e+00, -4.12269386e+00],\n", + " [ 8.25157363e-01, 8.85218162e-03, 3.82151920e-01],\n", + " [ 3.74536853e-01, -2.17994808e-01, 2.21086801e-02],\n", + " [-1.54682178e-01, 1.29444662e-01, 2.53030092e-01],\n", + " [-4.26278737e-01, 4.81692086e-02, 1.39014255e-01]])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "res.get_array('forces')[index]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bastonero/.conda/envs/aiida/lib/python3.9/site-packages/aiida/storage/psql_dos/backend.py:270: SAWarning: Object of type not in session, add operation along 'DbUser.dbnodes' will not proceed\n", + " with session.begin_nested() as savepoint:\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "res.creator" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.8.12 ('aiida')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.18" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "ad8f63c217015a5132ad55bc66b40838ad2ef6ce473dcbccdf600c93ceb49af4" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Modules/Ensemble.py b/Modules/Ensemble.py index 952fd0bc..bfd935ad 100644 --- a/Modules/Ensemble.py +++ b/Modules/Ensemble.py @@ -4215,6 +4215,7 @@ def get_energy_forces(self, ase_calculator, compute_stress = True, stress_numeri timer.execute_timed_function(self.init) else: self.init() + def w_to_a(self,w, T): n = len(w) a = np.zeros(n) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index d528ab52..976fe228 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -41,6 +41,7 @@ def compute_ensemble( # pylint: disable=arguments-renamed group_label: str | None = None, waiting_time: int | float = 2.5, batch_number: int = 1, + check_time: int = 60, **kwargs ) -> None: """Compute ensemble properties. @@ -57,6 +58,7 @@ def compute_ensemble( # pylint: disable=arguments-renamed For example: 2 would submit two batches, computing the first one, then the second. This is particularly useful when performing on-the-fly simulations, so that the ML potential can be trained on previous batches and (hopefully) predict on the following batches. + check_time: Seconds to wait before checking the status of the submitted workchains kwargs: The kwargs for the get_builder_from_protocol """ @@ -82,14 +84,16 @@ def compute_ensemble( # pylint: disable=arguments-renamed pass structures = copy(self.structures) + dft_counts = 0 dft_indices_batches = split_array(list(range(len(structures))), batch_number) # store here the indices to run with DFT/AiiDA if batch_number > 1: print(f"Submission in batches is active. Number of batches that will be submitted: {batch_number}") for batch_n, dft_indices in enumerate(dft_indices_batches): + dft_indices = dft_indices.tolist() if batch_number > 1: - print(f"Batch submitted: {batch_n}/{batch_number}") + print(f"Batch submitted: {batch_n+1}/{batch_number}") # ================ FLARE SECTION ================= # # If a model is specified and it's not empty, try to predict. @@ -105,68 +109,72 @@ def compute_ensemble( # pylint: disable=arguments-renamed if len(self.gp_model.training_data) > 0: self._predict_with_model(structures, dft_indices) + + dft_counts += len(dft_indices) # ================= AIIDA SECTION ================ # - workchains = submit_and_get_workchains( - structures=[structures[i] for i in dft_indices], - pw_code=pw_code, - temperature=self.current_T, - dft_indices=dft_indices, - protocol=protocol, - options=options, - overrides=overrides, - waiting_time=waiting_time, - **kwargs - ) - - if group: - group.add_nodes(workchains) - - workchains_copy = copy(workchains) - while workchains_copy: - workchains_copy = get_running_workchains(workchains_copy, self.force_computed) - if workchains_copy: - time.sleep(60) # wait before checking again - - for i, is_computed in enumerate(self.force_computed): - if is_computed and i in dft_indices: - dft_stress = None - wc = workchains[dft_indices.index(i)] + if len(dft_indices) > 0: + workchains = submit_and_get_workchains( + structures=[structures[i] for i in dft_indices], + pw_code=pw_code, + temperature=self.current_T, + dft_indices=dft_indices, + protocol=protocol, + options=options, + overrides=overrides, + waiting_time=waiting_time, + **kwargs + ) + + if group: + group.add_nodes(workchains) + + workchains_copy = copy(workchains) + while workchains_copy: + workchains_copy = get_running_workchains(workchains_copy, self.force_computed) + if workchains_copy: + time.sleep(check_time) # wait before checking again + + # ================ UPDATE SECTION ================ # + for i, is_computed in enumerate(self.force_computed): + if is_computed and i in dft_indices: + dft_stress = None + wc = workchains[dft_indices.index(i)] - dft_energy = wc.outputs.output_parameters.dict.energy - dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] + dft_energy = wc.outputs.output_parameters.dict.energy + dft_forces = wc.outputs.output_trajectory.get_array('forces')[-1] - self.energies[i] = dft_energy / CONSTANTS.ry_to_ev - self.forces[i] = dft_forces / CONSTANTS.ry_to_ev + self.energies[i] = dft_energy / CONSTANTS.ry_to_ev # eV -> Ry + self.forces[i] = dft_forces / CONSTANTS.ry_to_ev # eV/Ang -> Ry/Ang - if self.has_stress: - stress = wc.outputs.output_trajectory.get_array('stress')[-1] + if self.has_stress: + stress = wc.outputs.output_trajectory.get_array('stress')[-1] - self.stresses[i] = stress * gpa_to_rybohr3 + self.stresses[i, :, :] = stress * gpa_to_rybohr3 # GPa -> Ry/(Bohr^3) - dft_stress = ase_stress_units * np.array([ - stress[0, 0], stress[1, 1], stress[2, 2], - stress[1, 2], stress[0, 2], stress[0, 1], - ]) + dft_stress = ase_stress_units * np.array([ + stress[0, 0], stress[1, 1], stress[2, 2], + stress[1, 2], stress[0, 2], stress[0, 1], + ]) # GPa -> -eV/(Ang^3) - if self.gp_model is not None: - self._update_gp( - FLARE_Atoms.from_ase_atoms(wc.inputs.pw.structure.get_ase()), - dft_frcs=dft_forces, - dft_energy=dft_energy, - dft_stress=dft_stress, - ) + if self.gp_model is not None: + self._update_gp( + FLARE_Atoms.from_ase_atoms(wc.inputs.pw.structure.get_ase()), + dft_frcs=dft_forces, + dft_energy=dft_energy, + dft_stress=dft_stress, + ) - # ================ TRAIN SECTION ================ # - if self.gp_model is not None: - self._train_gp() - self._write_model() + # ================ TRAIN SECTION ================ # + if self.gp_model is not None: + self._train_gp() + self._write_model() # ================ FINALIZE ================ # - if self.has_stress: - self.stress_computed = copy(self.force_computed) + # if self.has_stress: + # self.stress_computed = copy(self.force_computed) - self._clean_runs(dft_indices) + self._clean_runs(dft_counts) def _predict_with_model( self, @@ -180,11 +188,11 @@ def _predict_with_model( Args: ---- structures: list of :class:`~cellconstructor.Structure.Structure` to simulate - sub_indices: list of integers related to the structures batch dft_indices: list of integers related to the structures """ - sub_indices = copy(dft_indices) + sub_indices = deepcopy(dft_indices) + for index in sub_indices: structure = structures[index] atoms = FLARE_Atoms.from_ase_atoms(structure.get_ase_atoms()) @@ -215,12 +223,11 @@ def _predict_with_model( print(f"[BFFS USED] For structure with id={index}") dft_indices.remove(index) # remove index computed via ML-FF - self.energies[index] = atoms.potential_energy / units.Ry - self.forces[index] = deepcopy(atoms.forces) / units.Ry + self.energies[index] = deepcopy(atoms.get_potential_energy()) / units.Ry # eV -> Ry + self.forces[index] = deepcopy(atoms.get_forces()) / units.Ry # eV/Ang -> Ry/Ang if self.has_stress: - self.stresses[index] = -1 * deepcopy( - atoms.get_stress(voigt=False) - ) * units.Bohr**3 / units.Ry + self.stresses[index, :, :] = -1 * deepcopy(atoms.get_stress(voigt=False)) * (units.Bohr**3 / units.Ry) # -eV/(Ang^3) -> Ry/(Bohr^3) + self.stress_computed[index] = True self.force_computed[index] = True @@ -261,7 +268,7 @@ def _update_gp( local environments will be added to the training set. dft_frcs (np.ndarray): DFT forces on all atoms in the structure, in eV/Angstrom. dft_energy (float): total energy of the entire structure, in eV. - dft_stress (np.ndarray): DFT forces on all atoms in the structure. + dft_stress (np.ndarray): DFT stress on structure. Sign as in ASE (-1 in respect with QE), units in eV/Angstrom^3, and in Voigt notation, i.e. (xx, yy, zz, yz, xz, xy). @@ -270,7 +277,11 @@ def _update_gp( tic = time.time() is_empty_model = len(self.gp_model.training_data) == 0 - + + # Here we make the decision to skip adding environments, if the stds + # are within the user-defined boundaries, even if the ab-initio calculation + # was performed. This avoids slowing down the model, while the SSCHA + # is feeded with the DFT results. if is_empty_model: std_in_bound = False train_atoms = self.init_atoms @@ -296,9 +307,6 @@ def _update_gp( self.output.write_wall_time(tic, task='Env Selection') - # Here we make the decision to skip adding environments even if the - # DFT calculation was performed. This avoids slowing down the model, - # while the SSCHA is feeded with the DFT results. if not std_in_bound: if not is_empty_model: stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) @@ -360,12 +368,12 @@ def _train_gp(self) -> None: hyps_mask=self.gp_model.hyps_mask, ) - def _clean_runs(self, dft_indices: list[int]) -> None: + def _clean_runs(self, dft_counts: int) -> None: """Clean the failed runs and print summary. Args: ---- - dft_indices (list[int]): list of performed dft indices calculations. + dft_counts (int): number of performed DFT calculations. """ n_calcs = np.sum(self.force_computed.astype(int)) @@ -373,7 +381,7 @@ def _clean_runs(self, dft_indices: list[int]) -> None: print('Total structures included: ', n_calcs) print('Structures not included : ', self.N-n_calcs) if self.gp_model is not None: - print('Steps using OTF-ML model : ', self.N-len(dft_indices)) + print('Steps using OTF-ML model : ', self.N-dft_counts) print() print('===================== END OF SUMMARY ===================== \n') if n_calcs != self.N: diff --git a/tests/aiida_ensemble/get_sgp.py b/tests/aiida_ensemble/get_sgp.py index ed71c8cc..7e23eb5e 100644 --- a/tests/aiida_ensemble/get_sgp.py +++ b/tests/aiida_ensemble/get_sgp.py @@ -158,7 +158,7 @@ def get_updated_sgp(n_types=2, power=2, multiple_cutoff=False, kernel_type="Norm mode="specific", ) - print("sparse_indices", sgp.sparse_gp.sparse_indices) + # print("sparse_indices", sgp.sparse_gp.sparse_indices) return sgp diff --git a/tests/aiida_ensemble/test_aiida_ensemble.py b/tests/aiida_ensemble/test_aiida_ensemble.py index f0d21926..f1d8f274 100644 --- a/tests/aiida_ensemble/test_aiida_ensemble.py +++ b/tests/aiida_ensemble/test_aiida_ensemble.py @@ -26,40 +26,7 @@ def test_clean_runs(): ensemble.stresses = np.ones((num_configs, 3, 3)) # (configs, 3, 3) ensemble.force_computed = np.array([True, False, True, True], dtype=bool) ensemble.stress_computed = np.copy(ensemble.force_computed) - ensemble._clean_runs() - - assert all(ensemble.force_computed) - assert len(ensemble.force_computed) == 3 - assert len(ensemble.stress_computed) == 3 - assert np.all(np.isclose(ensemble.forces, np.ones((num_configs-1, num_atoms, 3)))) - -import numpy as np - -from sscha.aiida_ensemble import AiiDAEnsemble - - -def get_ensemble() -> AiiDAEnsemble: - """Return an AiiDAEnsemble instance.""" - import os - from cellconstructor.Phonons import Phonons - - path = os.path.dirname(os.path.abspath(__file__)) - - return AiiDAEnsemble(Phonons(os.path.join(path,"dyn"), 3), 0, (2,1,2)) - - -def test_clean_runs(): - """Test the :func:`sscha.aiida_ensemble.AiiDAEnsemble._clean_runs` method.""" - ensemble = get_ensemble() - num_configs, num_atoms = 4, 1 - ensemble.generate(num_configs) - - ensemble.energies = np.ones((num_configs,)) # (configs,) - ensemble.forces = np.ones((num_configs, num_atoms, 3)) # (configs, atoms, force index) - ensemble.stresses = np.ones((num_configs, 3, 3)) # (configs, 3, 3) - ensemble.force_computed = np.array([True, False, True, True], dtype=bool) - ensemble.stress_computed = np.copy(ensemble.force_computed) - ensemble._clean_runs() + ensemble._clean_runs(0) assert all(ensemble.force_computed) assert len(ensemble.force_computed) == 3 From 570a6d77f15cb3a19f1db2753e991dc391cd0dbb Mon Sep 17 00:00:00 2001 From: bastonero Date: Tue, 7 May 2024 17:33:42 +0000 Subject: [PATCH 08/22] Spotting the infamous bug The `self.init()` wasn't called, and it was messing up the minimization. --- Examples/sscha_and_aiida/clean_runs.sh | 1 + Examples/sscha_and_aiida/debug.ipynb | 211 ++ Examples/sscha_and_aiida/log2 | 3460 ------------------------ Examples/sscha_and_aiida/log3 | 1273 --------- Examples/sscha_and_aiida/submit.sh | 2 +- Modules/aiida_ensemble.py | 1 + 6 files changed, 214 insertions(+), 4734 deletions(-) create mode 100644 Examples/sscha_and_aiida/debug.ipynb delete mode 100644 Examples/sscha_and_aiida/log2 delete mode 100644 Examples/sscha_and_aiida/log3 diff --git a/Examples/sscha_and_aiida/clean_runs.sh b/Examples/sscha_and_aiida/clean_runs.sh index 4c9c21cb..2f8cbe74 100755 --- a/Examples/sscha_and_aiida/clean_runs.sh +++ b/Examples/sscha_and_aiida/clean_runs.sh @@ -11,3 +11,4 @@ rm *.dat rm *.pdf rm otf_run* rm input_tmp.in +rm log* diff --git a/Examples/sscha_and_aiida/debug.ipynb b/Examples/sscha_and_aiida/debug.ipynb new file mode 100644 index 00000000..0a12f4a3 --- /dev/null +++ b/Examples/sscha_and_aiida/debug.ipynb @@ -0,0 +1,211 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "plt.rcParams.update({\n", + " 'text.usetex': False,\n", + " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", + " 'pdf.fonttype':42,\n", + " 'font.family':'sans-serif',\n", + " 'font.sans-serif':'Arial',\n", + " 'font.size':14,\n", + " 'mathtext.fontset': 'stixsans',\n", + "})" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "e1 = np.load('./ensembles_P0_T0/energies_pop1.npy')\n", + "e1_ref = np.load('./ensembles_P0_T0_flare/energies_pop1.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.43868396e-05, 1.43867750e-05, 1.43880794e-05, 1.43880354e-05,\n", + " 1.43876365e-05, 1.43876491e-05, 1.43881572e-05, 1.43880628e-05,\n", + " 1.43881299e-05, 1.43880515e-05, 1.43883702e-05, 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"metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(e1-e1_ref).max()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "e1 = np.load('./ensembles_P0_T0/xats_pop1.npy')\n", + "e1_ref = np.load('./ensembles_P0_T0_flare/xats_pop1.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.0" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(e1-e1_ref).max()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "f1 = np.load('./ensembles_P0_T0/forces_pop1.npy')\n", + "f1_ref = np.load('./ensembles_P0_T0_flare/forces_pop1.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.1266246074947972e-08" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(f1-f1_ref).max()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "f1 = np.load('./ensembles_P0_T0/stresses_pop1.npy')\n", + "f1_ref = np.load('./ensembles_P0_T0_flare/stresses_pop1.npy')" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0972052829011716e-11" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.abs(f1-f1_ref).max()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.16 ('aiida-sscha')", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "dbf713cbd6c5cb781e360dd03dc580f1c4e0f3272ba8f8d2e6f58f9ae4ed7519" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Examples/sscha_and_aiida/log2 b/Examples/sscha_and_aiida/log2 deleted file mode 100644 index ed873e6c..00000000 --- a/Examples/sscha_and_aiida/log2 +++ /dev/null @@ -1,3460 +0,0 @@ -Number of symmetry inequivalent displacements: 1 -[BFFS USED] For structure with id=0 -[BFFS USED] For structure with id=1 -[BFFS USED] For structure with id=2 -[BFFS USED] For structure with id=3 -[BFFS USED] For structure with id=4 -[BFFS USED] For structure with id=5 -[BFFS USED] For structure with id=6 -[BFFS USED] For structure with id=7 -[BFFS USED] For structure with id=8 -[BFFS USED] For structure with id=9 -[BFFS USED] For structure with id=10 -[BFFS USED] For structure with id=11 -[BFFS USED] For structure with id=12 -[BFFS USED] For structure with id=13 -[BFFS USED] For structure with id=14 -[BFFS USED] For structure with id=15 -[BFFS USED] For structure with id=16 -[BFFS USED] For structure with id=17 -[BFFS USED] For structure with id=18 -[BFFS USED] For structure with id=19 -[BFFS USED] For structure with id=20 -[BFFS USED] For structure with id=21 -[BFFS USED] For structure with id=22 -[BFFS USED] For structure with id=23 -[BFFS USED] For structure with id=24 -[BFFS USED] For structure with id=25 -[BFFS USED] For structure with id=26 -[BFFS USED] For structure with id=27 -[BFFS USED] For structure with id=28 -[BFFS USED] For structure with id=29 -[BFFS USED] For structure with id=30 -[BFFS USED] For structure with id=31 -[BFFS USED] For structure with id=32 -[BFFS USED] For structure with id=33 -[BFFS USED] For structure with id=34 -[BFFS USED] For structure with id=35 -[BFFS USED] For structure with id=36 -[BFFS USED] For structure with id=37 -[BFFS USED] For structure with id=38 -[BFFS USED] For structure with id=39 -[BFFS USED] For structure with id=40 -[BFFS USED] For structure with id=41 -[BFFS USED] For structure with id=42 -[BFFS USED] For structure with id=43 -[BFFS USED] For structure with id=44 -[BFFS USED] For structure with id=45 -[BFFS USED] For structure with id=46 -[BFFS USED] For structure with id=47 -[BFFS USED] For structure with id=48 -[BFFS USED] For structure with id=49 -=============== SUMMARY AIIDA CALCULATIONS =============== - -Total structures included: 50 -Structures not included : 0 -Steps using OTF-ML model : 50 - -===================== END OF SUMMARY ===================== - - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 1 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 109.20798851 meV -Anharmonic contribution to free energy = -308482.51006196 +- 0.42441910 meV -Free energy = -308373.30207344 +- 0.42441910 meV -FC gradient modulus = 31144.73750721 +- 704.31850696 bohr^2 -Struct gradient modulus = 0.00000000 +- 3.17358501 meV/A -Kong-Liu effective sample size = 43.76599535119353 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 2 -Minimization step, force computed: 50 -Step too large (scalar = 4.381110719001629 | kl_ratio = 0.875319907023871), reducing to 0.1310370697125 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 110.39283626 meV -Anharmonic contribution to free energy = -308483.77130987 +- 0.36594577 meV -Free energy = -308373.37847360 +- 0.36594577 meV -FC gradient modulus = 26075.94026588 +- 593.75571302 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.95176137 meV/A -Kong-Liu effective sample size = 45.313870421619505 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 3 -Minimization step, force computed: 50 -Good step found with 0.1310370697125, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 110.39283626 meV -Anharmonic contribution to free energy = -308483.77130987 +- 0.36594577 meV -Free energy = -308373.37847360 +- 0.36594577 meV -FC gradient modulus = 26689.79824809 +- 607.50273104 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.97586506 meV/A -Kong-Liu effective sample size = 45.313870421619505 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 4 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.38513711 meV -Anharmonic contribution to free energy = -308471.42620652 +- 1.22689717 meV -Free energy = -308372.04106941 +- 1.22689717 meV -FC gradient modulus = 26689.79824809 +- 607.50273104 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.97586506 meV/A -Kong-Liu effective sample size = 25.963274509548036 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 5 -Minimization step, force computed: 50 -Step too large (scalar = 3.093449498731049 | kl_ratio = 0.5729652812256975), reducing to 0.17170713638838586 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.84589890 meV -Anharmonic contribution to free energy = -308473.15235601 +- 1.07801134 meV -Free energy = -308372.30645710 +- 1.07801134 meV -FC gradient modulus = 21523.46542630 +- 484.49959331 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.76078741 meV/A -Kong-Liu effective sample size = 28.67143837308559 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 6 -Minimization step, force computed: 50 -Step too large (scalar = 3.1877455555406184 | kl_ratio = 0.6327298486382722), reducing to 0.15000000000705774 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 102.10410432 meV -Anharmonic contribution to free energy = -308474.61672341 +- 0.95671077 meV -Free energy = -308372.51261910 +- 0.95671077 meV -FC gradient modulus = 22159.81799260 +- 500.87213043 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.78813811 meV/A -Kong-Liu effective sample size = 31.07644772874749 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 7 -Minimization step, force computed: 50 -Step too large (scalar = 3.270031012486098 | kl_ratio = 0.6858043120042278), reducing to 0.1310370697186655 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.19015077 meV -Anharmonic contribution to free energy = -308475.86409362 +- 0.85790359 meV -Free energy = -308372.67394284 +- 0.85790359 meV -FC gradient modulus = 22717.52226235 +- 514.92103584 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.81154988 meV/A -Kong-Liu effective sample size = 33.17360891486492 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 8 -Minimization step, force computed: 50 -Step too large (scalar = 3.3419776505101644 | kl_ratio = 0.7320850901987309), reducing to 0.11447142426430995 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 104.12924948 meV -Anharmonic contribution to free energy = -308476.93041631 +- 0.77724621 meV -Free energy = -308372.80116682 +- 0.77724621 meV -FC gradient modulus = 23206.94507914 +- 527.01647153 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.83179116 meV/A -Kong-Liu effective sample size = 34.978871606051854 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 9 -Minimization step, force computed: 50 -Step too large (scalar = 3.4049601262426026 | kl_ratio = 0.7719241653955746), reducing to 0.10000000000941031 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 104.94248026 meV -Anharmonic contribution to free energy = -308477.84477765 +- 0.71117756 meV -Free energy = -308372.90229739 +- 0.71117756 meV -FC gradient modulus = 23636.70824691 +- 537.46021666 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.84941532 meV/A -Kong-Liu effective sample size = 36.51943833285862 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 10 -Minimization step, force computed: 50 -Step too large (scalar = 3.4601321132000256 | kl_ratio = 0.8059218511477004), reducing to 0.08735804648322065 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 105.64758598 meV -Anharmonic contribution to free energy = -308478.63090432 +- 0.65683304 meV -Free energy = -308372.98331834 +- 0.65683304 meV -FC gradient modulus = 24014.14277249 +- 546.49949666 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.86483328 meV/A -Kong-Liu effective sample size = 37.82700826431796 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 11 -Minimization step, force computed: 50 -Step too large (scalar = 3.5084771483529145 | kl_ratio = 0.834777694166475), reducing to 0.076314282846464 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 106.25958315 meV -Anharmonic contribution to free energy = -308479.30830563 +- 0.61192953 meV -Free energy = -308373.04872247 +- 0.61192953 meV -FC gradient modulus = 24345.57999410 +- 554.33841680 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.87836124 meV/A -Kong-Liu effective sample size = 38.93350980933003 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 12 -Minimization step, force computed: 50 -Step too large (scalar = 3.5508432682297526 | kl_ratio = 0.8591963000969928), reducing to 0.06666666667607696 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 106.79123936 meV -Anharmonic contribution to free energy = -308479.89314257 +- 0.57465991 meV -Free energy = -308373.10190322 +- 0.57465991 meV -FC gradient modulus = 24636.54391658 +- 561.14693290 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.89025125 meV/A -Kong-Liu effective sample size = 39.868733744068535 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 13 -Minimization step, force computed: 50 -Step too large (scalar = 3.587967367509013 | kl_ratio = 0.8798351006681374), reducing to 0.058238697658220644 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 107.25345196 meV -Anharmonic contribution to free energy = -308480.39889301 +- 0.54358496 meV -Free energy = -308373.14544105 +- 0.54358496 meV -FC gradient modulus = 24891.88423006 +- 567.06774018 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.90071056 meV/A -Kong-Liu effective sample size = 40.65924286389403 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 14 -Minimization step, force computed: 50 -Step too large (scalar = 3.620493018116797 | kl_ratio = 0.8972802915659853), reducing to 0.050876188566703125 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 107.65555239 meV -Anharmonic contribution to free energy = -308480.83686492 +- 0.51756546 meV -Free energy = -308373.18131252 +- 0.51756546 meV -FC gradient modulus = 25115.87349327 +- 572.22153740 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.90991393 meV/A -Kong-Liu effective sample size = 41.328058235793904 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 15 -Minimization step, force computed: 50 -Good step found with 0.050876188566703125, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 107.65555239 meV -Anharmonic contribution to free energy = -308480.83686492 +- 0.51756546 meV -Free energy = -308373.18131252 +- 0.51756546 meV -FC gradient modulus = 25312.28219689 +- 576.71106767 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.91801149 meV/A -Kong-Liu effective sample size = 41.328058235793904 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 16 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.64345831 meV -Anharmonic contribution to free energy = -308476.37105162 +- 0.82501309 meV -Free energy = -308372.72759331 +- 0.82501309 meV -FC gradient modulus = 25312.28219689 +- 576.71106767 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.91801149 meV/A -Kong-Liu effective sample size = 33.91805705111914 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 17 -Minimization step, force computed: 50 -Step too large (scalar = 3.201860544739119 | kl_ratio = 0.8207028952970015), reducing to 0.06666666667921373 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 104.15951048 meV -Anharmonic contribution to free energy = -308476.95733139 +- 0.78023143 meV -Free energy = -308372.79782090 +- 0.78023143 meV -FC gradient modulus = 23424.59541316 +- 532.18786353 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.83669319 meV/A -Kong-Liu effective sample size = 34.927323397701485 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 18 -Minimization step, force computed: 50 -Step too large (scalar = 3.234388471252214 | kl_ratio = 0.8451237461587588), reducing to 0.05823869766096086 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 104.60816188 meV -Anharmonic contribution to free energy = -308477.46410353 +- 0.74250859 meV -Free energy = -308372.85594165 +- 0.74250859 meV -FC gradient modulus = 23660.36349702 +- 537.93182169 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.84695859 meV/A -Kong-Liu effective sample size = 35.79708984462944 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 19 -Minimization step, force computed: 50 -Step too large (scalar = 3.262847744116356 | kl_ratio = 0.8661691686648337), reducing to 0.050876188569096925 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 104.99846832 meV -Anharmonic contribution to free energy = -308477.90277819 +- 0.71062605 meV -Free energy = -308372.90430987 +- 0.71062605 meV -FC gradient modulus = 23866.90429496 +- 542.91833238 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.85590526 meV/A -Kong-Liu effective sample size = 36.545958676896745 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 20 -Minimization step, force computed: 50 -Step too large (scalar = 3.287748139384161 | kl_ratio = 0.884289275542217), reducing to 0.044444444454900325 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 105.33820603 meV -Anharmonic contribution to free energy = -308478.28297411 +- 0.68359192 meV -Free energy = -308372.94476808 +- 0.68359192 meV -FC gradient modulus = 24047.81248489 +- 547.25186283 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.86371340 meV/A -Kong-Liu effective sample size = 37.19060142387497 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 21 -Minimization step, force computed: 50 -Step too large (scalar = 3.3095340224566896 | kl_ratio = 0.8998874617260506), reducing to 0.038825798442467384 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 105.63406817 meV -Anharmonic contribution to free energy = -308478.61283663 +- 0.66060042 meV -Free energy = -308372.97876846 +- 0.66060042 meV -FC gradient modulus = 24206.23861019 +- 551.02119282 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.87053425 meV/A -Kong-Liu effective sample size = 37.745678304120766 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 22 -Minimization step, force computed: 50 -Good step found with 0.038825798442467384, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 105.63406817 meV -Anharmonic contribution to free energy = -308478.61283663 +- 0.66060042 meV -Free energy = -308372.97876846 +- 0.66060042 meV -FC gradient modulus = 24344.94775862 +- 554.30211652 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.87649628 meV/A -Kong-Liu effective sample size = 37.745678304120766 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 23 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 102.65297925 meV -Anharmonic contribution to free energy = -308475.22805680 +- 0.91979265 meV -Free energy = -308372.57507755 +- 0.91979265 meV -FC gradient modulus = 24344.94775862 +- 554.30211652 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.87649628 meV/A -Kong-Liu effective sample size = 31.881150917885115 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 24 -Minimization step, force computed: 50 -Step too large (scalar = 3.0220215157691372 | kl_ratio = 0.8446304941459905), reducing to 0.05087618857149072 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.03479187 meV -Anharmonic contribution to free energy = -308475.66872934 +- 0.88375387 meV -Free energy = -308372.63393747 +- 0.88375387 meV -FC gradient modulus = 22983.76519400 +- 521.14464346 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.81473407 meV/A -Kong-Liu effective sample size = 32.64647363290491 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 25 -Minimization step, force computed: 50 -Step too large (scalar = 3.0446505526024676 | kl_ratio = 0.8649062647614636), reducing to 0.0444444444569915 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.36713665 meV -Anharmonic contribution to free energy = -308476.05056478 +- 0.85303521 meV -Free energy = -308372.68342813 +- 0.85303521 meV -FC gradient modulus = 23154.66610689 +- 525.42100898 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.82266123 meV/A -Kong-Liu effective sample size = 33.31170718712266 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 26 -Minimization step, force computed: 50 -Step too large (scalar = 3.064430715166865 | kl_ratio = 0.8825303633101211), reducing to 0.03882579844429419 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.65656096 meV -Anharmonic contribution to free energy = -308476.38177594 +- 0.82678757 meV -Free energy = -308372.72521498 +- 0.82678757 meV -FC gradient modulus = 23304.19002244 +- 529.13503155 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.82954626 meV/A -Kong-Liu effective sample size = 33.88950717062663 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 27 -Minimization step, force computed: 50 -Step too large (scalar = 3.0817219258395125 | kl_ratio = 0.8978380755957126), reducing to 0.033917459049256346 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.90871159 meV -Anharmonic contribution to free energy = -308476.66934278 +- 0.80431040 meV -Free energy = -308372.76063119 +- 0.80431040 meV -FC gradient modulus = 23435.00329746 +- 532.36349498 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.83553437 meV/A -Kong-Liu effective sample size = 34.39119352782019 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 28 -Minimization step, force computed: 50 -Good step found with 0.033917459049256346, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 103.90871159 meV -Anharmonic contribution to free energy = -308476.66934278 +- 0.80431040 meV -Free energy = -308372.76063119 +- 0.80431040 meV -FC gradient modulus = 23549.43740078 +- 535.17195298 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.84074788 meV/A -Kong-Liu effective sample size = 34.39119352782019 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 29 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 101.35801288 meV -Anharmonic contribution to free energy = -308473.70976162 +- 1.05209352 meV -Free energy = -308372.35174875 +- 1.05209352 meV -FC gradient modulus = 23549.43740078 +- 535.17195298 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.84074788 meV/A -Kong-Liu effective sample size = 29.22290194347556 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 30 -Minimization step, force computed: 50 -Step too large (scalar = 2.8511705426148986 | kl_ratio = 0.8497204937024408), reducing to 0.044444444459082674 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 101.68414856 meV -Anharmonic contribution to free energy = -308474.09385506 +- 1.01844531 meV -Free energy = -308372.40970650 +- 1.01844531 meV -FC gradient modulus = 22415.72781283 +- 506.51233375 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.78573420 meV/A -Kong-Liu effective sample size = 29.880635163383793 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 31 -Minimization step, force computed: 50 -Step too large (scalar = 2.8694480562462523 | kl_ratio = 0.8688455414963236), reducing to 0.038825798446121 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 101.96816509 meV -Anharmonic contribution to free energy = -308474.42697273 +- 0.98958476 meV -Free energy = -308372.45880765 +- 0.98958476 meV -FC gradient modulus = 22558.55037517 +- 510.21289464 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.79288058 meV/A -Kong-Liu effective sample size = 30.455645608398775 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 32 -Minimization step, force computed: 50 -Step too large (scalar = 2.885412656382911 | kl_ratio = 0.885565241687881), reducing to 0.03391745905085221 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 102.21560397 meV -Anharmonic contribution to free energy = -308474.71615266 +- 0.96478794 meV -Free energy = -308372.50054868 +- 0.96478794 meV -FC gradient modulus = 22683.39778529 +- 513.42625793 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.79906980 meV/A -Kong-Liu effective sample size = 30.957809087182262 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 33 -Minimization step, force computed: 50 -Good step found with 0.03391745905085221, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 102.21560397 meV -Anharmonic contribution to free energy = -308474.71615266 +- 0.96478794 meV -Free energy = -308372.50054868 +- 0.96478794 meV -FC gradient modulus = 22792.53661986 +- 516.21893568 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.80443841 meV/A -Kong-Liu effective sample size = 30.957809087182262 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 34 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.71208641 meV -Anharmonic contribution to free energy = -308471.73550100 +- 1.23476700 meV -Free energy = -308372.02341460 +- 1.23476700 meV -FC gradient modulus = 22792.53661986 +- 516.21893568 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.80443841 meV/A -Kong-Liu effective sample size = 25.89532015605089 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 35 -Minimization step, force computed: 50 -Step too large (scalar = 2.672397350523524 | kl_ratio = 0.8364713434056468), reducing to 0.04444444446117385 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.03219460 meV -Anharmonic contribution to free energy = -308472.12252228 +- 1.19858906 meV -Free energy = -308372.09032769 +- 1.19858906 meV -FC gradient modulus = 21707.89430590 +- 487.54054040 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.74679707 meV/A -Kong-Liu effective sample size = 26.525672178566428 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 36 -Minimization step, force computed: 50 -Step too large (scalar = 2.6893774030383533 | kl_ratio = 0.8568329917619748), reducing to 0.03882579844794781 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.31096074 meV -Anharmonic contribution to free energy = -308472.45814212 +- 1.16744246 meV -Free energy = -308372.14718138 +- 1.16744246 meV -FC gradient modulus = 21844.99274959 +- 491.25669216 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.75439070 meV/A -Kong-Liu effective sample size = 27.079868396811126 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 37 -Minimization step, force computed: 50 -Step too large (scalar = 2.7041949542761916 | kl_ratio = 0.8747346532356272), reducing to 0.03391745905244808 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.55382446 meV -Anharmonic contribution to free energy = -308472.74946295 +- 1.14059364 meV -Free energy = -308372.19563850 +- 1.14059364 meV -FC gradient modulus = 21964.72188724 +- 494.48069990 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.76094300 meV/A -Kong-Liu effective sample size = 27.56630053150732 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 38 -Minimization step, force computed: 50 -Step too large (scalar = 2.7171289886786814 | kl_ratio = 0.8904473974200209), reducing to 0.029629629642176684 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.76548508 meV -Anharmonic contribution to free energy = -308473.00254039 +- 1.11742044 meV -Free energy = -308372.23705531 +- 1.11742044 meV -FC gradient modulus = 22069.30099286 +- 497.28034798 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.76660782 meV/A -Kong-Liu effective sample size = 27.9927172030087 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 39 -Minimization step, force computed: 50 -Good step found with 0.029629629642176684, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 100.76548508 meV -Anharmonic contribution to free energy = -308473.00254039 +- 1.11742044 meV -Free energy = -308372.23705531 +- 1.11742044 meV -FC gradient modulus = 22160.65818177 +- 499.71345013 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.77151329 meV/A -Kong-Liu effective sample size = 27.9927172030087 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 40 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 98.61709046 meV -Anharmonic contribution to free energy = -308470.38945538 +- 1.36599299 meV -Free energy = -308371.77236492 +- 1.36599299 meV -FC gradient modulus = 22160.65818177 +- 499.71345013 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.77151329 meV/A -Kong-Liu effective sample size = 23.734494184829853 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 41 -Minimization step, force computed: 50 -Step too large (scalar = 2.543073766840762 | kl_ratio = 0.8478810403685582), reducing to 0.03882579844977462 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 98.89139135 meV -Anharmonic contribution to free energy = -308470.72768409 +- 1.33321890 meV -Free energy = -308371.83629274 +- 1.33321890 meV -FC gradient modulus = 21245.54833898 +- 474.58859571 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.71855081 meV/A -Kong-Liu effective sample size = 24.259056123715467 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 42 -Minimization step, force computed: 50 -Step too large (scalar = 2.557025122052333 | kl_ratio = 0.8666202694002163), reducing to 0.03391745905404394 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.13036358 meV -Anharmonic contribution to free energy = -308471.02125346 +- 1.30488539 meV -Free energy = -308371.89088988 +- 1.30488539 meV -FC gradient modulus = 21361.50681947 +- 477.84101714 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.72554820 meV/A -Kong-Liu effective sample size = 24.721253169900066 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 43 -Minimization step, force computed: 50 -Step too large (scalar = 2.569193722788679 | kl_ratio = 0.8831316013596204), reducing to 0.0296296296435708 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.33863171 meV -Anharmonic contribution to free energy = -308471.27627015 +- 1.28036733 meV -Free energy = -308371.93763844 +- 1.28036733 meV -FC gradient modulus = 21462.71176710 +- 480.66374289 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.73158360 meV/A -Kong-Liu effective sample size = 25.127816330474158 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 44 -Minimization step, force computed: 50 -Step too large (scalar = 2.5798106789015445 | kl_ratio = 0.8976554918996352), reducing to 0.025883865634400954 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.52019683 meV -Anharmonic contribution to free energy = -308471.49795630 +- 1.25913302 meV -Free energy = -308371.97775947 +- 1.25913302 meV -FC gradient modulus = 21551.06082255 +- 483.11563212 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.73679890 meV/A -Kong-Liu effective sample size = 25.48496576060005 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 45 -Minimization step, force computed: 50 -Good step found with 0.025883865634400954, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 99.52019683 meV -Anharmonic contribution to free energy = -308471.49795630 +- 1.25913302 meV -Free energy = -308371.97775947 +- 1.25913302 meV -FC gradient modulus = 21628.20053757 +- 485.24698479 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.74131263 meV/A -Kong-Liu effective sample size = 25.48496576060005 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 46 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 97.67227411 meV -Anharmonic contribution to free energy = -308469.20637561 +- 1.48434985 meV -Free energy = -308371.53410149 +- 1.48434985 meV -FC gradient modulus = 21628.20053757 +- 485.24698479 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.74131263 meV/A -Kong-Liu effective sample size = 21.933354415360366 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 47 -Minimization step, force computed: 50 -Step too large (scalar = 2.4358961480626515 | kl_ratio = 0.8606389595103751), reducing to 0.03391745905563981 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 97.90791366 meV -Anharmonic contribution to free energy = -308469.50213767 +- 1.45501686 meV -Free energy = -308371.59422401 +- 1.45501686 meV -FC gradient modulus = 20850.51674727 +- 463.16235424 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.69254939 meV/A -Kong-Liu effective sample size = 22.368512583859964 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 48 -Minimization step, force computed: 50 -Step too large (scalar = 2.447478519554621 | kl_ratio = 0.8777140528256802), reducing to 0.02962962964496492 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 98.11327621 meV -Anharmonic contribution to free energy = -308469.75905456 +- 1.42957996 meV -Free energy = -308371.64577836 +- 1.42957996 meV -FC gradient modulus = 20949.23142544 +- 466.01643654 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.69898871 meV/A -Kong-Liu effective sample size = 22.752307952922393 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 49 -Minimization step, force computed: 50 -Step too large (scalar = 2.4575777623921335 | kl_ratio = 0.8927737304673028), reducing to 0.02588386563561883 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 98.29230744 meV -Anharmonic contribution to free energy = -308469.98238787 +- 1.40750539 meV -Free energy = -308371.69008043 +- 1.40750539 meV -FC gradient modulus = 21035.35110122 +- 468.49472804 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.70454501 meV/A -Kong-Liu effective sample size = 23.090253085933018 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 50 -Minimization step, force computed: 50 -Good step found with 0.02588386563561883, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 98.29230744 meV -Anharmonic contribution to free energy = -308469.98238787 +- 1.40750539 meV -Free energy = -308371.69008043 +- 1.40750539 meV -FC gradient modulus = 21110.50240823 +- 470.64836023 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.70934754 meV/A -Kong-Liu effective sample size = 23.090253085933018 - - -The gw gradient satisfy the convergence condition. -KL: 23.090253085933018 KL/N: 0.46180506171866037 KL RAT: 0.5 - According to your input criteria - you are out of the statistical sampling. -Check the stopping criteria: Running = False -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - -Restoring the last good dynamical matrix. -Updating the importance sampling... - - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 50 steps - -Free energy = -308371.69008043 +- 1.40750539 meV -FC gradient modulus = 21110.50240823 +- 470.64836023 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.70934754 meV/A -Kong-Liu effective sample size = 23.090253085933018 - -Total force on the centroids [eV/A]: - 0) 0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - 1) 0.000000 0.000000 0.000000 +- 0.000000 -0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - 0.86860231 0.00000000 0.00000000 0.02163903 0.00000000 0.00000000 - 0.00000000 0.86860231 0.00000000 +- 0.00000000 0.02163903 0.00000000 - -0.00000000 0.00000000 0.86860231 0.00000000 0.00000000 0.02163903 - - Ab initio average stress [GPa]: - 0.68720493 0.00000000 0.00000000 - 0.00000000 0.68720493 0.00000000 - 0.00000000 -0.00000000 0.68720493 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds -Average of 0.6527698040008545 s per call -Subroutine report: - Function: GoParallel - N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.6516294479370117 s per call - Subroutine report: - Function: compute - N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.6515698432922363 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 1 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.6517899036407471 s per call - - -Function: minimization_step -N = 50 calls took: 0 hours; 0 minutes; 1.76 seconds -Average of 0.03528819561004639 s per call -Subroutine report: - Function: get_fourier_gradient - N = 50 calls took: 0 hours; 0 minutes; 0.11 seconds - Average of 0.002203860282897949 s per call - Subroutine report: - Function: GoParallel - N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds - Average of 0.0010434627532958985 s per call - Subroutine report: - Function: compute - N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds - Average of 0.0009998083114624023 s per call - Subroutine report: - - - Function: fourier gradient upsilon q - N = 50 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.000511336326599121 s per call - - Function: fourier gradient Y * u - N = 50 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.0005041360855102539 s per call - - Function: fourier gradient julia - N = 50 calls took: 0 hours; 0 minutes; 0.06 seconds - Average of 0.0011458396911621094 s per call - - - Function: SymmetrizeFCQ - N = 50 calls took: 0 hours; 0 minutes; 0.48 seconds - Average of 0.009649415016174317 s per call - - Function: Symmetrize - N = 50 calls took: 0 hours; 0 minutes; 0.49 seconds - Average of 0.00971813678741455 s per call - - Function: update - N = 50 calls took: 0 hours; 0 minutes; 0.62 seconds - Average of 0.012317957878112793 s per call - Subroutine report: - Function: update_weights_fourier - N = 50 calls took: 0 hours; 0 minutes; 0.61 seconds - Average of 0.012276368141174316 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 50 calls took: 0 hours; 0 minutes; 0.41 seconds - Average of 0.008104453086853028 s per call - Subroutine report: - Function: DyagDinQ - N = 400 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.00020899832248687743 s per call - - Function: Manipulate polarization vectors - N = 400 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.00017248690128326415 s per call - - - Function: Time to get SSCHA energy and forces - N = 50 calls took: 0 hours; 0 minutes; 0.05 seconds - Average of 0.0010889768600463867 s per call - - Function: get upsilon fourier - N = 50 calls took: 0 hours; 0 minutes; 0.04 seconds - Average of 0.0008661460876464844 s per call - - Function: get uYu - N = 50 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.0016811180114746093 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = 0.8686 +- 0.0216 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.0470 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0837169008e+02 eV - Gibbs Free energy = -3.0837169008e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.04698463143717 -[CELL] unit_cell: -Cell([[2.71548, 2.71548, 0.0], [2.71548, 0.0, 2.71548], [0.0, 2.71548, 2.71548]]) -[CELL] CURRENT STRAIN: -[[ 0.00000000e+00 4.39618027e-18 -4.39618027e-18] - [ 4.39618027e-18 0.00000000e+00 -4.39618027e-18] - [ 4.39618027e-18 -4.39618027e-18 0.00000000e+00]] -[CELL] NEW STRESS: -[[ 5.42138924e-03 1.24433616e-18 1.24433616e-18] - [ 1.86650424e-18 5.42138924e-03 0.00000000e+00] - [-6.22168079e-19 6.22168079e-19 5.42138924e-03]] -GRAD MAT: -[[-2.17110292e-01 -5.07863670e-17 -4.88774550e-17] - [-7.57023225e-17 -2.17110292e-01 9.54455980e-19] - [ 2.39614995e-17 -2.39614995e-17 -2.17110292e-01]] - -[CELL] New step: -[CELL] X_OLD = [ 0.00000000e+00 4.39618027e-18 -4.39618027e-18 4.39618027e-18 - 0.00000000e+00 -4.39618027e-18 4.39618027e-18 -4.39618027e-18 - 0.00000000e+00] | ALPHA = 0.013335807390121452 -[CELL] DIRECTION = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 - -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 - -2.17110292e-01] -[CELL] GRADIENT = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 - -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 - -2.17110292e-01] -[CELL] X_NEW = [ 2.89534103e-03 5.07345748e-18 -3.74435994e-18 5.40573186e-18 - 2.89534103e-03 -4.40890871e-18 4.07663433e-18 -4.07663433e-18 - 2.89534103e-03] -[CELL] Step number = 1 - -NEW STRAIN: -[[ 2.89534103e-03 5.07345748e-18 -3.74435994e-18] - [ 5.40573186e-18 2.89534103e-03 -4.40890871e-18] - [ 4.07663433e-18 -4.07663433e-18 2.89534103e-03]] -NEW VOLUME: -40.395841778473766 - - Currently estimated bulk modulus = 100.000 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72334224 2.72334224 -0.00000000) - v2 [A] = ( 2.72334224 0.00000000 2.72334224) - v3 [A] = ( 0.00000000 2.72334224 2.72334224) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. -[BFFS USED] For structure with id=0 -[BFFS USED] For structure with id=1 -[BFFS USED] For structure with id=2 -[BFFS USED] For structure with id=3 -[BFFS USED] For structure with id=4 -[BFFS USED] For structure with id=5 -[BFFS USED] For structure with id=6 -[BFFS USED] For structure with id=7 -[BFFS USED] For structure with id=8 -[BFFS USED] For structure with id=9 -[BFFS USED] For structure with id=10 -[BFFS USED] For structure with id=11 -[BFFS USED] For structure with id=12 -[BFFS USED] For structure with id=13 -[BFFS USED] For structure with id=14 -[BFFS USED] For structure with id=15 -[BFFS USED] For structure with id=16 -[BFFS USED] For structure with id=17 -[BFFS USED] For structure with id=18 -[BFFS USED] For structure with id=19 -[BFFS USED] For structure with id=20 -[BFFS USED] For structure with id=21 -[BFFS USED] For structure with id=22 -[BFFS USED] For structure with id=23 -[BFFS USED] For structure with id=24 -[BFFS USED] For structure with id=25 -[BFFS USED] For structure with id=26 -[BFFS USED] For structure with id=27 -[BFFS USED] For structure with id=28 -[BFFS USED] For structure with id=29 -[BFFS USED] For structure with id=30 -[BFFS USED] For structure with id=31 -[BFFS USED] For structure with id=32 -[BFFS USED] For structure with id=33 -[BFFS USED] For structure with id=34 -[BFFS USED] For structure with id=35 -[BFFS USED] For structure with id=36 -[BFFS USED] For structure with id=37 -[BFFS USED] For structure with id=38 -[BFFS USED] For structure with id=39 -[BFFS USED] For structure with id=40 -[BFFS USED] For structure with id=41 -[BFFS USED] For structure with id=42 -[BFFS USED] For structure with id=43 -[BFFS USED] For structure with id=44 -[BFFS USED] For structure with id=45 -[BFFS USED] For structure with id=46 -[BFFS USED] For structure with id=47 -[BFFS USED] For structure with id=48 -[BFFS USED] For structure with id=49 -=============== SUMMARY AIIDA CALCULATIONS =============== - -Total structures included: 50 -Structures not included : 0 -Steps using OTF-ML model : 50 - -===================== END OF SUMMARY ===================== - - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 51 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 90.88945656 meV -Anharmonic contribution to free energy = -308462.93607119 +- 0.91810859 meV -Free energy = -308372.04661463 +- 0.91810859 meV -FC gradient modulus = 22015.80640141 +- 485.62121751 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.44714794 meV/A -Kong-Liu effective sample size = 45.203949864959775 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 52 -Minimization step, force computed: 50 -Good step found with 0.15000000000000002, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 90.88945656 meV -Anharmonic contribution to free energy = -308462.93607119 +- 0.91810859 meV -Free energy = -308372.04661463 +- 0.91810859 meV -FC gradient modulus = 18271.01206509 +- 411.74840303 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.24762988 meV/A -Kong-Liu effective sample size = 45.203949864959775 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 53 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 80.68092225 meV -Anharmonic contribution to free energy = -308450.51056227 +- 1.46031226 meV -Free energy = -308369.82964002 +- 1.46031226 meV -FC gradient modulus = 18271.01206509 +- 411.74840303 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.24762988 meV/A -Kong-Liu effective sample size = 27.70751687783123 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 54 -Minimization step, force computed: 50 -Step too large (scalar = 1.3290557919573913 | kl_ratio = 0.6129445979964895), reducing to 0.19655560456875001 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.04461766 meV -Anharmonic contribution to free energy = -308452.18873596 +- 1.38810811 meV -Free energy = -308370.14411830 +- 1.38810811 meV -FC gradient modulus = 13520.42045673 +- 315.40643325 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.95707971 meV/A -Kong-Liu effective sample size = 30.10983237026976 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 55 -Minimization step, force computed: 50 -Step too large (scalar = 1.3906749879262446 | kl_ratio = 0.666088526781808), reducing to 0.17170713638838586 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 83.21680813 meV -Anharmonic contribution to free energy = -308453.62984556 +- 1.32456804 meV -Free energy = -308370.41303743 +- 1.32456804 meV -FC gradient modulus = 14131.91824415 +- 327.69156762 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.99660819 meV/A -Kong-Liu effective sample size = 32.23658084255212 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 56 -Minimization step, force computed: 50 -Step too large (scalar = 1.4441462505928628 | kl_ratio = 0.7131363727916303), reducing to 0.15000000000705774 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 84.22689177 meV -Anharmonic contribution to free energy = -308454.86941285 +- 1.26921767 meV -Free energy = -308370.64252107 +- 1.26921767 meV -FC gradient modulus = 14663.73883232 +- 338.43541311 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.03043645 meV/A -Kong-Liu effective sample size = 34.092738567753976 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 57 -Minimization step, force computed: 50 -Step too large (scalar = 1.4905661670685848 | kl_ratio = 0.7541982209431051), reducing to 0.1310370697186655 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.09906908 meV -Anharmonic contribution to free energy = -308455.93734975 +- 1.22129760 meV -Free energy = -308370.83828068 +- 1.22129760 meV -FC gradient modulus = 15126.40351807 +- 347.81520594 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.05945438 meV/A -Kong-Liu effective sample size = 35.696233361083124 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 58 -Minimization step, force computed: 50 -Step too large (scalar = 1.5308862825137615 | kl_ratio = 0.7896706696587451), reducing to 0.11447142426430995 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.85344973 meV -Anharmonic contribution to free energy = -308456.85883119 +- 1.17995897 meV -Free energy = -308371.00538146 +- 1.17995897 meV -FC gradient modulus = 15529.05602057 +- 355.99605325 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.08440368 meV/A -Kong-Liu effective sample size = 37.07176302247563 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 59 -Minimization step, force computed: 50 -Step too large (scalar = 1.565928274779367 | kl_ratio = 0.8201000826968026), reducing to 0.10000000000941031 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 86.50687293 meV -Anharmonic contribution to free energy = -308457.65506883 +- 1.14436548 meV -Free energy = -308371.14819590 +- 1.14436548 meV -FC gradient modulus = 15879.61745273 +- 363.12746366 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.10590093 meV/A -Kong-Liu effective sample size = 38.246421478782025 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 60 -Minimization step, force computed: 50 -Step too large (scalar = 1.5964002739416117 | kl_ratio = 0.8460858308408369), reducing to 0.08735804648322065 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 87.07352885 meV -Anharmonic contribution to free energy = -308458.34397179 +- 1.11374017 meV -Free energy = -308371.27044294 +- 1.11374017 meV -FC gradient modulus = 16184.94200835 +- 369.34260160 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.12445946 meV/A -Kong-Liu effective sample size = 39.246935776196175 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 61 -Minimization step, force computed: 50 -Step too large (scalar = 1.6229123216505097 | kl_ratio = 0.8682191687549581), reducing to 0.076314282846464 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 87.56543862 meV -Anharmonic contribution to free energy = -308458.94069943 +- 1.08738995 meV -Free energy = -308371.37526081 +- 1.08738995 meV -FC gradient modulus = 16450.96028557 +- 374.75890193 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.14050803 meV/A -Kong-Liu effective sample size = 40.098121775298054 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 62 -Minimization step, force computed: 50 -Step too large (scalar = 1.6459902117117944 | kl_ratio = 0.8870490719303371), reducing to 0.06666666667607696 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 87.99283091 meV -Anharmonic contribution to free energy = -308459.45811877 +- 1.06470698 meV -Free energy = -308371.46528785 +- 1.06470698 meV -FC gradient modulus = 16682.80614698 +- 379.47930456 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.15440637 meV/A -Kong-Liu effective sample size = 40.82216754010444 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 63 -Minimization step, force computed: 50 -Good step found with 0.06666666667607696, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 87.99283091 meV -Anharmonic contribution to free energy = -308459.45811877 +- 1.06470698 meV -Free energy = -308371.46528785 +- 1.06470698 meV -FC gradient modulus = 16884.92691674 +- 383.59371446 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.16645764 meV/A -Kong-Liu effective sample size = 40.82216754010444 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 64 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 83.80390395 meV -Anharmonic contribution to free energy = -308454.29049866 +- 1.30302428 meV -Free energy = -308370.48659471 +- 1.30302428 meV -FC gradient modulus = 16884.92691674 +- 383.59371446 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.16645764 meV/A -Kong-Liu effective sample size = 32.96307412623533 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 65 -Minimization step, force computed: 50 -Step too large (scalar = 1.3619576175073762 | kl_ratio = 0.8074797619173897), reducing to 0.08735804648733096 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 84.34547352 meV -Anharmonic contribution to free energy = -308454.96415899 +- 1.27176056 meV -Free energy = -308370.61868547 +- 1.27176056 meV -FC gradient modulus = 14941.22018823 +- 343.15164440 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.04280536 meV/A -Kong-Liu effective sample size = 34.01138081177903 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 66 -Minimization step, force computed: 50 -Step too large (scalar = 1.3848062655591078 | kl_ratio = 0.833159600806734), reducing to 0.07631428285005468 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 84.81561700 meV -Anharmonic contribution to free energy = -308455.54782480 +- 1.24462324 meV -Free energy = -308370.73220780 +- 1.24462324 meV -FC gradient modulus = 15189.43956752 +- 348.33166310 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.05910574 meV/A -Kong-Liu effective sample size = 34.920297786830076 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 67 -Minimization step, force computed: 50 -Step too large (scalar = 1.4046891680155689 | kl_ratio = 0.8554248804285991), reducing to 0.06666666667921371 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.22410624 meV -Anharmonic contribution to free energy = -308456.05401354 +- 1.22108458 meV -Free energy = -308370.82990731 +- 1.22108458 meV -FC gradient modulus = 15405.68008879 +- 352.84272573 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.07317830 meV/A -Kong-Liu effective sample size = 35.70701229252045 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 68 -Minimization step, force computed: 50 -Step too large (scalar = 1.421999503512891 | kl_ratio = 0.8746966279397398), reducing to 0.05823869766096085 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.57928752 meV -Anharmonic contribution to free energy = -308456.49339384 +- 1.20067074 meV -Free energy = -308370.91410632 +- 1.20067074 meV -FC gradient modulus = 15594.12801905 +- 356.77204032 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.08534693 meV/A -Kong-Liu effective sample size = 36.38732659028425 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 69 -Minimization step, force computed: 50 -Step too large (scalar = 1.4370765124905047 | kl_ratio = 0.8913619433494482), reducing to 0.05087618856909691 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.88831203 meV -Anharmonic contribution to free energy = -308456.87507996 +- 1.18296513 meV -Free energy = -308370.98676793 +- 1.18296513 meV -FC gradient modulus = 15758.40631607 +- 360.19543539 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.09588384 meV/A -Kong-Liu effective sample size = 36.975424642188614 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 70 -Minimization step, force computed: 50 -Good step found with 0.05087618856909691, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 85.88831203 meV -Anharmonic contribution to free energy = -308456.87507996 +- 1.18296513 meV -Free energy = -308370.98676793 +- 1.18296513 meV -FC gradient modulus = 15901.65372878 +- 363.17877623 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.10501876 meV/A -Kong-Liu effective sample size = 36.975424642188614 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 71 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.81916860 meV -Anharmonic contribution to free energy = -308453.02856106 +- 1.36575680 meV -Free energy = -308370.20939246 +- 1.36575680 meV -FC gradient modulus = 15901.65372878 +- 363.17877623 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.10501876 meV/A -Kong-Liu effective sample size = 30.868983704896838 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 72 -Minimization step, force computed: 50 -Step too large (scalar = 1.244881852950903 | kl_ratio = 0.8348513642132892), reducing to 0.06666666668235047 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 83.21374748 meV -Anharmonic contribution to free energy = -308453.52619883 +- 1.34226569 meV -Free energy = -308370.31245134 +- 1.34226569 meV -FC gradient modulus = 14496.99320427 +- 333.37906854 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.01068935 meV/A -Kong-Liu effective sample size = 31.65402156414764 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 73 -Minimization step, force computed: 50 -Step too large (scalar = 1.2603707938800812 | kl_ratio = 0.8560827054851642), reducing to 0.05823869766370106 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 83.55683736 meV -Anharmonic contribution to free energy = -308453.95823926 +- 1.32179006 meV -Free energy = -308370.40140191 +- 1.32179006 meV -FC gradient modulus = 14676.12237924 +- 337.19207944 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.02306400 meV/A -Kong-Liu effective sample size = 32.33920645444582 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 74 -Minimization step, force computed: 50 -Step too large (scalar = 1.2738586296460972 | kl_ratio = 0.874613524182413), reducing to 0.050876188571490705 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 83.85534458 meV -Anharmonic contribution to free energy = -308454.33360776 +- 1.30395380 meV -Free energy = -308370.47826318 +- 1.30395380 meV -FC gradient modulus = 14832.23247082 +- 340.51298051 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.03376377 meV/A -Kong-Liu effective sample size = 32.93648909132388 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 75 -Minimization step, force computed: 50 -Step too large (scalar = 1.2856085646942987 | kl_ratio = 0.8907670272904358), reducing to 0.044444444456991486 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 84.11520257 meV -Anharmonic contribution to free energy = -308454.65995357 +- 1.28842213 meV -Free energy = -308370.54475100 +- 1.28842213 meV -FC gradient modulus = 14968.32364691 +- 343.40608477 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.04302780 meV/A -Kong-Liu effective sample size = 33.45673356204702 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 76 -Minimization step, force computed: 50 -Good step found with 0.044444444456991486, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 84.11520257 meV -Anharmonic contribution to free energy = -308454.65995357 +- 1.28842213 meV -Free energy = -308370.54475100 +- 1.28842213 meV -FC gradient modulus = 15086.99508644 +- 345.92718500 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.05105814 meV/A -Kong-Liu effective sample size = 33.45673356204702 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 77 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 81.52101581 meV -Anharmonic contribution to free energy = -308451.36077216 +- 1.44684871 meV -Free energy = -308369.83975635 +- 1.44684871 meV -FC gradient modulus = 15086.99508644 +- 345.92718500 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.05105814 meV/A -Kong-Liu effective sample size = 28.18282131790501 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 78 -Minimization step, force computed: 50 -Step too large (scalar = 1.1337028678683456 | kl_ratio = 0.8423661941067468), reducing to 0.058238697666441276 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 81.85378637 meV -Anharmonic contribution to free energy = -308451.78613078 +- 1.42676964 meV -Free energy = -308369.93234440 +- 1.42676964 meV -FC gradient modulus = 13913.76744704 +- 320.57971974 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.96793982 meV/A -Kong-Liu effective sample size = 28.846111198773677 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 79 -Minimization step, force computed: 50 -Step too large (scalar = 1.145958078920399 | kl_ratio = 0.8621914971250036), reducing to 0.050876188573884505 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.14331714 meV -Anharmonic contribution to free energy = -308452.15576538 +- 1.40920960 meV -Free energy = -308370.01244824 +- 1.40920960 meV -FC gradient modulus = 14063.33749952 +- 323.82124967 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.97882645 meV/A -Kong-Liu effective sample size = 29.42779423860135 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 80 -Minimization step, force computed: 50 -Step too large (scalar = 1.156632600239579 | kl_ratio = 0.8795776247560504), reducing to 0.04444444445908266 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.39536239 meV -Anharmonic contribution to free energy = -308452.47717798 +- 1.39386481 meV -Free energy = -308370.08181559 +- 1.39386481 meV -FC gradient modulus = 14193.69850046 +- 326.64473153 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.98824464 meV/A -Kong-Liu effective sample size = 29.937194048596933 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 81 -Minimization step, force computed: 50 -Step too large (scalar = 1.165933710906406 | kl_ratio = 0.8948032536731972), reducing to 0.03882579844612099 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.61487711 meV -Anharmonic contribution to free energy = -308452.75681584 +- 1.38046507 meV -Free energy = -308370.14193873 +- 1.38046507 meV -FC gradient modulus = 14307.35113864 +- 329.10477327 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.99640260 meV/A -Kong-Liu effective sample size = 30.382836714684355 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 82 -Minimization step, force computed: 50 -Good step found with 0.03882579844612099, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 82.61487711 meV -Anharmonic contribution to free energy = -308452.75681584 +- 1.38046507 meV -Free energy = -308370.14193873 +- 1.38046507 meV -FC gradient modulus = 14406.46258673 +- 331.24873624 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.00347666 meV/A -Kong-Liu effective sample size = 30.382836714684355 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 83 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 80.41353288 meV -Anharmonic contribution to free energy = -308449.92260538 +- 1.51602935 meV -Free energy = -308369.50907250 +- 1.51602935 meV -FC gradient modulus = 14406.46258673 +- 331.24873624 bohr^2 -Struct gradient modulus = 0.00000000 +- 2.00347666 meV/A -Kong-Liu effective sample size = 25.923222599399196 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 84 -Minimization step, force computed: 50 -Step too large (scalar = 1.0442153142833297 | kl_ratio = 0.853219297553945), reducing to 0.0508761885762783 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 80.69536774 meV -Anharmonic contribution to free energy = -308450.28692005 +- 1.49901835 meV -Free energy = -308369.59155231 +- 1.49901835 meV -FC gradient modulus = 13419.90614291 +- 309.59138216 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.93022051 meV/A -Kong-Liu effective sample size = 26.477157756926804 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 85 -Minimization step, force computed: 50 -Step too large (scalar = 1.0540408477559233 | kl_ratio = 0.8714511421552058), reducing to 0.044444444461173835 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 80.94071455 meV -Anharmonic contribution to free energy = -308450.60376429 +- 1.48410504 meV -Free energy = -308369.66304974 +- 1.48410504 meV -FC gradient modulus = 13545.61703270 +- 312.35824621 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.93978826 meV/A -Kong-Liu effective sample size = 26.96419211872681 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 86 -Minimization step, force computed: 50 -Step too large (scalar = 1.062601358621769 | kl_ratio = 0.887481059518538), reducing to 0.0388257984479478 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 81.15439621 meV -Anharmonic contribution to free energy = -308450.87946993 +- 1.47104582 meV -Free energy = -308369.72507371 +- 1.47104582 meV -FC gradient modulus = 13655.19848057 +- 314.76885015 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.94807241 meV/A -Kong-Liu effective sample size = 27.39178974917923 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 87 -Minimization step, force computed: 50 -Good step found with 0.0388257984479478, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 81.15439621 meV -Anharmonic contribution to free energy = -308450.87946993 +- 1.47104582 meV -Free energy = -308369.72507371 +- 1.47104582 meV -FC gradient modulus = 13750.74636699 +- 316.86962713 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.95525321 meV/A -Kong-Liu effective sample size = 27.39178974917923 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 88 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.01237564 meV -Anharmonic contribution to free energy = -308448.08803035 +- 1.60153131 meV -Free energy = -308369.07565472 +- 1.60153131 meV -FC gradient modulus = 13750.74636699 +- 316.86962713 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.95525321 meV/A -Kong-Liu effective sample size = 23.17643383538277 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 89 -Minimization step, force computed: 50 -Step too large (scalar = 0.9505939811729262 | kl_ratio = 0.8461087810473293), reducing to 0.0508761885786721 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.28661103 meV -Anharmonic contribution to free energy = -308448.44657407 +- 1.58536571 meV -Free energy = -308369.15996305 +- 1.58536571 meV -FC gradient modulus = 12799.08935045 +- 295.64647986 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.88093833 meV/A -Kong-Liu effective sample size = 23.693091698983693 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 90 -Minimization step, force computed: 50 -Step too large (scalar = 0.9596411090234213 | kl_ratio = 0.8649705592783924), reducing to 0.04444444446326501 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.52534317 meV -Anharmonic contribution to free energy = -308448.75846799 +- 1.57114246 meV -Free energy = -308369.23312482 +- 1.57114246 meV -FC gradient modulus = 12920.41399714 +- 298.35756630 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.89065269 meV/A -Kong-Liu effective sample size = 24.148885177256624 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 91 -Minimization step, force computed: 50 -Step too large (scalar = 0.9675229148904957 | kl_ratio = 0.8816103437702615), reducing to 0.03882579844977461 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.73326463 meV -Anharmonic contribution to free energy = -308449.02991702 +- 1.55864588 meV -Free energy = -308369.29665239 +- 1.55864588 meV -FC gradient modulus = 13026.15865305 +- 300.71970530 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.89906226 meV/A -Kong-Liu effective sample size = 24.550266893640543 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 92 -Minimization step, force computed: 50 -Step too large (scalar = 0.974391792325262 | kl_ratio = 0.8962637023152593), reducing to 0.03391745905404393 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.91442407 meV -Anharmonic contribution to free energy = -308449.26627103 +- 1.54768310 meV -Free energy = -308369.35184696 +- 1.54768310 meV -FC gradient modulus = 13118.35055820 +- 302.77832620 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.90635045 meV/A -Kong-Liu effective sample size = 24.90322452411642 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 93 -Minimization step, force computed: 50 -Good step found with 0.03391745905404393, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 79.91442407 meV -Anharmonic contribution to free energy = -308449.26627103 +- 1.54768310 meV -Free energy = -308369.35184696 +- 1.54768310 meV -FC gradient modulus = 13198.74702302 +- 304.57286038 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.91267305 meV/A -Kong-Liu effective sample size = 24.90322452411642 - - -The gw gradient satisfy the convergence condition. -KL: 24.90322452411642 KL/N: 0.4980644904823284 KL RAT: 0.5 - According to your input criteria - you are out of the statistical sampling. -Check the stopping criteria: Running = False -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - -Restoring the last good dynamical matrix. -Updating the importance sampling... - - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 93 steps - -Free energy = -308369.35184696 +- 1.54768310 meV -FC gradient modulus = 13198.74702302 +- 304.57286038 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.91267305 meV/A -Kong-Liu effective sample size = 24.90322452411642 - -Total force on the centroids [eV/A]: - 0) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - 1) -0.000000 -0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - -0.05949984 0.00000000 -0.00000000 0.02025963 0.00000000 0.00000000 - -0.00000000 -0.05949984 0.00000000 +- 0.00000000 0.02025963 0.00000000 - -0.00000000 0.00000000 -0.05949984 0.00000000 0.00000000 0.02025963 - - Ab initio average stress [GPa]: - -0.26474779 -0.00000000 -0.00000000 - 0.00000000 -0.26474779 -0.00000000 - -0.00000000 -0.00000000 -0.26474779 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds -Average of 0.3272523880004883 s per call -Subroutine report: - Function: GoParallel - N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.32612764835357666 s per call - Subroutine report: - Function: compute - N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.3260691165924072 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 2 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.3262568712234497 s per call - - -Function: minimization_step -N = 93 calls took: 0 hours; 0 minutes; 3.30 seconds -Average of 0.03547732804411201 s per call -Subroutine report: - Function: get_fourier_gradient - N = 93 calls took: 0 hours; 0 minutes; 0.19 seconds - Average of 0.0020199847477738574 s per call - Subroutine report: - Function: GoParallel - N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.0008597476508027764 s per call - Subroutine report: - Function: compute - N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.0008147788304154591 s per call - Subroutine report: - - - Function: fourier gradient upsilon q - N = 93 calls took: 0 hours; 0 minutes; 0.05 seconds - Average of 0.0005139689291677167 s per call - - Function: fourier gradient Y * u - N = 93 calls took: 0 hours; 0 minutes; 0.05 seconds - Average of 0.0004989049767935148 s per call - - Function: fourier gradient julia - N = 93 calls took: 0 hours; 0 minutes; 0.09 seconds - Average of 0.0009624394037390268 s per call - - - Function: SymmetrizeFCQ - N = 93 calls took: 0 hours; 0 minutes; 0.90 seconds - Average of 0.009680781313168105 s per call - - Function: Symmetrize - N = 93 calls took: 0 hours; 0 minutes; 0.90 seconds - Average of 0.009720243433470367 s per call - - Function: update - N = 93 calls took: 0 hours; 0 minutes; 1.17 seconds - Average of 0.01262080797585108 s per call - Subroutine report: - Function: update_weights_fourier - N = 93 calls took: 0 hours; 0 minutes; 1.17 seconds - Average of 0.01257582890090122 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 93 calls took: 0 hours; 0 minutes; 0.76 seconds - Average of 0.008174468112248246 s per call - Subroutine report: - Function: DyagDinQ - N = 744 calls took: 0 hours; 0 minutes; 0.16 seconds - Average of 0.00021266104072652838 s per call - - Function: Manipulate polarization vectors - N = 744 calls took: 0 hours; 0 minutes; 0.13 seconds - Average of 0.00017434070187230264 s per call - - - Function: Time to get SSCHA energy and forces - N = 93 calls took: 0 hours; 0 minutes; 0.10 seconds - Average of 0.0011204622125112883 s per call - - Function: get upsilon fourier - N = 93 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.0008682435558688256 s per call - - Function: get uYu - N = 93 calls took: 0 hours; 0 minutes; 0.17 seconds - Average of 0.0018578780594692436 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = -0.0595 +- 0.0203 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.3958 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0836935185e+02 eV - Gibbs Free energy = -3.0836935185e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.395841778473766 -[CELL] unit_cell: -Cell([[2.723342240665962, 2.723342240665962, -4.322490091947834e-34], [2.723342240665962, 2.7068533300035466e-18, 2.723342240665962], [3.609137773338063e-18, 2.723342240665962, 2.723342240665962]]) -[CELL] CURRENT STRAIN: -[[ 2.89534103e-03 -4.42102081e-18 5.75011834e-18] - [-5.08556957e-18 2.89534103e-03 5.08556957e-18] - [-5.08556957e-18 5.08556957e-18 2.89534103e-03]] -[CELL] NEW STRESS: -[[-3.71368768e-04 3.88855050e-20 -1.16656515e-19] - [-3.88855050e-20 -3.71368768e-04 3.88855050e-20] - [-3.88855050e-20 3.88855050e-20 -3.71368768e-04]] -GRAD MAT: -[[ 1.50451892e-02 -1.64168381e-18 4.81234409e-18] - [ 1.49906828e-18 1.50451892e-02 -1.49906828e-18] - [ 1.49906828e-18 -1.49906828e-18 1.50451892e-02]] - -[CELL] y0 = 0.14141063624887285 | y1 = -0.009799396237494347 -[CELL] grad = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 - 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 - 1.50451892e-02] -[CELL] lastgrad = [-2.17110292e-01 -5.07863670e-17 -4.88774550e-17 -7.57023225e-17 - -2.17110292e-01 9.54455980e-19 2.39614995e-17 -2.39614995e-17 - -2.17110292e-01] -[CELL] GRADIENT DOT DIRECTION = 0.935193478393189 -[CELL] New step: -[CELL] X_OLD = [ 2.89534103e-03 -4.42102081e-18 5.75011834e-18 -5.08556957e-18 - 2.89534103e-03 5.08556957e-18 -5.08556957e-18 5.08556957e-18 - 2.89534103e-03] | ALPHA = 0.012471560100349277 -[CELL] DIRECTION = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 - 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 - 1.50451892e-02] -[CELL] GRADIENT = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 - 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 - 1.50451892e-02] -[CELL] X_NEW = [ 2.70770405e-03 -4.40054645e-18 5.69010090e-18 -5.10426529e-18 - 2.70770405e-03 5.10426529e-18 -5.10426529e-18 5.10426529e-18 - 2.70770405e-03] -[CELL] Step number = 2 - -NEW STRAIN: -[[ 2.70770405e-03 -4.40054645e-18 5.69010090e-18] - [-5.10426529e-18 2.70770405e-03 5.10426529e-18] - [-5.10426529e-18 5.10426529e-18 2.70770405e-03]] -NEW VOLUME: -40.373172406770884 - - Currently estimated bulk modulus = 99.136 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72283272 2.72283272 0.00000000) - v2 [A] = ( 2.72283272 0.00000000 2.72283272) - v3 [A] = ( 0.00000000 2.72283272 2.72283272) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. -[BFFS USED] For structure with id=0 -[BFFS USED] For structure with id=1 -[BFFS USED] For structure with id=2 -[BFFS USED] For structure with id=3 -[BFFS USED] For structure with id=4 -[BFFS USED] For structure with id=5 -[BFFS USED] For structure with id=6 -[BFFS USED] For structure with id=7 -[BFFS USED] For structure with id=8 -[BFFS USED] For structure with id=9 -[BFFS USED] For structure with id=10 -[BFFS USED] For structure with id=11 -[BFFS USED] For structure with id=12 -[BFFS USED] For structure with id=13 -[BFFS USED] For structure with id=14 -[BFFS USED] For structure with id=15 -[BFFS USED] For structure with id=16 -[BFFS USED] For structure with id=17 -[BFFS USED] For structure with id=18 -[BFFS USED] For structure with id=19 -[BFFS USED] For structure with id=20 -[BFFS USED] For structure with id=21 -[BFFS USED] For structure with id=22 -[BFFS USED] For structure with id=23 -[BFFS USED] For structure with id=24 -[BFFS USED] For structure with id=25 -[BFFS USED] For structure with id=26 -[BFFS USED] For structure with id=27 -[BFFS USED] For structure with id=28 -[BFFS USED] For structure with id=29 -[BFFS USED] For structure with id=30 -[BFFS USED] For structure with id=31 -[BFFS USED] For structure with id=32 -[BFFS USED] For structure with id=33 -[BFFS USED] For structure with id=34 -[BFFS USED] For structure with id=35 -[BFFS USED] For structure with id=36 -[BFFS USED] For structure with id=37 -[BFFS USED] For structure with id=38 -[BFFS USED] For structure with id=39 -[BFFS USED] For structure with id=40 -[BFFS USED] For structure with id=41 -[BFFS USED] For structure with id=42 -[BFFS USED] For structure with id=43 -[BFFS USED] For structure with id=44 -[BFFS USED] For structure with id=45 -[BFFS USED] For structure with id=46 -[BFFS USED] For structure with id=47 -[BFFS USED] For structure with id=48 -[BFFS USED] For structure with id=49 -=============== SUMMARY AIIDA CALCULATIONS =============== - -Total structures included: 50 -Structures not included : 0 -Steps using OTF-ML model : 50 - -===================== END OF SUMMARY ===================== - - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 94 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 74.00679849 meV -Anharmonic contribution to free energy = -308439.92916277 +- 1.20852972 meV -Free energy = -308365.92236428 +- 1.20852972 meV -FC gradient modulus = 13846.33536607 +- 310.51878255 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.37202425 meV/A -Kong-Liu effective sample size = 46.32075694267749 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 95 -Minimization step, force computed: 50 -Good step found with 0.15000000000000002, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 74.00679849 meV -Anharmonic contribution to free energy = -308439.92916277 +- 1.20852972 meV -Free energy = -308365.92236428 +- 1.20852972 meV -FC gradient modulus = 11422.48334105 +- 267.26801062 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.28302890 meV/A -Kong-Liu effective sample size = 46.32075694267749 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 96 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 65.92441896 meV -Anharmonic contribution to free energy = -308429.74078228 +- 1.40842512 meV -Free energy = -308363.81636331 +- 1.40842512 meV -FC gradient modulus = 11422.48334105 +- 267.26801062 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.28302890 meV/A -Kong-Liu effective sample size = 34.9459103862496 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 97 -Minimization step, force computed: 50 -Step too large (scalar = 0.5185671645618921 | kl_ratio = 0.7544330596647113), reducing to 0.19655560456875001 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 67.00119973 meV -Anharmonic contribution to free energy = -308431.05762978 +- 1.37647909 meV -Free energy = -308364.05643005 +- 1.37647909 meV -FC gradient modulus = 8408.87200984 +- 219.73668185 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22451081 meV/A -Kong-Liu effective sample size = 36.55518939004113 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 98 -Minimization step, force computed: 50 -Step too large (scalar = 0.5420016319160825 | kl_ratio = 0.7891751301749802), reducing to 0.17170713638838586 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 67.92756883 meV -Anharmonic contribution to free energy = -308432.20195236 +- 1.35034221 meV -Free energy = -308364.27438353 +- 1.35034221 meV -FC gradient modulus = 8787.29642952 +- 225.20548477 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22700703 meV/A -Kong-Liu effective sample size = 37.94459031264566 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 99 -Minimization step, force computed: 50 -Step too large (scalar = 0.5625325282378661 | kl_ratio = 0.8191703421341442), reducing to 0.15000000000705774 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 68.72638781 meV -Anharmonic contribution to free energy = -308433.19675967 +- 1.32882128 meV -Free energy = -308364.47037186 +- 1.32882128 meV -FC gradient modulus = 9119.05892036 +- 230.13759241 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23061947 meV/A -Kong-Liu effective sample size = 39.138667185990535 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 100 -Minimization step, force computed: 50 -Step too large (scalar = 0.5805011444072077 | kl_ratio = 0.8449487825603782), reducing to 0.1310370697186655 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 69.41654228 meV -Anharmonic contribution to free energy = -308434.06193355 +- 1.31098400 meV -Free energy = -308364.64539127 +- 1.31098400 meV -FC gradient modulus = 9409.57213877 +- 234.55466854 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23475972 meV/A -Kong-Liu effective sample size = 40.16159215936871 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 101 -Minimization step, force computed: 50 -Step too large (scalar = 0.5962160350058028 | kl_ratio = 0.8670322941628344), reducing to 0.11447142426430995 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 70.01376948 meV -Anharmonic contribution to free energy = -308434.81465982 +- 1.29610567 meV -Free energy = -308364.80089034 +- 1.29610567 meV -FC gradient modulus = 9663.75486880 +- 238.49006835 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23906447 meV/A -Kong-Liu effective sample size = 41.036097581614406 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 102 -Minimization step, force computed: 50 -Step too large (scalar = 0.6099531173240186 | kl_ratio = 0.8859116363835997), reducing to 0.10000000000941031 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 70.53127720 meV -Anharmonic contribution to free energy = -308435.46979905 +- 1.28362227 meV -Free energy = -308364.93852185 +- 1.28362227 meV -FC gradient modulus = 9886.02205286 +- 241.98262527 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24331211 meV/A -Kong-Liu effective sample size = 41.78288673064152 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 103 -Minimization step, force computed: 50 -Good step found with 0.10000000000941031, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 70.53127720 meV -Anharmonic contribution to free energy = -308435.46979905 +- 1.28362227 meV -Free energy = -308364.93852185 +- 1.28362227 meV -FC gradient modulus = 10080.30311094 +- 245.07286347 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24737147 meV/A -Kong-Liu effective sample size = 41.78288673064152 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 104 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 65.63486973 meV -Anharmonic contribution to free energy = -308429.37972239 +- 1.42292339 meV -Free energy = -308363.74485266 +- 1.42292339 meV -FC gradient modulus = 10080.30311094 +- 245.07286347 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24737147 meV/A -Kong-Liu effective sample size = 34.44521947111946 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 105 -Minimization step, force computed: 50 -Step too large (scalar = 0.4525818850588065 | kl_ratio = 0.8243858231523056), reducing to 0.13103706972483098 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 66.27426460 meV -Anharmonic contribution to free energy = -308430.15944334 +- 1.40252898 meV -Free energy = -308363.88517874 +- 1.40252898 meV -FC gradient modulus = 8313.17004633 +- 218.58729330 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22269119 meV/A -Kong-Liu effective sample size = 35.41001281409925 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 106 -Minimization step, force computed: 50 -Step too large (scalar = 0.46469977136723006 | kl_ratio = 0.8474764571048959), reducing to 0.11447142426969599 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 66.82771284 meV -Anharmonic contribution to free energy = -308430.83838820 +- 1.38539775 meV -Free energy = -308364.01067536 +- 1.38539775 meV -FC gradient modulus = 8535.19837265 +- 221.72469715 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22386741 meV/A -Kong-Liu effective sample size = 36.24836496177069 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 107 -Minimization step, force computed: 50 -Step too large (scalar = 0.4753062244390673 | kl_ratio = 0.8675409431485718), reducing to 0.10000000001411545 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 67.30739214 meV -Anharmonic contribution to free energy = -308431.42978306 +- 1.37094948 meV -Free energy = -308364.12239092 +- 1.37094948 meV -FC gradient modulus = 8729.60545415 +- 224.52108259 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22542044 meV/A -Kong-Liu effective sample size = 36.97599035849552 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 108 -Minimization step, force computed: 50 -Step too large (scalar = 0.4845853217026519 | kl_ratio = 0.8849553789058606), reducing to 0.08735804648733098 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 67.72359349 meV -Anharmonic contribution to free energy = -308431.94507698 +- 1.35871828 meV -Free energy = -308364.22148349 +- 1.35871828 meV -FC gradient modulus = 8899.73469791 +- 227.00441120 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22715382 meV/A -Kong-Liu effective sample size = 37.60707570817453 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 109 -Minimization step, force computed: 50 -Good step found with 0.08735804648733098, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 67.72359349 meV -Anharmonic contribution to free energy = -308431.94507698 +- 1.35871828 meV -Free energy = -308364.22148349 +- 1.35871828 meV -FC gradient modulus = 9048.55679011 +- 229.20339982 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22894054 meV/A -Kong-Liu effective sample size = 37.60707570817453 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 110 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 63.74038037 meV -Anharmonic contribution to free energy = -308427.09066847 +- 1.49246813 meV -Free energy = -308363.35028811 +- 1.49246813 meV -FC gradient modulus = 9048.55679011 +- 229.20339982 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22894054 meV/A -Kong-Liu effective sample size = 31.563557978236748 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 111 -Minimization step, force computed: 50 -Step too large (scalar = 0.37508079769239555 | kl_ratio = 0.8392983869090328), reducing to 0.11447142427508204 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 64.25786948 meV -Anharmonic contribution to free energy = -308427.71046372 +- 1.47360357 meV -Free energy = -308363.45259424 +- 1.47360357 meV -FC gradient modulus = 7674.79785242 +- 210.06257617 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22193601 meV/A -Kong-Liu effective sample size = 32.33535398602545 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 112 -Minimization step, force computed: 50 -Step too large (scalar = 0.3835214591947601 | kl_ratio = 0.8598210144533206), reducing to 0.1000000000188206 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 64.70647445 meV -Anharmonic contribution to free energy = -308428.25048569 +- 1.45758467 meV -Free energy = -308363.54401125 +- 1.45758467 meV -FC gradient modulus = 7847.12114019 +- 212.32953525 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22132286 meV/A -Kong-Liu effective sample size = 33.0094085770546 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 113 -Minimization step, force computed: 50 -Step too large (scalar = 0.3909114167647833 | kl_ratio = 0.8777446253253733), reducing to 0.08735804649144131 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 65.09578128 meV -Anharmonic contribution to free energy = -308428.72114873 +- 1.44394533 meV -Free energy = -308363.62536745 +- 1.44394533 meV -FC gradient modulus = 7998.04041870 +- 214.34909894 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22118438 meV/A -Kong-Liu effective sample size = 33.59759842143758 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 114 -Minimization step, force computed: 50 -Step too large (scalar = 0.39737866071968775 | kl_ratio = 0.8933850289809846), reducing to 0.0763142828536454 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 65.43393583 meV -Anharmonic contribution to free energy = -308429.13147387 +- 1.43230165 meV -Free energy = -308363.69753804 +- 1.43230165 meV -FC gradient modulus = 8130.15020412 +- 216.14221001 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22135096 meV/A -Kong-Liu effective sample size = 34.11057097684625 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 115 -Minimization step, force computed: 50 -Good step found with 0.0763142828536454, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 65.43393583 meV -Anharmonic contribution to free energy = -308429.13147387 +- 1.43230165 meV -Free energy = -308363.69753804 +- 1.43230165 meV -FC gradient modulus = 8245.75060406 +- 217.72998440 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22170625 meV/A -Kong-Liu effective sample size = 34.11057097684625 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 116 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 62.16343702 meV -Anharmonic contribution to free energy = -308425.21460867 +- 1.55709168 meV -Free energy = -308363.05117165 +- 1.55709168 meV -FC gradient modulus = 8245.75060406 +- 217.72998440 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22170625 meV/A -Kong-Liu effective sample size = 29.19821458706225 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 117 -Minimization step, force computed: 50 -Step too large (scalar = 0.319033127095163 | kl_ratio = 0.8559872717135566), reducing to 0.10000000002352576 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 62.58654686 meV -Anharmonic contribution to free energy = -308425.71394938 +- 1.53999757 meV -Free energy = -308363.12740252 +- 1.53999757 meV -FC gradient modulus = 7163.20626744 +- 203.67634117 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22578104 meV/A -Kong-Liu effective sample size = 29.81870737154356 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 118 -Minimization step, force computed: 50 -Step too large (scalar = 0.3250908334270587 | kl_ratio = 0.8741779019701564), reducing to 0.08735804649555164 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 62.95378497 meV -Anharmonic contribution to free energy = -308426.14917154 +- 1.52536773 meV -Free energy = -308363.19538658 +- 1.52536773 meV -FC gradient modulus = 7298.95515866 +- 205.34427718 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22411903 meV/A -Kong-Liu effective sample size = 30.361603938882922 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 119 -Minimization step, force computed: 50 -Step too large (scalar = 0.33039445255715855 | kl_ratio = 0.8900936885369619), reducing to 0.0763142828572361 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 63.27281222 meV -Anharmonic contribution to free energy = -308426.52861835 +- 1.51282308 meV -Free energy = -308363.25580612 +- 1.51282308 meV -FC gradient modulus = 7417.83620348 +- 206.82875825 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22296606 meV/A -Kong-Liu effective sample size = 30.836283465096415 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 120 -Minimization step, force computed: 50 -Good step found with 0.0763142828572361, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 63.27281222 meV -Anharmonic contribution to free energy = -308426.52861835 +- 1.51282308 meV -Free energy = -308363.25580612 +- 1.51282308 meV -FC gradient modulus = 7521.90168276 +- 208.14590624 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22217707 meV/A -Kong-Liu effective sample size = 30.836283465096415 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 121 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 60.18667295 meV -Anharmonic contribution to free energy = -308422.90144690 +- 1.64514280 meV -Free energy = -308362.71477395 +- 1.64514280 meV -FC gradient modulus = 7521.90168276 +- 208.14590624 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22217707 meV/A -Kong-Liu effective sample size = 26.312430497175804 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 122 -Minimization step, force computed: 50 -Step too large (scalar = 0.26601890477707346 | kl_ratio = 0.8532944810602368), reducing to 0.1000000000282309 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 60.58572020 meV -Anharmonic contribution to free energy = -308423.36395542 +- 1.62732155 meV -Free energy = -308362.77823522 +- 1.62732155 meV -FC gradient modulus = 6547.65853456 +- 196.56403259 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23731287 meV/A -Kong-Liu effective sample size = 26.879932664876105 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 123 -Minimization step, force computed: 50 -Step too large (scalar = 0.27098603624692286 | kl_ratio = 0.8716981959029368), reducing to 0.08735804649966196 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 60.93212609 meV -Anharmonic contribution to free energy = -308423.76703534 +- 1.61199825 meV -Free energy = -308362.83490925 +- 1.61199825 meV -FC gradient modulus = 6669.68194009 +- 197.92630473 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23421148 meV/A -Kong-Liu effective sample size = 27.377234159926388 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 124 -Minimization step, force computed: 50 -Step too large (scalar = 0.27533610374810813 | kl_ratio = 0.8878253499944206), reducing to 0.0763142828608268 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 61.23309522 meV -Anharmonic contribution to free energy = -308424.11843412 +- 1.59880400 meV -Free energy = -308362.88533890 +- 1.59880400 meV -FC gradient modulus = 6776.57285239 +- 199.14192938 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.23181136 meV/A -Kong-Liu effective sample size = 27.812681619985323 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 125 -Minimization step, force computed: 50 -Good step found with 0.0763142828608268, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 61.23309522 meV -Anharmonic contribution to free energy = -308424.11843412 +- 1.59880400 meV -Free energy = -308362.88533890 +- 1.59880400 meV -FC gradient modulus = 6870.16682546 +- 200.22288295 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22994052 meV/A -Kong-Liu effective sample size = 27.812681619985323 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 126 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 58.32032669 meV -Anharmonic contribution to free energy = -308420.75247121 +- 1.73581984 meV -Free energy = -308362.43214452 +- 1.73581984 meV -FC gradient modulus = 6870.16682546 +- 200.22288295 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.22994052 meV/A -Kong-Liu effective sample size = 23.66977053438384 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 127 -Minimization step, force computed: 50 -Step too large (scalar = 0.22240876907354018 | kl_ratio = 0.8510423718860494), reducing to 0.10000000003293603 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 58.69676058 meV -Anharmonic contribution to free energy = -308421.18191561 +- 1.71765362 meV -Free energy = -308362.48515503 +- 1.71765362 meV -FC gradient modulus = 5993.53225344 +- 190.78000686 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.25557256 meV/A -Kong-Liu effective sample size = 24.187106438106223 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 128 -Minimization step, force computed: 50 -Step too large (scalar = 0.22648777637025558 | kl_ratio = 0.8696430919025846), reducing to 0.08735804650377227 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 59.02358509 meV -Anharmonic contribution to free energy = -308421.55611144 +- 1.70196484 meV -Free energy = -308362.53252635 +- 1.70196484 meV -FC gradient modulus = 6103.25255342 +- 191.87950672 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.25110569 meV/A -Kong-Liu effective sample size = 24.640947669391444 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 129 -Minimization step, force computed: 50 -Step too large (scalar = 0.23006066781087356 | kl_ratio = 0.8859608723124788), reducing to 0.0763142828644175 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 59.30757756 meV -Anharmonic contribution to free energy = -308421.88228087 +- 1.68840482 meV -Free energy = -308362.57470331 +- 1.68840482 meV -FC gradient modulus = 6199.38087530 +- 192.86360150 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24752233 meV/A -Kong-Liu effective sample size = 25.03874107922509 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 130 -Minimization step, force computed: 50 -Good step found with 0.0763142828644175, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 59.30757756 meV -Anharmonic contribution to free energy = -308421.88228087 +- 1.68840482 meV -Free energy = -308362.57470331 +- 1.68840482 meV -FC gradient modulus = 6283.56362438 +- 193.74084284 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24462501 meV/A -Kong-Liu effective sample size = 25.03874107922509 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 131 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 56.55739302 meV -Anharmonic contribution to free energy = -308418.75052510 +- 1.82704981 meV -Free energy = -308362.19313208 +- 1.82704981 meV -FC gradient modulus = 6283.56362438 +- 193.74084284 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.24462501 meV/A -Kong-Liu effective sample size = 21.258373540677443 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 132 -Minimization step, force computed: 50 -Step too large (scalar = 0.1864746286905306 | kl_ratio = 0.849019264723167), reducing to 0.10000000003764119 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 56.91263586 meV -Anharmonic contribution to free energy = -308419.15039150 +- 1.80893861 meV -Free energy = -308362.23775564 +- 1.80893861 meV -FC gradient modulus = 5494.23528413 +- 186.13268972 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.28027060 meV/A -Kong-Liu effective sample size = 21.728592689449034 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 133 -Minimization step, force computed: 50 -Step too large (scalar = 0.18983226586604754 | kl_ratio = 0.8677989288957294), reducing to 0.0873580465078826 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 57.22110668 meV -Anharmonic contribution to free energy = -308419.49873591 +- 1.79323460 meV -Free energy = -308362.27762923 +- 1.79323460 meV -FC gradient modulus = 5592.99607839 +- 187.00798407 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.27450000 meV/A -Kong-Liu effective sample size = 22.14151629563222 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 134 -Minimization step, force computed: 50 -Step too large (scalar = 0.1927735295055105 | kl_ratio = 0.8842903173755516), reducing to 0.07631428286800819 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 57.48918398 meV -Anharmonic contribution to free energy = -308419.80231408 +- 1.77961210 meV -Free energy = -308362.31313011 +- 1.77961210 meV -FC gradient modulus = 5679.52738207 +- 187.79425313 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.26978714 meV/A -Kong-Liu effective sample size = 22.503769685579332 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 135 -Minimization step, force computed: 50 -Step too large (scalar = 0.19534899174865383 | kl_ratio = 0.8987580331764743), reducing to 0.06666666669489756 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 57.72232101 meV -Anharmonic contribution to free energy = -308420.06696593 +- 1.76779001 meV -Free energy = -308362.34464492 +- 1.76779001 meV -FC gradient modulus = 5755.31034244 +- 188.49722367 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.26591016 meV/A -Kong-Liu effective sample size = 22.82132312079843 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 136 -Minimization step, force computed: 50 -Good step found with 0.06666666669489756, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 57.72232101 meV -Anharmonic contribution to free energy = -308420.06696593 +- 1.76779001 meV -Free energy = -308362.34464492 +- 1.76779001 meV -FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A -Kong-Liu effective sample size = 22.82132312079843 - - -The gw gradient satisfy the convergence condition. -KL: 22.82132312079843 KL/N: 0.45642646241596857 KL RAT: 0.5 - According to your input criteria - you are out of the statistical sampling. -Check the stopping criteria: Running = False -ROOT NAME: ./minim_t0 -SAVE NAME: ./minim_t0 -FNAME NAME: None - -Restoring the last good dynamical matrix. -Updating the importance sampling... - - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 136 steps - -Free energy = -308362.34464492 +- 1.76779001 meV -FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A -Kong-Liu effective sample size = 22.82132312079843 - -Total force on the centroids [eV/A]: - 0) -0.000000 0.000000 0.000000 +- -0.000000 0.000000 0.000000 - 1) 0.000000 -0.000000 0.000000 +- 0.000000 -0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - 0.09021141 0.00000000 0.00000000 0.01405083 0.00000000 0.00000000 - 0.00000000 0.09021141 -0.00000000 +- 0.00000000 0.01405083 0.00000000 - -0.00000000 -0.00000000 0.09021141 0.00000000 0.00000000 0.01405083 - - Ab initio average stress [GPa]: - -0.15675322 -0.00000000 -0.00000000 - -0.00000000 -0.15675322 0.00000000 - -0.00000000 -0.00000000 -0.15675322 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 3 calls took: 0 hours; 0 minutes; 0.66 seconds -Average of 0.21869913736979166 s per call -Subroutine report: - Function: GoParallel - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21760932604471842 s per call - Subroutine report: - Function: compute - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21755274136861166 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21772448221842447 s per call - - -Function: minimization_step -N = 136 calls took: 0 hours; 0 minutes; 4.82 seconds -Average of 0.03541784426745247 s per call -Subroutine report: - Function: get_fourier_gradient - N = 136 calls took: 0 hours; 0 minutes; 0.29 seconds - Average of 0.00213162338032442 s per call - Subroutine report: - Function: GoParallel - N = 136 calls took: 0 hours; 0 minutes; 0.14 seconds - Average of 0.0009944105849546544 s per call - Subroutine report: - Function: compute - N = 136 calls took: 0 hours; 0 minutes; 0.13 seconds - Average of 0.0009495317935943604 s per call - Subroutine report: - - - Function: fourier gradient upsilon q - N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.0005079016965978286 s per call - - Function: fourier gradient Y * u - N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.0004844542811898624 s per call - - Function: fourier gradient julia - N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds - Average of 0.0010951547061695771 s per call - - - Function: SymmetrizeFCQ - N = 136 calls took: 0 hours; 0 minutes; 1.31 seconds - Average of 0.009660698035184075 s per call - - Function: Symmetrize - N = 136 calls took: 0 hours; 0 minutes; 1.32 seconds - Average of 0.009690807146184584 s per call - - Function: update - N = 136 calls took: 0 hours; 0 minutes; 1.70 seconds - Average of 0.012504090281093823 s per call - Subroutine report: - Function: update_weights_fourier - N = 136 calls took: 0 hours; 0 minutes; 1.69 seconds - Average of 0.012458666282541612 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 136 calls took: 0 hours; 0 minutes; 1.11 seconds - Average of 0.008144212119719562 s per call - Subroutine report: - Function: DyagDinQ - N = 1088 calls took: 0 hours; 0 minutes; 0.23 seconds - Average of 0.00021121716674636393 s per call - - Function: Manipulate polarization vectors - N = 1088 calls took: 0 hours; 0 minutes; 0.19 seconds - Average of 0.00017375148394528558 s per call - - - Function: Time to get SSCHA energy and forces - N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds - Average of 0.0011188352809232823 s per call - - Function: get upsilon fourier - N = 136 calls took: 0 hours; 0 minutes; 0.12 seconds - Average of 0.0008731326636146096 s per call - - Function: get uYu - N = 136 calls took: 0 hours; 0 minutes; 0.24 seconds - Average of 0.00176697618821088 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = 0.0902 +- 0.0141 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.3732 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0836234464e+02 eV - Gibbs Free energy = -3.0836234464e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.373172406770884 -[CELL] unit_cell: -Cell([[2.7228327161963652, 2.7228327161963652, 1.5195328858278707e-34], [2.7228327161963652, 1.5195328858278707e-34, 2.7228327161963652], [3.501759329709108e-18, 2.7228327161963652, 2.7228327161963652]]) -[CELL] CURRENT STRAIN: -[[ 2.70770405e-03 5.78492681e-18 -4.49537236e-18] - [ 5.14014958e-18 2.70770405e-03 -5.14014958e-18] - [ 5.14014958e-18 -5.14014958e-18 2.70770405e-03]] -[CELL] NEW STRESS: -[[ 5.63055310e-04 0.00000000e+00 3.88855050e-20] - [ 3.88855050e-20 5.63055310e-04 -3.88855050e-20] - [-1.16656515e-19 -7.77710099e-20 5.63055310e-04]] -GRAD MAT: -[[-2.27938815e-02 -1.31504860e-19 -1.47199182e-18] - [-1.69102968e-18 -2.27938815e-02 1.69102968e-18] - [ 4.60569874e-18 3.26521178e-18 -2.27938815e-02]] - -[CELL] y0 = 0.000679073152958703 | y1 = -0.0010288147802553307 -[CELL] grad = [-2.27938815e-02 -1.31504860e-19 -1.47199182e-18 -1.69102968e-18 - -2.27938815e-02 1.69102968e-18 4.60569874e-18 3.26521178e-18 - -2.27938815e-02] -[CELL] lastgrad = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 - 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 - 1.50451892e-02] -[CELL] GRADIENT DOT DIRECTION = 0.3976099015353843 -[CELL] Step not good: -[CELL] X_START = [ 2.89534103e-03 -4.42102081e-18 5.75011834e-18 -5.08556957e-18 - 2.89534103e-03 5.08556957e-18 -5.08556957e-18 5.08556957e-18 - 2.89534103e-03] | ALPHA = 0.0062357800501746385 -[CELL] DIRECTION = [ 1.50451892e-02 -1.64168381e-18 4.81234409e-18 1.49906828e-18 - 1.50451892e-02 -1.49906828e-18 1.49906828e-18 -1.49906828e-18 - 1.50451892e-02] -[CELL] GRADIENT = [-2.27938815e-02 -1.31504860e-19 -1.47199182e-18 -1.69102968e-18 - -2.27938815e-02 1.69102968e-18 4.60569874e-18 3.26521178e-18 - -2.27938815e-02] -[CELL] X_NEW = [ 2.80152254e-03 -4.41078363e-18 5.72010962e-18 -5.09491743e-18 - 2.80152254e-03 5.09491743e-18 -5.09491743e-18 5.09491743e-18 - 2.80152254e-03] -[CELL] Step number = 3 - -NEW STRAIN: -[[ 2.80152254e-03 -4.41078363e-18 5.72010962e-18] - [-5.09491743e-18 2.80152254e-03 5.09491743e-18] - [-5.09491743e-18 5.09491743e-18 2.80152254e-03]] -NEW VOLUME: -40.384506032190046 - - Currently estimated bulk modulus = 106.066 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72308748 2.72308748 -0.00000000) - v2 [A] = ( 2.72308748 -0.00000000 2.72308748) - v3 [A] = ( 0.00000000 2.72308748 2.72308748) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 136 steps - -Free energy = -308362.34464492 +- 1.76779001 meV -FC gradient modulus = 5821.65568155 +- 189.12335459 bohr^2 -Struct gradient modulus = 0.00000000 +- 1.26269994 meV/A -Kong-Liu effective sample size = 22.82132312079843 - -Total force on the centroids [eV/A]: - 0) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - 1) 0.000000 -0.000000 0.000000 +- -0.000000 0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - 0.09021141 0.00000000 0.00000000 0.01405083 0.00000000 0.00000000 - 0.00000000 0.09021141 -0.00000000 +- 0.00000000 0.01405083 0.00000000 - -0.00000000 -0.00000000 0.09021141 0.00000000 0.00000000 0.01405083 - - Ab initio average stress [GPa]: - -0.15675322 -0.00000000 -0.00000000 - -0.00000000 -0.15675322 0.00000000 - -0.00000000 -0.00000000 -0.15675322 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 3 calls took: 0 hours; 0 minutes; 0.66 seconds -Average of 0.21869913736979166 s per call -Subroutine report: - Function: GoParallel - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21760932604471842 s per call - Subroutine report: - Function: compute - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21755274136861166 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 3 calls took: 0 hours; 0 minutes; 0.65 seconds - Average of 0.21772448221842447 s per call - - -Function: minimization_step -N = 136 calls took: 0 hours; 0 minutes; 4.82 seconds -Average of 0.03541784426745247 s per call -Subroutine report: - Function: get_fourier_gradient - N = 136 calls took: 0 hours; 0 minutes; 0.29 seconds - Average of 0.00213162338032442 s per call - Subroutine report: - Function: GoParallel - N = 136 calls took: 0 hours; 0 minutes; 0.14 seconds - Average of 0.0009944105849546544 s per call - Subroutine report: - Function: compute - N = 136 calls took: 0 hours; 0 minutes; 0.13 seconds - Average of 0.0009495317935943604 s per call - Subroutine report: - - - Function: fourier gradient upsilon q - N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.0005079016965978286 s per call - - Function: fourier gradient Y * u - N = 136 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.0004844542811898624 s per call - - Function: fourier gradient julia - N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds - Average of 0.0010951547061695771 s per call - - - Function: SymmetrizeFCQ - N = 136 calls took: 0 hours; 0 minutes; 1.31 seconds - Average of 0.009660698035184075 s per call - - Function: Symmetrize - N = 136 calls took: 0 hours; 0 minutes; 1.32 seconds - Average of 0.009690807146184584 s per call - - Function: update - N = 136 calls took: 0 hours; 0 minutes; 1.70 seconds - Average of 0.012504090281093823 s per call - Subroutine report: - Function: update_weights_fourier - N = 136 calls took: 0 hours; 0 minutes; 1.69 seconds - Average of 0.012458666282541612 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 136 calls took: 0 hours; 0 minutes; 1.11 seconds - Average of 0.008144212119719562 s per call - Subroutine report: - Function: DyagDinQ - N = 1088 calls took: 0 hours; 0 minutes; 0.23 seconds - Average of 0.00021121716674636393 s per call - - Function: Manipulate polarization vectors - N = 1088 calls took: 0 hours; 0 minutes; 0.19 seconds - Average of 0.00017375148394528558 s per call - - - Function: Time to get SSCHA energy and forces - N = 136 calls took: 0 hours; 0 minutes; 0.15 seconds - Average of 0.0011188352809232823 s per call - - Function: get upsilon fourier - N = 136 calls took: 0 hours; 0 minutes; 0.12 seconds - Average of 0.0008731326636146096 s per call - - Function: get uYu - N = 136 calls took: 0 hours; 0 minutes; 0.24 seconds - Average of 0.00176697618821088 s per call - - - - - - END OF TIMER REPORT -===================== - diff --git a/Examples/sscha_and_aiida/log3 b/Examples/sscha_and_aiida/log3 deleted file mode 100644 index 64bb1567..00000000 --- a/Examples/sscha_and_aiida/log3 +++ /dev/null @@ -1,1273 +0,0 @@ -Number of symmetry inequivalent displacements: 1 -Force computed shape: 50 -Computing configuration 1 out of 50 (nat = 16) -Computing configuration 2 out of 50 (nat = 16) -Computing configuration 3 out of 50 (nat = 16) -Computing configuration 4 out of 50 (nat = 16) -Computing configuration 5 out of 50 (nat = 16) -Computing configuration 6 out of 50 (nat = 16) -Computing configuration 7 out of 50 (nat = 16) -Computing configuration 8 out of 50 (nat = 16) -Computing configuration 9 out of 50 (nat = 16) -Computing configuration 10 out of 50 (nat = 16) -Computing configuration 11 out of 50 (nat = 16) -Computing configuration 12 out of 50 (nat = 16) -Computing configuration 13 out of 50 (nat = 16) -Computing configuration 14 out of 50 (nat = 16) -Computing configuration 15 out of 50 (nat = 16) -Computing configuration 16 out of 50 (nat = 16) -Computing configuration 17 out of 50 (nat = 16) -Computing configuration 18 out of 50 (nat = 16) -Computing configuration 19 out of 50 (nat = 16) -Computing configuration 20 out of 50 (nat = 16) -Computing configuration 21 out of 50 (nat = 16) -Computing configuration 22 out of 50 (nat = 16) -Computing configuration 23 out of 50 (nat = 16) -Computing configuration 24 out of 50 (nat = 16) -Computing configuration 25 out of 50 (nat = 16) -Computing configuration 26 out of 50 (nat = 16) -Computing configuration 27 out of 50 (nat = 16) -Computing configuration 28 out of 50 (nat = 16) -Computing configuration 29 out of 50 (nat = 16) -Computing configuration 30 out of 50 (nat = 16) -Computing configuration 31 out of 50 (nat = 16) -Computing configuration 32 out of 50 (nat = 16) -Computing configuration 33 out of 50 (nat = 16) -Computing configuration 34 out of 50 (nat = 16) -Computing configuration 35 out of 50 (nat = 16) -Computing configuration 36 out of 50 (nat = 16) -Computing configuration 37 out of 50 (nat = 16) -Computing configuration 38 out of 50 (nat = 16) -Computing configuration 39 out of 50 (nat = 16) -Computing configuration 40 out of 50 (nat = 16) -Computing configuration 41 out of 50 (nat = 16) -Computing configuration 42 out of 50 (nat = 16) -Computing configuration 43 out of 50 (nat = 16) -Computing configuration 44 out of 50 (nat = 16) -Computing configuration 45 out of 50 (nat = 16) -Computing configuration 46 out of 50 (nat = 16) -Computing configuration 47 out of 50 (nat = 16) -Computing configuration 48 out of 50 (nat = 16) -Computing configuration 49 out of 50 (nat = 16) -Computing configuration 50 out of 50 (nat = 16) -Force computed shape: 50 - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 1 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.20417178 meV -Anharmonic contribution to free energy = -308491.83663769 +- 0.18821541 meV -Free energy = -308373.63246591 +- 0.18821541 meV -FC gradient modulus = 182.75557442 +- 90.14152625 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43309923 meV/A -Kong-Liu effective sample size = 49.99931246175452 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 2 -Minimization step, force computed: 50 -Good step found with 0.15000000000000002, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.20417178 meV -Anharmonic contribution to free energy = -308491.83663769 +- 0.18821541 meV -Free energy = -308373.63246591 +- 0.18821541 meV -FC gradient modulus = 152.95855939 +- 90.10531616 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43327265 meV/A -Kong-Liu effective sample size = 49.99931246175452 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 3 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.15072753 meV -Anharmonic contribution to free energy = -308491.78549128 +- 0.18790604 meV -Free energy = -308373.63476375 +- 0.18790604 meV -FC gradient modulus = 152.95855939 +- 90.10531616 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43327265 meV/A -Kong-Liu effective sample size = 49.996444413429145 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 4 -Minimization step, force computed: 50 -Good step found with 0.22500000000000003, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.15072753 meV -Anharmonic contribution to free energy = -308491.78549128 +- 0.18790604 meV -Free energy = -308373.63476375 +- 0.18790604 meV -FC gradient modulus = 115.77849587 +- 90.06940684 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43351103 meV/A -Kong-Liu effective sample size = 49.996444413429145 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 5 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.08761323 meV -Anharmonic contribution to free energy = -308491.72512389 +- 0.18759715 meV -Free energy = -308373.63751066 +- 0.18759715 meV -FC gradient modulus = 115.77849587 +- 90.06940684 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43351103 meV/A -Kong-Liu effective sample size = 49.99031730556114 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 6 -Minimization step, force computed: 50 -Good step found with 0.3375, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.08761323 meV -Anharmonic contribution to free energy = -308491.72512389 +- 0.18759715 meV -Free energy = -308373.63751066 +- 0.18759715 meV -FC gradient modulus = 74.01158891 +- 90.04266371 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43382080 meV/A -Kong-Liu effective sample size = 49.99031730556114 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 7 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.02315360 meV -Anharmonic contribution to free energy = -308491.66360756 +- 0.18733845 meV -Free energy = -308373.64045397 +- 0.18733845 meV -FC gradient modulus = 74.01158891 +- 90.04266371 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43382080 meV/A -Kong-Liu effective sample size = 49.98128027174389 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 8 -Minimization step, force computed: 50 -Good step found with 0.5062500000000001, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 118.02315360 meV -Anharmonic contribution to free energy = -308491.66360756 +- 0.18733845 meV -Free energy = -308373.64045397 +- 0.18733845 meV -FC gradient modulus = 34.77896702 +- 90.03402519 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43418490 meV/A -Kong-Liu effective sample size = 49.98128027174389 - - -The gc gradient satisfy the convergence condition. - -The gw gradient satisfy the convergence condition. -The system satisfy the convergence criteria according to the input. -Check the stopping criteria: Running = False -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 8 steps - -Free energy = -308373.64045397 +- 0.18733845 meV -FC gradient modulus = 34.77896702 +- 90.03402519 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.43418490 meV/A -Kong-Liu effective sample size = 49.98128027174389 - -Total force on the centroids [eV/A]: - 0) 0.000000 -0.000000 0.000000 +- 0.000000 0.000000 -0.000000 - 1) 0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - 0.81636588 0.00000000 -0.00000000 0.01024800 0.00000000 0.00000000 - 0.00000000 0.81636588 -0.00000000 +- 0.00000000 0.01024800 0.00000000 - -0.00000000 -0.00000000 0.81636588 0.00000000 0.00000000 0.01024800 - - Ab initio average stress [GPa]: - 0.66256699 0.00000000 -0.00000000 - 0.00000000 0.66256699 0.00000000 - -0.00000000 0.00000000 0.66256699 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds -Average of 0.8426022529602051 s per call -Subroutine report: - Function: GoParallel - N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.8413608074188232 s per call - Subroutine report: - Function: compute - N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.8412981033325195 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 1 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.8415110111236572 s per call - - -Function: minimization_step -N = 8 calls took: 0 hours; 0 minutes; 0.28 seconds -Average of 0.035197049379348755 s per call -Subroutine report: - Function: get_fourier_gradient - N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0017607808113098145 s per call - Subroutine report: - Function: GoParallel - N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds - Average of 0.0006138086318969727 s per call - Subroutine report: - Function: compute - N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds - Average of 0.0005699694156646729 s per call - Subroutine report: - - - Function: fourier gradient upsilon q - N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds - Average of 0.0005290806293487549 s per call - - Function: fourier gradient Y * u - N = 8 calls took: 0 hours; 0 minutes; 0.00 seconds - Average of 0.0004737973213195801 s per call - - Function: fourier gradient julia - N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0007123053073883057 s per call - - - Function: SymmetrizeFCQ - N = 8 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.009617865085601807 s per call - - Function: Symmetrize - N = 8 calls took: 0 hours; 0 minutes; 0.08 seconds - Average of 0.009717166423797607 s per call - - Function: update - N = 8 calls took: 0 hours; 0 minutes; 0.10 seconds - Average of 0.0125904381275177 s per call - Subroutine report: - Function: update_weights_fourier - N = 8 calls took: 0 hours; 0 minutes; 0.10 seconds - Average of 0.012545883655548096 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 8 calls took: 0 hours; 0 minutes; 0.07 seconds - Average of 0.008427917957305908 s per call - Subroutine report: - Function: DyagDinQ - N = 64 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0002085752785205841 s per call - - Function: Manipulate polarization vectors - N = 64 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.00017771124839782715 s per call - - - Function: Time to get SSCHA energy and forces - N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0011301040649414062 s per call - - Function: get upsilon fourier - N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0008168518543243408 s per call - - Function: get uYu - N = 8 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.001642853021621704 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = 0.8164 +- 0.0102 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.0470 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0837364045e+02 eV - Gibbs Free energy = -3.0837364045e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.04698463143717 -[CELL] unit_cell: -Cell([[2.71548, 2.71548, 0.0], [2.71548, 0.0, 2.71548], [0.0, 2.71548, 2.71548]]) -[CELL] CURRENT STRAIN: -[[ 0.00000000e+00 4.39618027e-18 -4.39618027e-18] - [ 4.39618027e-18 0.00000000e+00 -4.39618027e-18] - [ 4.39618027e-18 -4.39618027e-18 0.00000000e+00]] -[CELL] NEW STRESS: -[[ 5.09535512e-03 1.86650424e-18 -2.48867232e-18] - [ 1.24433616e-18 5.09535512e-03 -1.86650424e-18] - [-9.33252119e-19 -1.86650424e-18 5.09535512e-03]] -GRAD MAT: -[[-2.04053608e-01 -7.56449230e-17 1.00560878e-16] - [-5.07289675e-17 -2.04053608e-01 7.56449230e-17] - [ 3.64768768e-17 7.56449230e-17 -2.04053608e-01]] - -[CELL] New step: -[CELL] X_OLD = [ 0.00000000e+00 4.39618027e-18 -4.39618027e-18 4.39618027e-18 - 0.00000000e+00 -4.39618027e-18 4.39618027e-18 -4.39618027e-18 - 0.00000000e+00] | ALPHA = 0.013335807390121452 -[CELL] DIRECTION = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 - -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 - -2.04053608e-01] -[CELL] GRADIENT = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 - -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 - -2.04053608e-01] -[CELL] X_NEW = [ 2.72121961e-03 5.40496639e-18 -5.73724078e-18 5.07269201e-18 - 2.72121961e-03 -5.40496639e-18 3.90973167e-18 -5.40496639e-18 - 2.72121961e-03] -[CELL] Step number = 1 - -NEW STRAIN: -[[ 2.72121961e-03 5.40496639e-18 -5.73724078e-18] - [ 5.07269201e-18 2.72121961e-03 -5.40496639e-18] - [ 3.90973167e-18 -5.40496639e-18 2.72121961e-03]] -NEW VOLUME: -40.374805006719775 - - Currently estimated bulk modulus = 100.000 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72286942 2.72286942 -0.00000000) - v2 [A] = ( 2.72286942 -0.00000000 2.72286942) - v3 [A] = ( -0.00000000 2.72286942 2.72286942) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. -Force computed shape: 50 -Computing configuration 1 out of 50 (nat = 16) -Computing configuration 2 out of 50 (nat = 16) -Computing configuration 3 out of 50 (nat = 16) -Computing configuration 4 out of 50 (nat = 16) -Computing configuration 5 out of 50 (nat = 16) -Computing configuration 6 out of 50 (nat = 16) -Computing configuration 7 out of 50 (nat = 16) -Computing configuration 8 out of 50 (nat = 16) -Computing configuration 9 out of 50 (nat = 16) -Computing configuration 10 out of 50 (nat = 16) -Computing configuration 11 out of 50 (nat = 16) -Computing configuration 12 out of 50 (nat = 16) -Computing configuration 13 out of 50 (nat = 16) -Computing configuration 14 out of 50 (nat = 16) -Computing configuration 15 out of 50 (nat = 16) -Computing configuration 16 out of 50 (nat = 16) -Computing configuration 17 out of 50 (nat = 16) -Computing configuration 18 out of 50 (nat = 16) -Computing configuration 19 out of 50 (nat = 16) -Computing configuration 20 out of 50 (nat = 16) -Computing configuration 21 out of 50 (nat = 16) -Computing configuration 22 out of 50 (nat = 16) -Computing configuration 23 out of 50 (nat = 16) -Computing configuration 24 out of 50 (nat = 16) -Computing configuration 25 out of 50 (nat = 16) -Computing configuration 26 out of 50 (nat = 16) -Computing configuration 27 out of 50 (nat = 16) -Computing configuration 28 out of 50 (nat = 16) -Computing configuration 29 out of 50 (nat = 16) -Computing configuration 30 out of 50 (nat = 16) -Computing configuration 31 out of 50 (nat = 16) -Computing configuration 32 out of 50 (nat = 16) -Computing configuration 33 out of 50 (nat = 16) -Computing configuration 34 out of 50 (nat = 16) -Computing configuration 35 out of 50 (nat = 16) -Computing configuration 36 out of 50 (nat = 16) -Computing configuration 37 out of 50 (nat = 16) -Computing configuration 38 out of 50 (nat = 16) -Computing configuration 39 out of 50 (nat = 16) -Computing configuration 40 out of 50 (nat = 16) -Computing configuration 41 out of 50 (nat = 16) -Computing configuration 42 out of 50 (nat = 16) -Computing configuration 43 out of 50 (nat = 16) -Computing configuration 44 out of 50 (nat = 16) -Computing configuration 45 out of 50 (nat = 16) -Computing configuration 46 out of 50 (nat = 16) -Computing configuration 47 out of 50 (nat = 16) -Computing configuration 48 out of 50 (nat = 16) -Computing configuration 49 out of 50 (nat = 16) -Computing configuration 50 out of 50 (nat = 16) -Force computed shape: 50 - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 9 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.95071445 meV -Anharmonic contribution to free energy = -308492.27277791 +- 0.12630427 meV -Free energy = -308374.32206346 +- 0.12630427 meV -FC gradient modulus = 571.33305580 +- 87.20487894 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.37164914 meV/A -Kong-Liu effective sample size = 49.98834525233436 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 10 -Minimization step, force computed: 50 -Good step found with 0.15000000000000002, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.95071445 meV -Anharmonic contribution to free energy = -308492.27277791 +- 0.12630427 meV -Free energy = -308374.32206346 +- 0.12630427 meV -FC gradient modulus = 483.77196318 +- 87.04634377 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.37099603 meV/A -Kong-Liu effective sample size = 49.98834525233436 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 11 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.85765758 meV -Anharmonic contribution to free energy = -308492.18364013 +- 0.12392259 meV -Free energy = -308374.32598255 +- 0.12392259 meV -FC gradient modulus = 483.77196318 +- 87.04634377 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.37099603 meV/A -Kong-Liu effective sample size = 49.9409735529959 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 12 -Minimization step, force computed: 50 -Good step found with 0.22500000000000003, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.85765758 meV -Anharmonic contribution to free energy = -308492.18364013 +- 0.12392259 meV -Free energy = -308374.32598255 +- 0.12392259 meV -FC gradient modulus = 372.90564876 +- 86.90757818 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.37035883 meV/A -Kong-Liu effective sample size = 49.9409735529959 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 13 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.74854581 meV -Anharmonic contribution to free energy = -308492.07814773 +- 0.12199468 meV -Free energy = -308374.32960193 +- 0.12199468 meV -FC gradient modulus = 372.90564876 +- 86.90757818 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.37035883 meV/A -Kong-Liu effective sample size = 49.84283113117479 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 14 -Minimization step, force computed: 50 -Good step found with 0.3375, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.74854581 meV -Anharmonic contribution to free energy = -308492.07814773 +- 0.12199468 meV -Free energy = -308374.32960193 +- 0.12199468 meV -FC gradient modulus = 245.66216705 +- 86.83577615 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36990406 meV/A -Kong-Liu effective sample size = 49.84283113117479 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 15 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.63910565 meV -Anharmonic contribution to free energy = -308491.97199157 +- 0.12094287 meV -Free energy = -308374.33288592 +- 0.12094287 meV -FC gradient modulus = 245.66216705 +- 86.83577615 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36990406 meV/A -Kong-Liu effective sample size = 49.70170289869779 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 16 -Minimization step, force computed: 50 -Good step found with 0.5062500000000001, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.63910565 meV -Anharmonic contribution to free energy = -308491.97199157 +- 0.12094287 meV -Free energy = -308374.33288592 +- 0.12094287 meV -FC gradient modulus = 122.19204085 +- 86.86061801 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36977497 meV/A -Kong-Liu effective sample size = 49.70170289869779 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 17 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55684460 meV -Anharmonic contribution to free energy = -308491.89335796 +- 0.12068592 meV -Free energy = -308374.33651336 +- 0.12068592 meV -FC gradient modulus = 122.19204085 +- 86.86061801 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36977497 meV/A -Kong-Liu effective sample size = 49.56774596722804 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 18 -Minimization step, force computed: 50 -Good step found with 0.7593750000000001, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55684460 meV -Anharmonic contribution to free energy = -308491.89335796 +- 0.12068592 meV -Free energy = -308374.33651336 +- 0.12068592 meV -FC gradient modulus = 34.71806260 +- 86.94538150 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36991785 meV/A -Kong-Liu effective sample size = 49.56774596722804 - - -The gc gradient satisfy the convergence condition. - -The gw gradient satisfy the convergence condition. -The system satisfy the convergence criteria according to the input. -Check the stopping criteria: Running = False -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 18 steps - -Free energy = -308374.33651336 +- 0.12068592 meV -FC gradient modulus = 34.71806260 +- 86.94538150 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.36991785 meV/A -Kong-Liu effective sample size = 49.56774596722804 - -Total force on the centroids [eV/A]: - 0) 0.000000 -0.000000 -0.000000 +- -0.000000 0.000000 -0.000000 - 1) -0.000000 0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - -0.07664727 0.00000000 0.00000000 0.01136236 0.00000000 0.00000000 - -0.00000000 -0.07664727 -0.00000000 +- 0.00000000 0.01136236 0.00000000 - -0.00000000 -0.00000000 -0.07664727 0.00000000 0.00000000 0.01136236 - - Ab initio average stress [GPa]: - -0.22722149 -0.00000000 -0.00000000 - -0.00000000 -0.22722149 0.00000000 - -0.00000000 0.00000000 -0.22722149 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds -Average of 0.4221266508102417 s per call -Subroutine report: - Function: GoParallel - N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.42097902297973633 s per call - Subroutine report: - Function: compute - N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.42092299461364746 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 2 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.42110109329223633 s per call - - -Function: minimization_step -N = 18 calls took: 0 hours; 0 minutes; 0.62 seconds -Average of 0.034615808063083224 s per call -Subroutine report: - Function: SymmetrizeFCQ - N = 18 calls took: 0 hours; 0 minutes; 0.17 seconds - Average of 0.009491642316182455 s per call - - Function: Symmetrize - N = 18 calls took: 0 hours; 0 minutes; 0.17 seconds - Average of 0.009512212541368272 s per call - - Function: update - N = 18 calls took: 0 hours; 0 minutes; 0.22 seconds - Average of 0.01243762175242106 s per call - Subroutine report: - Function: update_weights_fourier - N = 18 calls took: 0 hours; 0 minutes; 0.22 seconds - Average of 0.012397381994459365 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 18 calls took: 0 hours; 0 minutes; 0.15 seconds - Average of 0.00832959016164144 s per call - Subroutine report: - Function: DyagDinQ - N = 144 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.00020677347977956137 s per call - - Function: Manipulate polarization vectors - N = 144 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.00017636352115207247 s per call - - - Function: Time to get SSCHA energy and forces - N = 18 calls took: 0 hours; 0 minutes; 0.02 seconds - Average of 0.0010606580310397679 s per call - - Function: get upsilon fourier - N = 18 calls took: 0 hours; 0 minutes; 0.01 seconds - Average of 0.0008082522286309137 s per call - - Function: get uYu - N = 18 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.0016922023561265734 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = -0.0766 +- 0.0114 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.3748 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0837433651e+02 eV - Gibbs Free energy = -3.0837433651e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.374805006719775 -[CELL] unit_cell: -Cell([[2.7228694174377295, 2.7228694174377295, -4.060279995005321e-18], [2.7228694174377295, -9.022844433345156e-19, 2.7228694174377295], [-9.022844433345154e-19, 2.7228694174377295, 2.7228694174377295]]) -[CELL] CURRENT STRAIN: -[[ 2.72121961e-03 -2.90375764e-17 2.87053020e-17] - [-2.88714392e-17 2.72121961e-03 2.88714392e-17] - [-2.88714392e-17 2.88714392e-17 2.72121961e-03]] -[CELL] NEW STRESS: -[[-4.78394610e-04 0.00000000e+00 3.88855050e-20] - [-3.88855050e-20 -4.78394610e-04 -3.88855050e-20] - [-1.16656515e-19 -7.77710099e-20 -4.78394610e-04]] -GRAD MAT: -[[ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18] - [ 1.01661256e-18 1.93676497e-02 2.13192140e-18] - [ 4.16514652e-18 3.70618838e-18 1.93676497e-02]] - -[CELL] y0 = 0.12491362486531585 | y1 = -0.011856116393323065 -[CELL] grad = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 - 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 - 1.93676497e-02] -[CELL] lastgrad = [-2.04053608e-01 -7.56449230e-17 1.00560878e-16 -5.07289675e-17 - -2.04053608e-01 7.56449230e-17 3.64768768e-17 7.56449230e-17 - -2.04053608e-01] -[CELL] GRADIENT DOT DIRECTION = 0.9133133083077015 -[CELL] New step: -[CELL] X_OLD = [ 2.72121961e-03 -2.90375764e-17 2.87053020e-17 -2.88714392e-17 - 2.72121961e-03 2.88714392e-17 -2.88714392e-17 2.88714392e-17 - 2.72121961e-03] | ALPHA = 0.012179770366426118 -[CELL] DIRECTION = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 - 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 - 1.93676497e-02] -[CELL] GRADIENT = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 - 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 - 1.93676497e-02] -[CELL] X_NEW = [ 2.48532609e-03 -2.90307452e-17 2.87177232e-17 -2.88838213e-17 - 2.48532609e-03 2.88454728e-17 -2.89221697e-17 2.88262986e-17 - 2.48532609e-03] -[CELL] Step number = 2 - -NEW STRAIN: -[[ 2.48532609e-03 -2.90307452e-17 2.87177232e-17] - [-2.88838213e-17 2.48532609e-03 2.88454728e-17] - [-2.89221697e-17 2.88262986e-17 2.48532609e-03]] -NEW VOLUME: -40.34631678535821 - - Currently estimated bulk modulus = 99.188 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72222885 2.72222885 -0.00000000) - v2 [A] = ( 2.72222885 -0.00000000 2.72222885) - v3 [A] = ( -0.00000000 2.72222885 2.72222885) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. -Force computed shape: 50 -Computing configuration 1 out of 50 (nat = 16) -Computing configuration 2 out of 50 (nat = 16) -Computing configuration 3 out of 50 (nat = 16) -Computing configuration 4 out of 50 (nat = 16) -Computing configuration 5 out of 50 (nat = 16) -Computing configuration 6 out of 50 (nat = 16) -Computing configuration 7 out of 50 (nat = 16) -Computing configuration 8 out of 50 (nat = 16) -Computing configuration 9 out of 50 (nat = 16) -Computing configuration 10 out of 50 (nat = 16) -Computing configuration 11 out of 50 (nat = 16) -Computing configuration 12 out of 50 (nat = 16) -Computing configuration 13 out of 50 (nat = 16) -Computing configuration 14 out of 50 (nat = 16) -Computing configuration 15 out of 50 (nat = 16) -Computing configuration 16 out of 50 (nat = 16) -Computing configuration 17 out of 50 (nat = 16) -Computing configuration 18 out of 50 (nat = 16) -Computing configuration 19 out of 50 (nat = 16) -Computing configuration 20 out of 50 (nat = 16) -Computing configuration 21 out of 50 (nat = 16) -Computing configuration 22 out of 50 (nat = 16) -Computing configuration 23 out of 50 (nat = 16) -Computing configuration 24 out of 50 (nat = 16) -Computing configuration 25 out of 50 (nat = 16) -Computing configuration 26 out of 50 (nat = 16) -Computing configuration 27 out of 50 (nat = 16) -Computing configuration 28 out of 50 (nat = 16) -Computing configuration 29 out of 50 (nat = 16) -Computing configuration 30 out of 50 (nat = 16) -Computing configuration 31 out of 50 (nat = 16) -Computing configuration 32 out of 50 (nat = 16) -Computing configuration 33 out of 50 (nat = 16) -Computing configuration 34 out of 50 (nat = 16) -Computing configuration 35 out of 50 (nat = 16) -Computing configuration 36 out of 50 (nat = 16) -Computing configuration 37 out of 50 (nat = 16) -Computing configuration 38 out of 50 (nat = 16) -Computing configuration 39 out of 50 (nat = 16) -Computing configuration 40 out of 50 (nat = 16) -Computing configuration 41 out of 50 (nat = 16) -Computing configuration 42 out of 50 (nat = 16) -Computing configuration 43 out of 50 (nat = 16) -Computing configuration 44 out of 50 (nat = 16) -Computing configuration 45 out of 50 (nat = 16) -Computing configuration 46 out of 50 (nat = 16) -Computing configuration 47 out of 50 (nat = 16) -Computing configuration 48 out of 50 (nat = 16) -Computing configuration 49 out of 50 (nat = 16) -Computing configuration 50 out of 50 (nat = 16) -Force computed shape: 50 - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 19 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55589434 meV -Anharmonic contribution to free energy = -308491.91576859 +- 0.22448665 meV -Free energy = -308374.35987425 +- 0.22448665 meV -FC gradient modulus = 53.33262212 +- 85.36885845 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39036331 meV/A -Kong-Liu effective sample size = 49.9999692008167 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 20 -Minimization step, force computed: 50 -Good step found with 0.15000000000000002, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55589434 meV -Anharmonic contribution to free energy = -308491.91576859 +- 0.22448665 meV -Free energy = -308374.35987425 +- 0.22448665 meV -FC gradient modulus = 45.76513188 +- 85.37974344 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39041837 meV/A -Kong-Liu effective sample size = 49.9999692008167 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 21 -Minimization step, force computed: 50 - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55469315 meV -Anharmonic contribution to free energy = -308491.91442268 +- 0.22446124 meV -Free energy = -308374.35972953 +- 0.22446124 meV -FC gradient modulus = 45.76513188 +- 85.37974344 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39041837 meV/A -Kong-Liu effective sample size = 49.99983849028925 - - -The gw gradient satisfy the convergence condition. -Check the stopping criteria: Running = True - - # ---------------- NEW MINIMIZATION STEP -------------------- -Step ka = 22 -Minimization step, force computed: 50 -Good step found with 0.22500000000000003, try increment - - -Number of symmetries before the step: 24 -Harmonic contribution to free energy = 117.55469315 meV -Anharmonic contribution to free energy = -308491.91442268 +- 0.22446124 meV -Free energy = -308374.35972953 +- 0.22446124 meV -FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A -Kong-Liu effective sample size = 49.99983849028925 - - -The gc gradient satisfy the convergence condition. - -The gw gradient satisfy the convergence condition. -The system satisfy the convergence criteria according to the input. -Check the stopping criteria: Running = False -ROOT NAME: ./thermal_expansion/minim_t0 -SAVE NAME: ./thermal_expansion/minim_t0 -FNAME NAME: None - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 22 steps - -Free energy = -308374.35972953 +- 0.22446124 meV -FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A -Kong-Liu effective sample size = 49.99983849028925 - -Total force on the centroids [eV/A]: - 0) 0.000000 -0.000000 -0.000000 +- -0.000000 0.000000 -0.000000 - 1) -0.000000 0.000000 0.000000 +- -0.000000 0.000000 -0.000000 - - - ==== STRESS TENSOR [GPa] ==== - -0.00076058 0.00000000 0.00000000 0.00787638 0.00000000 0.00000000 - 0.00000000 -0.00076058 0.00000000 +- 0.00000000 0.00787638 0.00000000 - -0.00000000 0.00000000 -0.00076058 0.00000000 0.00000000 0.00787638 - - Ab initio average stress [GPa]: - -0.14847648 -0.00000000 0.00000000 - -0.00000000 -0.14847648 0.00000000 - 0.00000000 0.00000000 -0.14847648 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 3 calls took: 0 hours; 0 minutes; 0.85 seconds -Average of 0.281984806060791 s per call -Subroutine report: - Function: GoParallel - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.28085025151570636 s per call - Subroutine report: - Function: compute - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.2807942231496175 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.28096747398376465 s per call - - -Function: minimization_step -N = 22 calls took: 0 hours; 0 minutes; 0.76 seconds -Average of 0.034483660351146354 s per call -Subroutine report: - Function: SymmetrizeFCQ - N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds - Average of 0.00945215875452215 s per call - - Function: Symmetrize - N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds - Average of 0.009492018006064674 s per call - - Function: update - N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds - Average of 0.01239886067130349 s per call - Subroutine report: - Function: update_weights_fourier - N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds - Average of 0.01235907728021795 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 22 calls took: 0 hours; 0 minutes; 0.18 seconds - Average of 0.00831416520205411 s per call - Subroutine report: - Function: DyagDinQ - N = 176 calls took: 0 hours; 0 minutes; 0.04 seconds - Average of 0.00020634044300426137 s per call - - Function: Manipulate polarization vectors - N = 176 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.00017645413225347346 s per call - - - Function: Time to get SSCHA energy and forces - N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds - Average of 0.0010743899778886275 s per call - - Function: get upsilon fourier - N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds - Average of 0.000806494192643599 s per call - - Function: get uYu - N = 22 calls took: 0 hours; 0 minutes; 0.04 seconds - Average of 0.0016618641940030184 s per call - - - - - - END OF TIMER REPORT -===================== - - - ====================== - ENTHALPIC CONTRIBUTION - ====================== - - Current pressure P = -0.0008 +- 0.0079 GPa - Target pressure P = 0.0000 GPa - - For enthalpy we use the target pressure. - - P = 0.0000 GPa V = 40.3463 A^3 - - P V = 0.00000000e+00 eV - - Helmoltz Free energy = -3.0837435973e+02 eV - Gibbs Free energy = -3.0837435973e+02 eV <-- - Zero energy = 0.0000000000e+00 eV - - -[CELL] VOLUME: 40.34631678535821 -[CELL] unit_cell: -Cell([[2.722228853286519, 2.722228853286519, -2.6033592320191136e-19], [2.722228853286519, -1.0413436928075911e-19, 2.722228853286519], [-8.500049932564735e-19, 2.722228853286519, 2.722228853286519]]) -[CELL] CURRENT STRAIN: -[[ 2.48532609e-03 -6.36429382e-18 6.05127181e-18] - [-6.20778281e-18 2.48532609e-03 6.20778281e-18] - [-6.20778281e-18 6.20778281e-18 2.48532609e-03]] -[CELL] NEW STRESS: -[[-4.74714456e-06 3.03793008e-22 2.12655105e-21] - [ 6.07586015e-21 -4.74714456e-06 1.51896504e-21] - [-6.68344617e-21 6.37965316e-21 -4.74714456e-06]] -GRAD MAT: -[[ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20] - [-2.46936803e-19 1.92005812e-04 -6.02479815e-20] - [ 2.69133635e-19 -2.56846244e-19 1.92005812e-04]] - -[CELL] y0 = 0.0011253175631047963 | y1 = 1.1156103932368531e-05 -[CELL] grad = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 - 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 - 1.92005812e-04] -[CELL] lastgrad = [ 1.93676497e-02 -5.60863374e-19 -1.01982152e-18 1.01661256e-18 - 1.93676497e-02 2.13192140e-18 4.16514652e-18 3.70618838e-18 - 1.93676497e-02] -[CELL] GRADIENT DOT DIRECTION = 1.0100130047045919 -[CELL] New step: -[CELL] X_OLD = [ 2.48532609e-03 -6.36429382e-18 6.05127181e-18 -6.20778281e-18 - 2.48532609e-03 6.20778281e-18 -6.20778281e-18 6.20778281e-18 - 2.48532609e-03] | ALPHA = 0.012301726464405992 -[CELL] DIRECTION = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 - 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 - 1.92005812e-04] -[CELL] GRADIENT = [ 1.92005812e-04 -1.35063433e-20 -8.48527408e-20 -2.46936803e-19 - 1.92005812e-04 -6.02479815e-20 2.69133635e-19 -2.56846244e-19 - 1.92005812e-04] -[CELL] X_NEW = [ 2.48296409e-03 -6.36412767e-18 6.05231565e-18 -6.20474507e-18 - 2.48296409e-03 6.20852397e-18 -6.21109362e-18 6.21094247e-18 - 2.48296409e-03] -[CELL] Step number = 3 - -NEW STRAIN: -[[ 2.48296409e-03 -6.36412767e-18 6.05231565e-18] - [-6.20474507e-18 2.48296409e-03 6.20852397e-18] - [-6.21109362e-18 6.21094247e-18 2.48296409e-03]] -NEW VOLUME: -40.34603160044756 - - Currently estimated bulk modulus = 108.679 GPa - (Note: this is just indicative, do not use it for computing bulk modulus) - - - New unit cell: - v1 [A] = ( 2.72222244 2.72222244 -0.00000000) - v2 [A] = ( 2.72222244 0.00000000 2.72222244) - v3 [A] = ( -0.00000000 2.72222244 2.72222244) - -Check the symmetries in the new cell: -Symmetries of the bravais lattice: 48 -Symmetries of the crystal: 24 -Symmetries of the small group of q: 24 -Forcing the symmetries in the dynamical matrix. - - * * * * * * * * - * * - * RESULTS * - * * - * * * * * * * * - - -Minimization ended after 22 steps - -Free energy = -308374.35972953 +- 0.22446124 meV -FC gradient modulus = 36.09260911 +- 85.39466500 bohr^2 -Struct gradient modulus = 0.00000000 +- 0.39049349 meV/A -Kong-Liu effective sample size = 49.99983849028925 - -Total force on the centroids [eV/A]: - 0) 0.000000 0.000000 -0.000000 +- -0.000000 0.000000 0.000000 - 1) 0.000000 -0.000000 -0.000000 +- 0.000000 0.000000 0.000000 - - - ==== STRESS TENSOR [GPa] ==== - -0.00076058 0.00000000 0.00000000 0.00787638 0.00000000 0.00000000 - 0.00000000 -0.00076058 0.00000000 +- 0.00000000 0.00787638 0.00000000 - -0.00000000 0.00000000 -0.00076058 0.00000000 0.00000000 0.00787638 - - Ab initio average stress [GPa]: - -0.14847648 -0.00000000 0.00000000 - -0.00000000 -0.14847648 0.00000000 - 0.00000000 0.00000000 -0.14847648 - - - -======================== - TIMER REPORT -======================== - -Threshold for printing: 5 % - -Function: get_fourier_gradient -N = 3 calls took: 0 hours; 0 minutes; 0.85 seconds -Average of 0.281984806060791 s per call -Subroutine report: - Function: GoParallel - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.28085025151570636 s per call - Subroutine report: - Function: compute - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.2807942231496175 s per call - Subroutine report: - - - Function: fourier gradient julia - N = 3 calls took: 0 hours; 0 minutes; 0.84 seconds - Average of 0.28096747398376465 s per call - - -Function: minimization_step -N = 22 calls took: 0 hours; 0 minutes; 0.76 seconds -Average of 0.034483660351146354 s per call -Subroutine report: - Function: SymmetrizeFCQ - N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds - Average of 0.00945215875452215 s per call - - Function: Symmetrize - N = 22 calls took: 0 hours; 0 minutes; 0.21 seconds - Average of 0.009492018006064674 s per call - - Function: update - N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds - Average of 0.01239886067130349 s per call - Subroutine report: - Function: update_weights_fourier - N = 22 calls took: 0 hours; 0 minutes; 0.27 seconds - Average of 0.01235907728021795 s per call - Subroutine report: - Function: DiagonalizeSupercell - N = 22 calls took: 0 hours; 0 minutes; 0.18 seconds - Average of 0.00831416520205411 s per call - Subroutine report: - Function: DyagDinQ - N = 176 calls took: 0 hours; 0 minutes; 0.04 seconds - Average of 0.00020634044300426137 s per call - - Function: Manipulate polarization vectors - N = 176 calls took: 0 hours; 0 minutes; 0.03 seconds - Average of 0.00017645413225347346 s per call - - - Function: Time to get SSCHA energy and forces - N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds - Average of 0.0010743899778886275 s per call - - Function: get upsilon fourier - N = 22 calls took: 0 hours; 0 minutes; 0.02 seconds - Average of 0.000806494192643599 s per call - - Function: get uYu - N = 22 calls took: 0 hours; 0 minutes; 0.04 seconds - Average of 0.0016618641940030184 s per call - - - - - - END OF TIMER REPORT -===================== - diff --git a/Examples/sscha_and_aiida/submit.sh b/Examples/sscha_and_aiida/submit.sh index e0e6c32d..8b1b15ef 100755 --- a/Examples/sscha_and_aiida/submit.sh +++ b/Examples/sscha_and_aiida/submit.sh @@ -2,7 +2,7 @@ eval "$(conda shell.bash hook)" conda activate base -export OMP_NUM_THREADS=1 +export OMP_NUM_THREADS=4 python run_aiida_flare_sscha.py > log2 diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 976fe228..00bbaa7e 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -175,6 +175,7 @@ def compute_ensemble( # pylint: disable=arguments-renamed # self.stress_computed = copy(self.force_computed) self._clean_runs(dft_counts) + self.init() def _predict_with_model( self, From 511a47917152367f392a6105f7818a1c0c19d9bf Mon Sep 17 00:00:00 2001 From: bastonero Date: Wed, 8 May 2024 10:26:09 +0000 Subject: [PATCH 09/22] Flush the stdout to avoid waiting aiida workchains --- Modules/aiida_ensemble.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 00bbaa7e..82f6b2d7 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -4,6 +4,7 @@ from copy import copy, deepcopy import time +import sys from ase import units from cellconstructor.Structure import Structure @@ -126,6 +127,8 @@ def compute_ensemble( # pylint: disable=arguments-renamed **kwargs ) + sys.stdout.flush() + if group: group.add_nodes(workchains) @@ -169,6 +172,8 @@ def compute_ensemble( # pylint: disable=arguments-renamed if self.gp_model is not None: self._train_gp() self._write_model() + + sys.stdout.flush() # ================ FINALIZE ================ # # if self.has_stress: @@ -231,6 +236,8 @@ def _predict_with_model( self.stress_computed[index] = True self.force_computed[index] = True + + sys.stdout.flush() def _compute_properties(self, atoms: FLARE_Atoms) -> None: From e85e8101321ff8202c78de664560430be2d4d445 Mon Sep 17 00:00:00 2001 From: bastonero Date: Wed, 8 May 2024 15:56:18 +0000 Subject: [PATCH 10/22] Do not train hyperparameters if no DFT was done --- Examples/sscha_and_aiida/run_aiida_flare_sscha.py | 2 +- Examples/sscha_and_aiida/run_flare_sscha.py | 2 +- Modules/aiida_ensemble.py | 5 +++-- 3 files changed, 5 insertions(+), 4 deletions(-) diff --git a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py index c3a34341..c60af2d8 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py @@ -28,7 +28,7 @@ def main(): number_of_configurations = 50 batch_number = 1 check_time = 3 - max_iterations = 3 + max_iterations = 10 temperature = 0 pressure = 0 meaningful_factor = 0.5 diff --git a/Examples/sscha_and_aiida/run_flare_sscha.py b/Examples/sscha_and_aiida/run_flare_sscha.py index b1507b2f..277befb0 100644 --- a/Examples/sscha_and_aiida/run_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_flare_sscha.py @@ -18,7 +18,7 @@ def main(): # =========== GENERAL INPUTS =============== # np.random.seed(0) number_of_configurations = 50 - max_iterations = 3 + max_iterations = 10 temperature_i = 0 temperature_f = 0 temperature_step = 10 diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 82f6b2d7..28c49a6b 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -170,8 +170,9 @@ def compute_ensemble( # pylint: disable=arguments-renamed # ================ TRAIN SECTION ================ # if self.gp_model is not None: - self._train_gp() - self._write_model() + if dft_counts > 0: + self._train_gp() + self._write_model() sys.stdout.flush() From 8bcb77973674ea33754399e0f371bc538bc61b55 Mon Sep 17 00:00:00 2001 From: bastonero Date: Wed, 19 Jun 2024 14:31:50 +0000 Subject: [PATCH 11/22] Add `train_hyps` to the on-the-fly settings A variable controlling when the training is performed is added. This can give improvements if the hyperparameter training gets stucked into local minima due to few environments in the dataset. --- Modules/Ensemble.py | 8 ++++++++ Modules/aiida_ensemble.py | 3 ++- tests/aiida_ensemble/test_otf_flare.py | 2 ++ 3 files changed, 12 insertions(+), 1 deletion(-) diff --git a/Modules/Ensemble.py b/Modules/Ensemble.py index bfd935ad..d31be677 100644 --- a/Modules/Ensemble.py +++ b/Modules/Ensemble.py @@ -194,6 +194,7 @@ def __init__(self, dyn0, T0, supercell = None, **kwargs): self.checkpt_files = None self.write_model = None self.init_atoms = None + self.train_hyps = None # The frequencies and polarizations of the ensemble # In q space @@ -4239,6 +4240,7 @@ def set_otf( update_threshold: float | None = None, # other args build_mode="bayesian", + train_hyps: tuple = (100,120), ): """Set on-the-fly training. @@ -4299,6 +4301,12 @@ def set_otf( ] self.write_model = write_model + + if train_hyps[0] == "inf": + train_hyps[0] = np.inf + if train_hyps[1] == "inf": + train_hyps[1] = np.inf + self.train_hyps = train_hyps #------------------------------------------------------------------------------- diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 28c49a6b..a5ffecea 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -171,7 +171,8 @@ def compute_ensemble( # pylint: disable=arguments-renamed # ================ TRAIN SECTION ================ # if self.gp_model is not None: if dft_counts > 0: - self._train_gp() + if self.train_hyps[0] <= len(self.gp_model.training_data) <= self.train_hyps[1]: + self._train_gp() self._write_model() sys.stdout.flush() diff --git a/tests/aiida_ensemble/test_otf_flare.py b/tests/aiida_ensemble/test_otf_flare.py index 46075029..ed98bf33 100644 --- a/tests/aiida_ensemble/test_otf_flare.py +++ b/tests/aiida_ensemble/test_otf_flare.py @@ -74,6 +74,7 @@ def test_no_otf(generate_ensemble): assert ensemble.checkpt_files is None assert ensemble.write_model is None assert ensemble.init_atoms is None + assert ensemble.train_hyps is None def test_set_otf(generate_ensemble): @@ -83,6 +84,7 @@ def test_set_otf(generate_ensemble): ensemble.set_otf(flare_calc, max_atoms_added=-1) assert ensemble.gp_model is not None + assert ensemble.train_hyps == (100,120) def test_compute_properties(generate_ensemble): From e1edeb7c5bfe9d90b2e783bcf50e3de616ecca7f Mon Sep 17 00:00:00 2001 From: bastonero Date: Thu, 20 Jun 2024 12:18:18 +0200 Subject: [PATCH 12/22] Trying to see if we fix the stress issue --- Modules/aiida_ensemble.py | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index a5ffecea..e33a56b4 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -25,6 +25,7 @@ try: from flare.atoms import FLARE_Atoms + from flare.io.output import compute_mae from flare.learners.utils import get_env_indices, is_std_in_bound except ImportError: pass @@ -317,6 +318,19 @@ def _update_gp( self.output.write_wall_time(tic, task='Env Selection') + # compute mae and write to output + e_mae, e_mav, f_mae, f_mav, s_mae, s_mav = compute_mae( + atoms, + self.output.basename, + atoms.potential_energy, + atoms.forces, + atoms.stress, + dft_energy, + dft_frcs, + dft_stress, + self.force_only, + ) + if not std_in_bound: if not is_empty_model: stds = self.flare_calc.results.get('stds', np.zeros_like(dft_frcs)) @@ -339,7 +353,7 @@ def _update_gp( 'forces': dft_frcs, 'energy': dft_energy, 'free_energy': dft_energy, - 'stress': flare_stress, + 'stress': dft_stress, } atoms.calc = SinglePointCalculator(atoms, **results) From 5acc0d7e759d74537ec32e34758657e3a938d917 Mon Sep 17 00:00:00 2001 From: bastonero Date: Thu, 20 Jun 2024 18:12:07 +0000 Subject: [PATCH 13/22] Fix little bug --- Modules/aiida_ensemble.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index e33a56b4..034376aa 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -328,7 +328,7 @@ def _update_gp( dft_energy, dft_frcs, dft_stress, - self.force_only, + False, ) if not std_in_bound: From ed837e0a1d4ad39a7500554117352ebbd932b0f5 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Fri, 20 Dec 2024 00:51:03 +0100 Subject: [PATCH 14/22] Fix check on state of workchains to be `is_terminated` --- Modules/aiida_ensemble.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 034376aa..6dad6768 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -426,7 +426,7 @@ def get_running_workchains(workchains: list[WorkChainNode], success: list[bool]) wcs_left = copy(workchains) for workchain in workchains: - if workchain.is_finished: + if workchain.is_terminated: if workchain.is_failed: print(f'[FAILURE] for with PK={workchain.pk}') else: From 7a2111a98af7cdcfeed4025023149457d652572a Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Wed, 21 Jan 2026 11:59:51 +0000 Subject: [PATCH 15/22] Active-learning: new module and enhanced installation options --- Modules/Ensemble.py | 2 +- Modules/ml/__init__.py | 1 + Modules/ml/flare.py | 240 +++++++++++++++++++++++++++++++++++++++++ meson.build | 10 +- pyproject.toml | 24 +++++ 5 files changed, 275 insertions(+), 2 deletions(-) create mode 100644 Modules/ml/__init__.py create mode 100644 Modules/ml/flare.py diff --git a/Modules/Ensemble.py b/Modules/Ensemble.py index 6bcddfbc..02ee7840 100644 --- a/Modules/Ensemble.py +++ b/Modules/Ensemble.py @@ -4265,7 +4265,7 @@ def set_otf( update_threshold: float | None = None, # other args build_mode="bayesian", - train_hyps: tuple = (100,120), + train_hyps: tuple = (1,np.inf), ): """Set on-the-fly training. diff --git a/Modules/ml/__init__.py b/Modules/ml/__init__.py new file mode 100644 index 00000000..7e1dbfb5 --- /dev/null +++ b/Modules/ml/__init__.py @@ -0,0 +1 @@ +"""Module for machine learning functionalities.""" \ No newline at end of file diff --git a/Modules/ml/flare.py b/Modules/ml/flare.py new file mode 100644 index 00000000..61f8f957 --- /dev/null +++ b/Modules/ml/flare.py @@ -0,0 +1,240 @@ +"""Utility functions for setting up FLARE models.""" +from __future__ import annotations + +import sys, json, yaml +import numpy as np +from ase.symbols import symbols2numbers + + +def get_flare_calc(flare_config): + """Set up ASE flare calculator.""" + gp_name = flare_config.get("gp") + if gp_name == "GaussianProcess": + return get_gp_calc(flare_config) + elif gp_name == "SGP_Wrapper": + return get_sgp_calc(flare_config) + else: + raise NotImplementedError(f"{gp_name} is not implemented") + + +def get_gp_calc(flare_config): + """Return a FLARE_Calculator with gp from GaussianProcess.""" + from flare.bffs.gp import GaussianProcess + from flare.bffs.mgp import MappedGaussianProcess + from flare.bffs.gp.calculator import FLARE_Calculator + from flare.utils.parameter_helper import ParameterHelper + + gp_file = flare_config.get("file", None) + + # Load GP from file + if gp_file is not None: + with open(gp_file, "r") as f: + gp_dct = json.loads(f.readline()) + if gp_dct.get("class", None) == "FLARE_Calculator": + flare_calc = FLARE_Calculator.from_file(gp_file) + else: + gp, _ = GaussianProcess.from_file(gp_file) + flare_calc = FLARE_Calculator(gp) + return flare_calc + + # Create gaussian process model + kernels = flare_config.get("kernels") + hyps = flare_config.get("hyps", "random") + opt_algorithm = flare_config.get("opt_algorithm", "BFGS") + max_iterations = flare_config.get("max_iterations", 20) + bounds = flare_config.get("bounds", None) + + gp_parameters = flare_config.get("gp_parameters") + n_cpus = flare_config.get("n_cpus", 1) + use_mapping = flare_config.get("use_mapping", False) + + # set up GP hyperparameters + pm = ParameterHelper( + kernels=kernels, + random=True, + parameters=gp_parameters, + ) + hm = pm.as_dict() + if hyps == "random": + hyps = hm["hyps"] + + gp_model = GaussianProcess( + kernels=kernels, + component="mc", + hyps=hyps, + cutoffs=hm["cutoffs"], + hyps_mask=None, + hyp_labels=hm["hyp_labels"], + opt_algorithm=opt_algorithm, + maxiter=max_iterations, + parallel=n_cpus > 1, + per_atom_par=flare_config.get("per_atom_par", True), + n_cpus=n_cpus, + n_sample=flare_config.get("n_sample", 100), + output=None, + name=flare_config.get("name", "default_gp"), + energy_noise=flare_config.get("energy_noise", 0.01), + ) + + # create mapped gaussian process + if use_mapping: + grid_params = flare_config.get("grid_params") + var_map = flare_config.get("var_map", "pca") + unique_species = flare_config.get("unique_species") + coded_unique_species = symbols2numbers(unique_species) + mgp_model = MappedGaussianProcess( + grid_params=grid_params, + unique_species=coded_unique_species, + n_cpus=n_cpus, + var_map=var_map, + ) + else: + mgp_model = None + + flare_calc = FLARE_Calculator( + gp_model=gp_model, + mgp_model=mgp_model, + par=n_cpus > 1, + use_mapping=use_mapping, + ) + return flare_calc, kernels + + +def get_sgp_calc(flare_config): + """Return a SGP_Calculator with sgp from SparseGP.""" + from flare.bffs.sgp._C_flare import NormalizedDotProduct, SquaredExponential + from flare.bffs.sgp._C_flare import B2, B3, TwoBody, ThreeBody, FourBody + from flare.bffs.sgp import SGP_Wrapper + from flare.bffs.sgp.calculator import SGP_Calculator + + sgp_file = flare_config.get("file", None) + + # Load sparse GP from file + if sgp_file is not None: + with open(sgp_file, "r") as f: + gp_dct = json.loads(f.readline()) + if gp_dct.get("class", None) == "SGP_Calculator": + flare_calc, kernels = SGP_Calculator.from_file(sgp_file) + else: + sgp, kernels = SGP_Wrapper.from_file(sgp_file) + flare_calc = SGP_Calculator(sgp) + return flare_calc, kernels + + kernels = flare_config.get("kernels") + opt_algorithm = flare_config.get("opt_algorithm", "BFGS") + max_iterations = flare_config.get("max_iterations", 20) + bounds = flare_config.get("bounds", None) + use_mapping = flare_config.get("use_mapping", False) + + # Define kernels. + kernels = [] + for k in flare_config["kernels"]: + if k["name"] == "NormalizedDotProduct": + kernels.append(NormalizedDotProduct(k["sigma"], k["power"])) + elif k["name"] == "SquaredExponential": + kernels.append(SquaredExponential(k["sigma"], k["ls"])) + else: + raise NotImplementedError(f"{k['name']} kernel is not implemented") + + # Define descriptor calculators. + n_species = len(flare_config["species"]) + cutoff = flare_config["cutoff"] + descriptors = [] + for d in flare_config["descriptors"]: + if "cutoff_matrix" in d: # multiple cutoffs + assert np.allclose(np.array(d["cutoff_matrix"]).shape, (n_species, n_species)),\ + "cutoff_matrix needs to be of shape (n_species, n_species)" + + if d["name"] == "B2": + radial_hyps = [0.0, cutoff] + cutoff_hyps = [] + descriptor_settings = [n_species, d["nmax"], d["lmax"]] + if "cutoff_matrix" in d: # multiple cutoffs + desc_calc = B2( + d["radial_basis"], + d["cutoff_function"], + radial_hyps, + cutoff_hyps, + descriptor_settings, + d["cutoff_matrix"], + ) + else: + desc_calc = B2( + d["radial_basis"], + d["cutoff_function"], + radial_hyps, + cutoff_hyps, + descriptor_settings, + ) + + elif d["name"] == "B3": + radial_hyps = [0.0, cutoff] + cutoff_hyps = [] + descriptor_settings = [n_species, d["nmax"], d["lmax"]] + desc_calc = B3( + d["radial_basis"], + d["cutoff_function"], + radial_hyps, + cutoff_hyps, + descriptor_settings, + ) + + elif d["name"] == "TwoBody": + desc_calc = TwoBody(cutoff, n_species, d["cutoff_function"], cutoff_hyps) + + elif d["name"] == "ThreeBody": + desc_calc = ThreeBody(cutoff, n_species, d["cutoff_function"], cutoff_hyps) + + elif d["name"] == "FourBody": + desc_calc = FourBody(cutoff, n_species, d["cutoff_function"], cutoff_hyps) + + else: + raise NotImplementedError(f"{d['name']} descriptor is not supported") + + descriptors.append(desc_calc) + + # Define remaining parameters for the SGP wrapper. + species_map = {flare_config.get("species")[i]: i for i in range(n_species)} + sae_dct = flare_config.get("single_atom_energies", None) + if sae_dct is not None: + assert n_species == len( + sae_dct + ), "'single_atom_energies' should be the same length as 'species'" + single_atom_energies = {i: sae_dct[i] for i in range(n_species)} + else: + single_atom_energies = {i: 0 for i in range(n_species)} + + sgp = SGP_Wrapper( + kernels=kernels, + descriptor_calculators=descriptors, + cutoff=cutoff, + sigma_e=flare_config.get("energy_noise"), + sigma_f=flare_config.get("forces_noise"), + sigma_s=flare_config.get("stress_noise"), + species_map=species_map, + variance_type=flare_config.get("variance_type", "local"), + single_atom_energies=single_atom_energies, + energy_training=flare_config.get("energy_training", True), + force_training=flare_config.get("force_training", True), + stress_training=flare_config.get("stress_training", True), + max_iterations=max_iterations, + opt_method=opt_algorithm, + bounds=bounds, + ) + + flare_calc = SGP_Calculator(sgp, use_mapping) + return flare_calc, kernels + + +def get_model(file: str): + """Main method of the script.""" + with open(file, "r") as f: + config = yaml.safe_load(f) + + return get_flare_calc(config) + + +if __name__ == "__main__": + """Launch script from cmd.""" + model, kernels = get_model(sys.argv[1]) + print(model, kernels) \ No newline at end of file diff --git a/meson.build b/meson.build index c64fc29c..aa2d3b92 100644 --- a/meson.build +++ b/meson.build @@ -207,11 +207,19 @@ py.install_sources([ 'Modules/Relax.py', 'Modules/SchaMinimizer.py', 'Modules/Tools.py', - 'Modules/Utilities.py' + 'Modules/Utilities.py', ], subdir: 'sscha', ) +py.install_sources( + [ + 'Modules/ml/__init__.py', + 'Modules/ml/flare.py', + ], + subdir: 'sscha/ml', +) + # --- Installing Scripts --- # Meson is great for installing scripts and making them executable. # Scripts will be installed in the `bin` directory of the Python environment (e.g., venv/bin/). diff --git a/pyproject.toml b/pyproject.toml index 4c634db1..d27a5853 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,6 +29,30 @@ Repository = "https://github.com/SSCHAcode/python-sscha" # Documentation = "https://documentacion.readthedocs.io/" Issues = "https://github.com/SSCHAcode/python-sscha/issues" +[project.optional-dependencies] +pre-commit = [ + 'pre-commit~=2.17', + 'pylint==2.13.7', + 'toml', +] +tests = [ + 'pgtest~=1.3', + 'pytest~=6.0', + 'pytest-regressions~=2.3', + 'pytest-timeout', +] +aiida = [ + 'aiida-core~=2.3', + 'aiida-quantumespresso~=4.10', + 'aiida-pseudo', +] +active-learning = [ + 'mir-flare~=1.4', + 'aiida-core~=2.3', + 'aiida-quantumespresso~=4.10', + 'aiida-pseudo', +] + # --- Meson-python specific configuration (Optional but useful) --- [tool.meson-python] # Here you can pass options to Meson that control the build process. From f9ae38221d7c166163be99b6f083c93ae330bb21 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Wed, 21 Jan 2026 12:00:29 +0000 Subject: [PATCH 16/22] Examples: add realistic active learning examples --- Examples/sscha_and_aiida/Si-dynamical-matrix1 | 56 +++++++++ Examples/sscha_and_aiida/Si-dynamical-matrix2 | 98 +++++++++++++++ Examples/sscha_and_aiida/Si-dynamical-matrix3 | 119 ++++++++++++++++++ Examples/sscha_and_aiida/analysis.ipynb | 53 ++------ Examples/sscha_and_aiida/flare_config.yaml | 32 +++++ .../run_aiida_flare_ensemble.py | 1 - .../sscha_and_aiida/run_aiida_flare_sscha.py | 53 ++++---- Examples/sscha_and_aiida/run_flare_sscha.py | 39 +++--- 8 files changed, 369 insertions(+), 82 deletions(-) create mode 100644 Examples/sscha_and_aiida/Si-dynamical-matrix1 create mode 100644 Examples/sscha_and_aiida/Si-dynamical-matrix2 create mode 100644 Examples/sscha_and_aiida/Si-dynamical-matrix3 create mode 100644 Examples/sscha_and_aiida/flare_config.yaml diff --git a/Examples/sscha_and_aiida/Si-dynamical-matrix1 b/Examples/sscha_and_aiida/Si-dynamical-matrix1 new file mode 100644 index 00000000..0c25b739 --- /dev/null +++ b/Examples/sscha_and_aiida/Si-dynamical-matrix1 @@ -0,0 +1,56 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 2 0 1.8897259890000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 +Basis vectors + 2.7154799999999999 2.7154799999999999 0.0000000000000000 + 2.7154799999999999 0.0000000000000000 2.7154799999999999 + 0.0000000000000000 2.7154799999999999 2.7154799999999999 + 1 'Si ' 25597.9124185021937592 + 1 1 -0.0000000000000004 0.0000000000000004 0.0000000000000004 + 2 1 1.3577400000000002 1.3577400000000006 1.3577400000000004 + + Dynamical Matrix in cartesian axes + + q = ( 0.000000000000 0.000000000000 0.000000000000 ) + + 1 1 + 0.2590944141379855 0.0000000000000000 0.0000000000000001 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0.000000 ) +( -0.106088 0.000000 -0.636928 0.000000 0.288216 0.000000 ) + freq ( 4) = 14.80188490 [THz] = 493.73766382 [cm-1] +( -0.042416 0.000000 -0.451763 0.000000 -0.542320 0.000000 ) +( 0.042416 0.000000 0.451763 0.000000 0.542320 0.000000 ) + freq ( 5) = 14.80188490 [THz] = 493.73766382 [cm-1] +( -0.515182 0.000000 0.391193 0.000000 -0.285579 0.000000 ) +( 0.515182 0.000000 -0.391193 0.000000 0.285579 0.000000 ) + freq ( 6) = 14.80188490 [THz] = 493.73766382 [cm-1] +( -0.482481 0.000000 -0.377992 0.000000 0.352610 0.000000 ) +( 0.482481 0.000000 0.377992 0.000000 -0.352610 0.000000 ) +*************************************************************************** diff --git a/Examples/sscha_and_aiida/Si-dynamical-matrix2 b/Examples/sscha_and_aiida/Si-dynamical-matrix2 new file mode 100644 index 00000000..9a7d901e --- /dev/null +++ b/Examples/sscha_and_aiida/Si-dynamical-matrix2 @@ -0,0 +1,98 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 2 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0.0000000000000000 -0.0000000000000000 + -0.0000000000000000 -0.0000000000000000 0.0000000000000000 0.0000000000000000 0.2477607075541518 0.0000000000000000 + + Diagonalizing the dynamical matrix + + q = ( -0.184129509332 0.000000000000 0.000000000000 ) + +*************************************************************************** + freq ( 1) = 4.45331342 [THz] = 148.54652494 [cm-1] +( -0.000000 0.000000 0.703431 0.000000 0.072005 0.000000 ) +( 0.000000 -0.000000 0.072005 -0.000000 0.703431 -0.000000 ) + freq ( 2) = 4.45331342 [THz] = 148.54652494 [cm-1] +( 0.000000 -0.000000 -0.072005 -0.000000 0.703431 0.000000 ) +( -0.000000 0.000000 0.703431 -0.000000 -0.072005 0.000000 ) + freq ( 3) = 12.24928837 [THz] = 408.59222083 [cm-1] +( -0.145074 0.000000 0.000000 -0.000000 -0.000000 0.000000 ) +( -0.989421 0.000000 0.000000 -0.000000 -0.000000 0.000000 ) + freq ( 4) = 12.24928837 [THz] = 408.59222083 [cm-1] +( 0.989421 0.000000 -0.000000 -0.000000 -0.000000 0.000000 ) +( -0.145074 0.000000 -0.000000 -0.000000 0.000000 0.000000 ) + freq ( 5) = 13.77242792 [THz] = 459.39867995 [cm-1] +( 0.000000 -0.000000 0.411585 -0.000000 -0.574977 0.000000 ) +( 0.000000 -0.000000 0.574977 -0.000000 -0.411585 0.000000 ) + freq ( 6) = 13.77242792 [THz] = 459.39867995 [cm-1] +( 0.000000 -0.000000 0.574977 -0.000000 0.411585 -0.000000 ) +( 0.000000 0.000000 -0.411585 0.000000 -0.574977 0.000000 ) +*************************************************************************** diff --git a/Examples/sscha_and_aiida/Si-dynamical-matrix3 b/Examples/sscha_and_aiida/Si-dynamical-matrix3 new file mode 100644 index 00000000..b3429299 --- /dev/null +++ b/Examples/sscha_and_aiida/Si-dynamical-matrix3 @@ -0,0 +1,119 @@ +Dynamical matrix file +File generated with the CellConstructor by Lorenzo Monacelli +1 2 0 1.8897259890000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 0.0000000000000000 +Basis vectors + 2.7154799999999999 2.7154799999999999 0.0000000000000000 + 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-0.0916577820034767 0.0000000020032446 -0.0916577820034767 0.0000000020032446 -0.1450170224563141 0.0000000031694479 + 2 1 + -0.1450170224563140 -0.0000000031694479 0.0916577820034768 0.0000000020032446 -0.0916577820034767 -0.0000000020032446 + 0.0916577820034766 0.0000000020032446 -0.1450170224563140 -0.0000000031694479 -0.0916577820034767 -0.0000000020032446 + -0.0916577820034767 -0.0000000020032446 -0.0916577820034767 -0.0000000020032446 -0.1450170224563141 -0.0000000031694479 + 2 2 + 0.2749110163951162 0.0000000000000000 0.0187616737939292 0.0000000000000000 -0.0187616737939293 0.0000000000000000 + 0.0187616737939292 -0.0000000000000000 0.2749110163951161 -0.0000000000000000 -0.0187616737939292 -0.0000000000000000 + -0.0187616737939293 -0.0000000000000000 -0.0187616737939293 0.0000000000000000 0.2749110163951161 -0.0000000000000000 + + Dynamical Matrix in cartesian axes + + q = ( -0.092064754666 -0.092064754666 -0.092064754666 ) + + 1 1 + 0.2749110163951161 -0.0000000000000000 0.0187616737939294 -0.0000000000000000 0.0187616737939294 0.0000000000000000 + 0.0187616737939294 0.0000000000000000 0.2749110163951163 -0.0000000000000000 0.0187616737939293 -0.0000000000000000 + 0.0187616737939294 -0.0000000000000000 0.0187616737939293 0.0000000000000000 0.2749110163951161 -0.0000000000000000 + 1 2 + 0.1450170224563137 0.0000000095083433 -0.0916577820034765 -0.0000000060097335 -0.0916577820034765 -0.0000000060097335 + -0.0916577820034765 -0.0000000060097335 0.1450170224563138 0.0000000095083433 -0.0916577820034765 -0.0000000060097335 + -0.0916577820034765 -0.0000000060097335 -0.0916577820034765 -0.0000000060097335 0.1450170224563137 0.0000000095083433 + 2 1 + 0.1450170224563137 -0.0000000095083433 -0.0916577820034765 0.0000000060097335 -0.0916577820034765 0.0000000060097335 + -0.0916577820034765 0.0000000060097335 0.1450170224563138 -0.0000000095083433 -0.0916577820034765 0.0000000060097335 + -0.0916577820034765 0.0000000060097335 -0.0916577820034765 0.0000000060097335 0.1450170224563137 -0.0000000095083433 + 2 2 + 0.2749110163951163 -0.0000000000000000 0.0187616737939293 -0.0000000000000000 0.0187616737939293 -0.0000000000000000 + 0.0187616737939293 0.0000000000000000 0.2749110163951162 0.0000000000000000 0.0187616737939294 0.0000000000000000 + 0.0187616737939293 0.0000000000000000 0.0187616737939294 -0.0000000000000000 0.2749110163951162 -0.0000000000000000 + + Dynamical Matrix in cartesian axes + + q = ( -0.092064754666 0.092064754666 0.092064754666 ) + + 1 1 + 0.2749110163951163 0.0000000000000000 -0.0187616737939294 0.0000000000000000 -0.0187616737939294 0.0000000000000000 + -0.0187616737939294 -0.0000000000000000 0.2749110163951159 0.0000000000000000 0.0187616737939296 -0.0000000000000000 + -0.0187616737939293 -0.0000000000000000 0.0187616737939296 0.0000000000000000 0.2749110163951159 0.0000000000000000 + 1 2 + -0.1450170224563140 0.0000000031694477 -0.0916577820034767 0.0000000020032444 -0.0916577820034767 0.0000000020032444 + -0.0916577820034767 0.0000000020032444 -0.1450170224563138 0.0000000031694477 0.0916577820034765 -0.0000000020032444 + -0.0916577820034767 0.0000000020032444 0.0916577820034766 -0.0000000020032444 -0.1450170224563140 0.0000000031694477 + 2 1 + -0.1450170224563140 -0.0000000031694477 -0.0916577820034767 -0.0000000020032444 -0.0916577820034767 -0.0000000020032444 + -0.0916577820034767 -0.0000000020032444 -0.1450170224563138 -0.0000000031694477 0.0916577820034766 0.0000000020032444 + -0.0916577820034767 -0.0000000020032444 0.0916577820034765 0.0000000020032444 -0.1450170224563140 -0.0000000031694477 + 2 2 + 0.2749110163951162 -0.0000000000000000 -0.0187616737939292 0.0000000000000000 -0.0187616737939293 0.0000000000000000 + -0.0187616737939292 0.0000000000000000 0.2749110163951162 -0.0000000000000000 0.0187616737939293 -0.0000000000000000 + -0.0187616737939293 0.0000000000000000 0.0187616737939293 0.0000000000000000 0.2749110163951162 0.0000000000000000 + + Dynamical Matrix in cartesian axes + + q = ( 0.092064754666 -0.092064754666 0.092064754666 ) + + 1 1 + 0.2749110163951160 0.0000000000000000 -0.0187616737939294 -0.0000000000000000 0.0187616737939294 -0.0000000000000000 + -0.0187616737939294 0.0000000000000000 0.2749110163951164 -0.0000000000000000 -0.0187616737939294 0.0000000000000000 + 0.0187616737939294 0.0000000000000000 -0.0187616737939294 -0.0000000000000000 0.2749110163951167 -0.0000000000000000 + 1 2 + -0.1450170224563140 0.0000000031694478 -0.0916577820034766 0.0000000020032445 0.0916577820034766 -0.0000000020032445 + -0.0916577820034767 0.0000000020032445 -0.1450170224563142 0.0000000031694478 -0.0916577820034767 0.0000000020032445 + 0.0916577820034768 -0.0000000020032445 -0.0916577820034768 0.0000000020032445 -0.1450170224563141 0.0000000031694478 + 2 1 + -0.1450170224563140 -0.0000000031694478 -0.0916577820034766 -0.0000000020032445 0.0916577820034768 0.0000000020032445 + -0.0916577820034766 -0.0000000020032445 -0.1450170224563141 -0.0000000031694478 -0.0916577820034768 -0.0000000020032445 + 0.0916577820034766 0.0000000020032445 -0.0916577820034767 -0.0000000020032445 -0.1450170224563141 -0.0000000031694478 + 2 2 + 0.2749110163951161 -0.0000000000000000 -0.0187616737939293 0.0000000000000000 0.0187616737939293 0.0000000000000000 + -0.0187616737939293 -0.0000000000000000 0.2749110163951163 0.0000000000000000 -0.0187616737939292 0.0000000000000000 + 0.0187616737939293 -0.0000000000000000 -0.0187616737939292 -0.0000000000000000 0.2749110163951161 0.0000000000000000 + + Diagonalizing the dynamical matrix + + q = ( 0.092064754666 0.092064754666 -0.092064754666 ) + +*************************************************************************** + freq ( 1) = 2.86950234 [THz] = 95.71628150 [cm-1] +( -0.037580 0.000000 -0.480150 0.000000 -0.517730 0.000000 ) +( -0.037580 -0.000000 -0.480150 -0.000000 -0.517730 -0.000000 ) + freq ( 2) = 2.86950234 [THz] = 95.71628150 [cm-1] +( -0.576126 0.000000 0.320608 -0.000000 -0.255518 -0.000000 ) +( -0.576126 -0.000000 0.320608 0.000000 -0.255518 -0.000000 ) + freq ( 3) = 10.76603767 [THz] = 359.11631010 [cm-1] +( -0.408248 0.000000 -0.408248 0.000000 0.408248 0.000000 ) +( 0.408248 0.000000 0.408248 0.000000 -0.408248 -0.000000 ) + freq ( 4) = 12.17758744 [THz] = 406.20053535 [cm-1] +( -0.408248 -0.000000 -0.408248 -0.000000 0.408248 -0.000000 ) +( -0.408248 -0.000000 -0.408248 -0.000000 0.408248 0.000000 ) + freq ( 5) = 14.43507317 [THz] = 481.50214305 [cm-1] +( -0.118390 -0.000000 -0.430180 -0.000000 -0.548570 -0.000000 ) +( 0.118390 0.000000 0.430180 0.000000 0.548570 0.000000 ) + freq ( 6) = 14.43507317 [THz] = 481.50214305 [cm-1] +( -0.565082 0.000000 0.385069 0.000000 -0.180012 0.000000 ) +( 0.565082 0.000000 -0.385069 -0.000000 0.180012 -0.000000 ) +*************************************************************************** diff --git a/Examples/sscha_and_aiida/analysis.ipynb b/Examples/sscha_and_aiida/analysis.ipynb index 833f2e09..4e6239ba 100644 --- a/Examples/sscha_and_aiida/analysis.ipynb +++ b/Examples/sscha_and_aiida/analysis.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 10, + "execution_count": 116, "metadata": {}, "outputs": [], "source": [ @@ -30,24 +30,24 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 117, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 19, + "execution_count": 117, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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z2vU+ffrUqu5hhx0WjRs3rrI+bdq0WtWtC1599dUqa8XFxVWOCQYAAOqnS47dPyN9Lu1/QEb6AAAAVEcgWUt33nlnxRGtyWQyEolEdOnSJbtD7UQymYyLLrooNm/eXLHWqFGjeOCBB6oN9lJl5syZ1a4feuihtarbrFmz2Hfffausv/3227Wqm23jxo2LRYsWVVn/9re/nYVpAACAdBhY3D4G9Uzv0a2De3WIAcXt0toDAADg8+Rle4D67Pnnn4+RI0dW2h0ZEfG1r30tSxPtmoceeihee+21SmuXX355HH744Wnt+9mjbbc78MADa137wAMPrFJ/4cKFsW3btmjUqP7l7u+//35ceeWVVdb32muvuPTSS1PSY/78+fGLX/wiXn/99ZgzZ06sWLEi1qxZEy1btoy2bdvGnnvuGd27d49jjjkmjjnmmDoftAMAQH1146Bu8ff5K2N56eadv7iG2rdqEiNO7pbyugAAADVR/5KaOmD58uVx5ZVXxmmnnRZlZWVVnj/55JOzMNWuWbp0aVx33XWV1jp27Bg333xz2nsvXLiwylpeXl60b9++1rU7dKj6ieKysrJYsmRJrWtn2vPPPx9f+cpXqsyeSCTioYceirZtU3OPmV//+tfx/e9/P8aNGxdz5syJjz/+OMrLy2PVqlUxb968+Pvf/x4PP/xwnHvuubHffvtF//79409/+lNKegMAAP/RpnlBjD2vbxQ2zU9p3cKm+TH2vL7RpnlBSusCAADUVE7ukPzs7r/a2LZtW6xbty5WrVoVc+bMib///e/x+uuvx7Zt2yqOaI34z3GtZ511VhQXF6esf6pdeeWVsWbNmkpro0aNipYtW6a990cffVRlrV27dlV2mO6OoqKiatc//vjj6NSpU63rp8uGDRuipKQk3n333Zg6dWo88cQTMX369Cqva9y4cTzwwANxyimnZHzG7V577bV47bXXok+fPvHEE0/EQQcdlPaeH330UXz88cc1umbevHlpmgYAANKnuKhVPHlxvzh3zNSU7JRs36pJjD2vbxQXtUrBdAAAALWTk4Hksccem5KQa0eSyWRERJUehYWFcdttt6Wtb20999xz8fvf/77S2kknnRSnn356RvqvXLmyylphYWFKau+oTnU9s+HOO++Ma665ZreuPfjgg2PMmDFx1FFHpXiq3fPPf/4z+vTpE7/61a/irLPOSmuv++67L2688ca09gAAgLqiuKhVvDD8mBjx/Ox4bvrun/YyuFeHGHFyNzsjAQCAOiMnA8nttgeHqfbZIDKZTEbz5s3jj3/8Y+yzzz5p6VlbpaWlcfnll1daa9asWdx7770Zm2HdunVV1lq0aJGS2jva4bl27dqU1M+0vLy8GDBgQAwdOjTOPvvsaNy4ccp77LXXXtG9e/c48MADo7CwMFq0aBGlpaWxcuXKePvtt+Ptt9+Obdu2VXvt2rVr4+yzz46SkpK48MILUz4bAAA0VG2aF8SoIYfF4F4dYvSk92Pq/FW7fG3f/drGpf0PiAHF7dI4IQAAQM3ldCCZzl2SEf8JPHv06BGPPPJI9O7dO639auP666+PxYsXV1q74YYbokuXLhmbYfPmqscOFRSk5hO7+fnV32ulup71QcuWLaN9+/bRtGnTlP497t+/f5xyyilx0kkn7fTI1dLS0vjtb38bd955Z7z33nvVvubSSy+Ngw46KI499tiUzQgAAEQMLG4fA4vbx7vL1sb4GYtjxoclMXNxSZRsLK94TWHT/OjRsTB6di6MQT07Rtei9N+KAwAAYHfkdCCZap/dcXnIIYfERRddFJdffnnk5dXdP8rJkyfH6NGjK6316NEjrrrqqozOUV5eXmUtVX9uOwokq+tZH6xevToef/zxePzxx+PAAw+M2267LU477bTdrved73wnRo8eXaP7m7Zq1SouueSSuOCCC+KHP/xh3HnnnVX+G9i6dWucc845MXfu3GjWrNluz7cjl112WZx55pk1umbevHlZvdcmAACkUteilnFN0Sf/jk8mk7G+bGuUbdkWBXmNonlB47R/EBcAACAV6m6KVkupOq41kUhEy5Yto1WrVtG2bdvo1q1b9OnTJ4455pg4/PDDU9IjncrKyuKiiy6q9OeRSCRi9OjRGQ9RGzVqFFu3bq20tqMjQWtqR3UaNWqUkvq1dfTRR8fIkSMrrSWTySgpKYnVq1fHzJkzY8aMGVFWVlbl2nnz5sXpp58eF154Ydx///27dXzr+eefv9uz5+Xlxe233x6HHHJInHfeeVWe//DDD+PnP/95/M///M9u99iRdu3aRbt2jpsCAICIT36Wa9EkL6JJticBAAComZwMJFMVcuWCW265Jd55551KaxdeeGEceeSRGZ8lPz+/SiC5ZcuWlNTeUZ1UHQlbW/369Yt+/fp97ms2bdoUTz31VNx1110xbdq0Ks8/9NBDsWHDhnjsscey8inoYcOGxb/+9a+49dZbqzx39913x3XXXbfDnaoAAAAAAEDDVTe2j5EWc+bMiZ/+9KeV1tq1a1dtoJQJTZs2rbK2cePGlNTesGFDtet77LFHSupnwh577BHf+c534h//+Efceuut1e7u/M1vfhP33XdfFqb7xP/+7/9Gx44dq6x//PHH8corr2RhIgAAAAAAoK4TSOaoZDIZF154YZUjQH/+859HmzZtsjJTdX1LS0tTUnvt2rXVrrdt2zYl9TOpcePGcd1118WDDz5Y7fPXXnttrFixIsNTfaJp06bx/e9/v9rnXn755QxPAwAAAAAA1AcCyRw1evTomDx5cqW14447Lr71rW9laaKIPffcs8raypUrU1J7RwFdfQwktzv//PNjyJAhVdY3bNgQo0ePzsJEnzjppJOqXX/zzTczPAkAAAAAAFAfCCRz0IoVK+L666+vtNakSZO4//77szTRJzp06FBlraSkJCXHti5btqza9U6dOtW6djbdfPPN1a6PGzcuw5P8R3FxcbVB7/vvv5+FaQAAAAAAgLouL9sDkHqLFi2qchRq165d48knn0xZj4ULF8ZPfvKTKutFRUVxwQUXVHvNfvvtV+36ggUL4pBDDqnVPAsWLKiytueee0bLli1rVTfb9t9//+jZs2fMmDGj0vqMGTNi7dq1WXt/7du3j1WrVlVaS9VuVwAAAAAAILcIJBuIt99+O95+++2U1VuwYEH8+Mc/rrLes2fPHQaSBx98cLXr//rXv2odSP773//e5X71zWGHHVYlkNy2bVssXrw4iouLszJTdfcD3bRpUxYmAQAAAAAA6jpHtpIxhx12WLXrnw3bamrBggWxZs2aXe5X37Rv377a9c/uUMyk1atXV1lr2rRpFiYBAAAAAADqOoEkGdOrV69o0qRJlfU33nijVnV3dH3fvn1rVbeu2NHOw7y87G1wXr58eZW16u4rCQAAAAAAIJAkY/bYY4844ogjqqy//vrrsXnz5t2u+5e//KXa9a9+9au7XbMuqS78i8heADh37txqd2d26dIl88MAAAAAAAB1Xp2/h+TAgQOzPUKNJBKJeOWVV7I6Q69evSKZTKasXiKRqLLWv3//mDhxYo1rnXjiiVWuW79+ffzpT3+KU089tcb1ysvL49lnn62y/sUvfjE6duxY43p10V//+tcqa/n5+bHvvvtmYZqIP/7xj9Wu9+nTJ8OTAAAAAAAA9UGdDyQnTpxYbSBWFyWTyXoza7YMGTIkrrvuuiqB6ejRo3crkPzd735X7f0Mv/nNb+72jHXJlClTYtGiRVXW+/TpE/n5+RmfZ9OmTXHXXXdV+1x9+/AAAAAAAACQGfXmyNZkMlmnv9g1nTt3jhNOOKHK+ksvvVTje0lu2bIlbrnllirrBQUFcc455+z2jHVFMpmMq6++utrnBg0alOFpPjFy5MhYvHhxlfU2bdrE8ccfn4WJAAAAAACAuq7eBJKJRKJOf7Hrrr322mrXL7744ti0adMu17n11lvjnXfeqbJ+zjnnxN57712jmUaMGFHt/64jRozY5RqzZs2qUc+dufbaa2Py5MlV1ps0aRLnnnvuLtVYuHBhygLzX//619UGwBERl112WTRp0iQlfQAAAAAAgNxSLwLJbO9+tEsytY499tg46aSTqqzPnDkzvvnNb0Z5eflOazzxxBPVhoXNmzevUYiYSt/+9rfj2GOP3a17a37aqlWrYujQoXHnnXdW+/yVV14ZHTp02KVad911V/To0SN++9vfxpYtW3Zrnq1bt8YPfvCDGDp0aLXP77333nHNNdfsVm0AAAAAACD31fl7SN5www3ZHoE0uPvuu+O1116LtWvXVlp/5pln4uijj477778/evfuXeW61atXx0033RSjRo2qNgS++eabo2PHjmmbe2cmTZoUAwYMiP322y/OOuusOOWUU6JXr16xxx577PTauXPnxuOPPx4PPPBArFixotrXHHrooXHTTTfVaKbZs2fHt771rRg+fHicdtppccYZZ8QRRxwRLVq0+NzrSktL4//+7//iZz/7WfzrX/+q9jWNGjWKMWPGRGFhYY1mAgAAAAAAGg6BJFmx//77x8MPPxxnn312lWBx6tSp0adPn+jdu3ccccQRsddee8WGDRti9uzZMWHChB0e63rqqafG8OHDMzH+Ts2fPz9uu+22uO222yIvLy+6du0ahx56aLRp0yZat24dzZo1i/Xr10dpaWnMnz8/pk+fHh999NHn1uzcuXP86U9/iqZNm+7WTCtWrIgHH3wwHnzwwUgkEnHAAQdEjx49Yq+99orCwsJo3rx5rF27NlatWhVvv/12zJgxI7Zu3fq5Ne++++5q7wkKAAAAAACwXZ0PJMldZ555Znz88cdxxRVXVLvb8a233oq33nprl2odd9xx8dvf/jbVI6bEli1bYvbs2TF79uzdrtGvX7946qmnolOnTimZKZlMxrx582LevHm7dX1hYWHcf//98d///d8pmQcAAAAAAMhd9eIekuSuyy67LH7/+9/X6sjPiy++OP7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6V/3lL3+xav/yyy+1bds2h3MEUL+XX37Zqi04OFjPPfecXXFiY2N1//33W7UfOXJEc+fOdTQ94ISBAwfqvPPOMz1jw9Nqamr06quvWrW3atVKDz30kF2xevbsqQkTJli1Z2ZmatmyZXbFYjzD3XxpHPoqs3EoSS+++KICAmx/6yM8PFzTpk2zaq+srNRrr73maHrwU9dff71uvvlmBQUFOR2rbdu2uu+++0yvLV682OY4zIVoTHxxDPoq5kH4i969e2vEiBFW7cePH9f3339vUwzmQv9FQRIA/MxHH32k48ePW7X/4x//sOuXzN/dddddVm2GYWjevHkO5Qegfr/88ovS0tKs2q+++mq1b9/e7niTJk0yfZP63XffdSg/wFctX75cBw4csGqfOHGimjVrZnc8szlQsm/sMJ4B7ysqKtKSJUus2s8991ydffbZdse76qqrTMfvvHnzZBiGQzkC0m/FFTPfffedzTGYCwHHuWIM+iLmQfgbs4KkJOXm5tp0P3Oh/6IgCQB+5uOPP7ZqCw0N1dVXX+1QvAsuuEBt2rSxav/oo48cigegfmbjWJLGjh3rULzmzZvrsssus2r/7rvvdPDgQYdiAr6orrFzww03OBTvrLPOMn2TZtGiRaqurnYqJ8Yz4DmfffaZ6Qf2HB2HgYGBuvbaa63a9+zZY/pGE2Cr9u3b6/TTT7dqN3tTtS7MhcyFcJwrxqAvYh6Ev6mrQJeXl2fT/cyF/jsXUpAEAD9SUVFh+sm9QYMGKTIy0qGYAQEBuvjii63as7OztW/fPodiAjg1s20/wsPDNXToUIdjXnrppVZthmHom2++cTgm4GvMXs9nnnmm4uPjHY5pNnaKi4u1bt06m+5nPAPeV9d2WmZjyVZ13Wvv1l3An8XGxlq12foGrMRcyFwIZzk7Bn0R8yD8TUhIiGm7rccTMBf671xIQRIA/MhPP/2k8vJyq3ZnJrdT3b969Wqn4gKwVl1dbfoL7bnnnqvg4GCH4zKO0dDt27dPOTk5Vu3enAMZz4Bv+Pbbb63azjrrLLVt29bhmGeffbbCwsKs2hmHcJbZdodNmjSx6V7mQsYgnOfMGPRVzIPwN3WtSrZla1PmQv8ehxQkAcCP/Pzzz6btffv2dSpuv379TNs3btzoVFwA1rKysky303F2HMfFxZl+2pdxjIbCXXNg7969FRgYaNVuy9hhPAPeV1hYqJ07d1q1OzsOg4ODlZiYaNXOOISzzF6vZj/zzTAXMgbhPGfGoC9iHoQ/WrFihWn7ueeeW++9zIX+PQ4pSAKAH9m8ebNpe7du3ZyKe8YZZ5hul7Bp0yan4gKw5q5xXFeMzMxM008BA/7GXWOnadOm6tChg1W7LXMg4xnwvs2bN5uOC3eNw6NHj2r//v1Ox0bjlJmZqaNHj1q1d+7c2ab7mQuZC+EcZ8egL2IehL/Zu3evFi5caNV+wQUXKCYmpt77mQv9ey6kIAkAfsTsU29hYWGKi4tzKm5gYKA6duxo1W62BQLQkOTl5Sk1NVXXXXedevXqpTZt2igkJEQtWrRQly5dlJycrOuvv16zZs1Sdna2S/o0G8fSbx8McJZZjIqKCv7DiAbB02Nn9+7dqq2t9amcGM/wZUVFRZo9e7Zuuukm9e7dW3FxcWrSpIkiIyPVqVMn9e3bV1dddZVeeeUVZWRk1Du+bOXpcSjxOzIc9+6775q2jxgxwqb7mQuZC+EcZ8fgqTAPAvUrLy/XuHHjVFZWdlK7xWLRww8/bFMM5kL/nguDvJ0AAMB2u3fvtmpr06aNLBaL07Hbtm2rX375xao/wzBcEh/wRV999ZW++uorq/aCggIVFBRo586d+umnnzRv3jxJUlJSku69915dffXVplt52MJsHEty+oMFkuo8IyQnJ8cl8QFvMhs7QUFBNn2Ktj5mY6eyslL79+9Xu3bt7MpJYjyjcdq4caNuuukmq/aKigoVFxdr165d2rBhgz7++GNJv725cvfdd2v8+PFOnd3lrXFoy5ZiwB8dO3ZMb7zxhum1yy67zKYYzIW/YS6EI1wxBk+FeRA4tS1btmjChAmmZy3+4x//0ODBg22Kw1z4G3+dC1khCQB+5NChQ1ZtrjrrwCxOVVWVCgoKXBIfaAjS09N17bXXKiEhQWlpaQ7FMBvHklzyy3NdPw8OHz7sdGzA28zGTuvWrV3yoRlHxw7jGXDc9u3bNXnyZHXs2FFffvmlw3HqGoeu+B2ZcQhXeuSRR0z/bzVixAjT3WrMMBfalhNgxhVj0JWYB9GQVVRU6PDhw1q/fr1mzZqlv/71r+rVq5dpMfLGG2/U888/b3Ns5kLbcvJVFCQBwE9UVlaqpKTEqj0qKsol8euKY3a+AtDYbd++Xeeff75eeeUVu+81G1NhYWGm57jai3GMhszsdeztOZDxDDgvLy9Pl1xyiR544AHV1NTYfX9dY8IVPx8Yh3CVlStX6vXXX7dqDwgI0JNPPmlzHOZC23IC/sxVY9AdmAfhz9avXy+LxWL11aRJE7Vu3Vr9+/fXxIkT9dVXX1m9vps3b65Zs2bprbfeUkCA7WUq5kLbcvJVbNkKAH7CrBgpSc2aNXNJ/IiICNP24uJil8QHfFFUVJS6d++u+Ph4tWjRQhERESopKdGxY8eUnZ2t9evXq6qqyvTeyspKTZkyRYcOHdJTTz1lc59mY5lxDNTPF8eOL+YEeEt4eLi6deumrl27Kjo6WpGRkTp+/LiOHj2qHTt26Mcff1R5ebnpvYZh6JlnnlFubq7mzJlj1yfc3fk7MuMQrnDo0CFdd911MgzD6trNN9+sfv362RzLF+cdX8wJ+CNXjsFTYR4EbJOUlKS//e1vmjRpkiIjI+2+3xfnHV/MyVdRkAQAP1FRUWHa7opP20hScHCwXf0C/qpv37664oordMkll6hXr16nfGxZWZkWL16s5557Tunp6aaPefrppxUfH68bbrjBpv7NxhTjGKifL44dX8wJ8KT4+HhdddVVuuSSS5ScnHzKT7dXVlZq6dKleu655/Ttt9+aPmbu3Lk688wz9cgjj9icgzt/R2YcwllVVVW66qqrdODAAatrHTt21H/+8x+74vnivOOLOQG/c/UY/DPmQcA+wcHBatu2rSIjI+1aFflHvjjv+GJOvootWwHAT9S1SisoyDWfLalrgqurX8DfXHzxxUpLS9P69ev1wAMP1FuMlKSmTZvqb3/7mzZu3KgXXnihznFy6623av/+/TblYTamGMdA/Xxx7PhiToAnnH322frmm2+UnZ2tJ598UgMGDKj3TaWQkBBdeumlWrNmjebNm1fnp8Yff/zxOj8EZMadvyMzDuGsSZMmac2aNVbtwcHBev/99+tc9VAXX5x3fDEn4HeuHoO/Yx5kDMIxVVVV+uKLLzR58mS1b99e06ZNs3urYl+cd3wxJ1/FCkkA8BN1/XJbW1vrkvh1xXH0E0uAr7n66quduv+uu+5Sjx49dMkll6i6uvqkayUlJXr00Uf13//+t944ZmOKcQzULyAgwOo/q94eO4xnNFZ//etfnbr/2muvVffu3TVo0CAVFRWddK2mpkb/+te/9M0339gU61S/Izs7XhiHcMbjjz+ut956y/TaSy+9pAEDBtgdk7nQtpwAyT1j8HfMg4xB/CYuLs70HNaSkhIVFBRo+/btWr9+vQoLC60eU1BQoIceekiffvqplixZotNOO82mPpkLbcvJV1GQBAA/UdcnYv5cGHFUXXFctcUA0BBcdNFFmjFjhiZNmmR1be7cuZo2bZpat259yhhmY5lxDNQvODjY6j+e3h47jGfAcYmJiZo/f77pm7rLly9XRkaGEhMT641zqt+RnR0vjEM4aubMmZo6darptQceeEC33XabQ3GZC23LCXDXGHQl5kE0BG3atNHDDz98yscYhqEVK1ZoxowZWrRokdX1devWadiwYVq9erWio6Pr7ZO50LacfJV/llEBoBEKCwszba/rUHR7lZWVmbY3adLEJfGBhuKWW25R3759rdorKyu1YMGCeu83G8uMY6B+vjh2fDEnwJ+MGDFCo0ePNr32/vvv2xTDnb8jMw7hiHnz5umOO+4wvTZp0iRNmzbN4di+OO/4Yk5o3Nw5Bl2NeRCNgcVi0fDhw7Vw4UJ9+umnatmypdVjMjMzNXHiRJvi+eK844s5+SoKkgDgJyIiIhQYGGjV/uftPRxVXFxs2m7Lp5OAxsRiseiBBx4wvWbLtjotWrSwaqtr/NmLcYyGzGzseHsOZDwDznvooYdM223dqs5sHEqu+fnAOIS9Fi1apPHjx5tur3bddddp5syZTsVnLrQtJzRe7h6D7sA8iMbk0ksv1dKlSxUVFWV17eOPP9aXX35ZbwzmQtty8lUUJAHAT1gsFtPJ5ujRoy6Jf+TIEdN2f53gAHe66KKLTLfkWL9+fb33mn0asKamRgUFBU7nxThGQ2Y2drw9BzKeAef16dNHsbGxVu0ZGRmqqqqq936zcSi55ucD4xD2WLp0qcaMGWO6tdqoUaP09ttvy2KxONUHc6FtOaFx8sQYdAfmQTQ2ffr00bPPPmt67YUXXqj3fuZC23LyVRQkAcCPtG3b1qrt4MGDLoltFic6OrrO7T+AxiwiIkI9e/a0at+7d2+9/2k0G8eSa8ZyXTHatWvndGzA28zGTmFhoUu2wnF07DCeAedZLBadc845Vu3V1dXau3dvvfczDuEL1qxZo9GjR6uiosLq2oUXXqgPPvhAQUFBTvfDXGhbTmh8PDUG3YF5EI3RzTffrE6dOlm1r1y5st4iHnOhbTn5KgqSAOBHzCbrQ4cO1bmfuD127dplU38AfhMTE2PVVltbW+8vz3WNq5ycHKdzMhvHp+oT8Cd1vY7ret3bwyxGy5YtFRER4VBOjGfAPmZzqmTbp90Zh/C2H3/8UZdeeqnp/8nOP/98LVq0SKGhoS7pi7nw1H2icfLkGHQX5kE0NgEBARo5cqRVe21trb7//vtT3stceOo+fR0FSQDwI2eddZZVm2EY+vXXX52KW1hYqMOHD9vUH4Df1HVWx/Hjx095X13j6pdffnE6J7OfBW3atFGzZs2cjg14m6fHji1zIOMZcA1H51TJ8+MwMDBQXbp0cTo2GoaNGzdqxIgRpuc79e/fX5999pmaNm3qsv6YC5kLcTJPj0F3YR5EY9S7d2/T9j179pzyPuZC/54LKUgCgB+pa7LOyMhwKu7GjRvt6g+AlJ+fb9pe3zbH7hrHlZWV2rJli839Af7GXWNn165dpiubbRk7jGfANRydUyUpPj7e9M1mZ8ehZP47cnx8PEcaQJKUlZWliy66yHQO6dWrl77++mtFRka6tE/mQuZC/B9vjEF3YR5EY1TXyuBjx46d8j7mQv+eCylIAoAfOfvss03bf/jhB6fi1nV/cnKyU3GBhiwvL8+qLSAgQFFRUae8LzY2VqeffrpVu7Pj+Oeff1ZlZaVVO+MYDUVSUpLpdlvenAMZz4BrmM2p0m/nmdcnICBA/fr1s2pfv369qqurHc7pwIED2r17t1U74xDSbyseLrjgAh05csTqWkJCgpYtW1bniidnMBcyBvEbb41Bd2EeRGNU1wrg+s57ZS7073FIQRIA/EinTp3UsWNHq/Zly5Y5Fdfs/qZNm2rgwIFOxQUaquLiYm3evNmqPS4uTsHBwfXeP2zYMKu27Oxs7d271+Gc6vo5cMEFFzgcE/AlTZo0MZ2Xvv32W1VUVDgc19mxw3gGnGMYhulZQYGBgWrfvr1NMczGYXFxsdatW+dwXoxD1CUnJ0fDhw/XwYMHra516dJFy5cvV+vWrd3SN3MhYxDeHYPuwDyIxsrRQjxzoX+PQwqSAOBnLr74Yqu2HTt21Lntan3y8vK0Zs0aq/YLLrhAISEhDsUEGrqlS5eqqqrKqr1v37423W82jiXp448/djinjz76yKotOjq6zpXVgD8yGzulpaX64osvHIpXVVWlRYsWWbX36tVLcXFxDuckMZ4BW23YsMH0TeWePXva9CEfqe5xaDaWbGV2b2BgoC666CKHY8L/5ebmavjw4dq3b5/VtdNPP13Lly9X27Zt3ZoDcyFzYWPmC2PQ1ZgH0Vh9++23pu1nnnlmvfcyF/rvXEhBEgD8zLXXXmvanpqa6lC8//73v6qpqbG5H6CxMwxD//73v02vmX0izsyll16qiIgIq/ZZs2bJMAy7c1q7dq0yMzOt2q+++up6tzsB/MmYMWNksVis2h2dAz/88EPTM3vsmQMZz4Bzpk2bZtpu65wqSf3799cZZ5xh1T537lyVlpbandPu3bv15ZdfWrVfeOGFOu200+yOh4bh0KFDGj58uHJycqyutWnTRsuXL1eHDh3cngdzIXNhY+UrY9DVmAfRGJWVlZm+xoKCgky3IP4z5kL/nQspSAKAnznnnHPUrVs3q/Y5c+Zo165ddsUqLCzU9OnTrdpbt26tlJQUR1MEGrT//ve/+vnnn63ag4KCdOWVV9oUIywsTNdff71Ve3Z2tubPn293To8//rhp+80332x3LMCXtW/fXiNGjLBqX7p0qd3nc1RXV5u+ARQSEqKxY8faHIfxDDhu6dKlWrBggem1MWPG2BXLbIzk5+fr1VdftTuvp59+2vQDe4zDxis/P18XXnihtm3bZnXttNNO0zfffGNaDHAH5kI0Rr40Bl2JeRCN1dNPP61jx45ZtQ8bNkzh4eH13s9c6McMAIDfmT17tiHJ6usvf/mLUVtba3OcCRMmmMZ56qmn3Jg94Fl79+41KisrXRLrm2++MYKDg03HzXXXXWdXrF9//dUIDAy0itO2bVvj8OHDNseZO3euaT4XXHCBvU8PcEpdc9Ps2bNd2s/KlStN++nZs6dRXl5uc5wnn3zSNM7f//53u3NiPMNXuHsc5uXlGaWlpS6JtXnzZiMqKso033PPPdfueAUFBUZkZKRVrPDwcGPbtm02x1m1apUREBBgFeess84yampq7M4L/q+oqMjo37+/6Wu1RYsWRnp6usdzYi5EY+JLY5B5kHmwMcrOzjaqqqpcFm/BggV1vq/yySef2ByHudA/UZAEAD9UXV1t9OrVy3RyuuOOO2wqSj777LOm97dr184oKSnxwLMAPOOll14yTj/9dGPmzJl2/VL6Zy+//LIREhJiOm6aNm1q5OTk2B3ztttuM403cOBAo6ioqN77V65caTRt2tTq/oCAAGPDhg0OPEvAcZ4qSBqGYVxyySWmfY0ePdqmDyC89957pv9RDA8PN/bt2+dQToxn+AJ3j8OFCxcarVq1MqZNm2YUFBQ4HOeDDz4wIiIiTHO1WCzGDz/84FDc//znP6YxzzzzTCM3N7fe+zMzM43TTjvNNMaiRYscygn+rayszBg8eLDpayIyMtJIS0vzWm7MhWgMfG0MMg+iMZoyZYrRpUsX4+2333bqw95VVVXGf/7znzqLkf3797drkYVhMBf6I4thOLCBLQDA69atW6fzzz9f1dXVVtdGjBihV1991XTLkv379+vee+/VvHnzTOMuXLhQo0aNcnW6gNe8/PLL+uc//ylJioiI0MiRI3X11Vfr/PPPV4sWLU55b3l5uZYsWaLnnntOGzZsqPNxb7zxhm655Ra7c8vPz1diYqL27t1rde2ss87S66+/bnp2SHl5uV566SVNnTpVVVVVVtf/8Y9/6KWXXrI7H6Auc+fO1e7du0/5mI0bN5puOXX55Zerd+/ep7y3Q4cOuuGGG2zOZ+fOnUpKSlJxcbHVteTkZL3++uvq06eP1bX8/Hw98cQTmj59uuk5Hi+//LKmTJlicx5/js14hjv5wjhctGiRRo8eLUlq0qSJRowYoauvvlrDhg1TTEzMKe+tqqrSsmXL9Pzzz2vlypV1Pu6BBx6o8zyt+lRVVenss8/Wxo0bra61adNGr776qi6//HKrM4eqq6v1v//9T/fcc4/pz5VRo0Zp4cKFDuUE/zZ+/HjNmTPH9Nqll16qs88+22V93XDDDXadf8dciMbA18Yg8yAao3/84x8njntq0aKFRo0apauuukoDBw5U8+bN673/8OHD+uCDD5SamqotW7aYPiY8PFxpaWmmR1SdCnOh/6EgCQB+7IUXXtC//vUv02sWi0XnnHOO+vXrpxYtWqioqEjp6elas2aNaRFTajiTG/BHfyxI/tnpp5+uXr16KSYmRlFRUYqIiFBpaamOHTum7OxsrV+/XpWVlaeMf8899+i5555zOL+1a9dq+PDhqqioML2ekJCgQYMGKTY2VpWVlfrll1/0zTffqKioyPTxZ599ttasWaOQkBCHcwL+bMiQIVq9erXb4g8ePFirVq2y656PPvpI11xzjel/ICWpT58+GjhwoFq1aqWysjJlZWVpxYoVOn78uOnjR48eXecZPrZiPMOdfGEc/vGN2D+LjY1VYmKi2rZtq6ioKEVGRqqiokJHjx7Vzp07tW7dOpWVlZ0y/jXXXKP33ntPAQEBjj4Nbd++XcnJycrPzze93qFDBw0dOlTt27dXbW2tdu7cqW+++UaHDx82fXznzp21fv36ej/EhIbJ3ePuj1auXKkhQ4bYdQ9zIRo6XxuDzINojP5YkPyzDh06qFevXmrduvWJ1/3x48dVVFSkgwcPKj09XTk5OXXOU5IUGhqqhQsX6q9//atD+TEX+hkvrcwEALjIvffea7oVgL1f119/PecBoEF66aWXXDJG/vwVGhpqvPjiiy7JcdGiRXVuB2vPV8+ePY0jR464JCfgj+raKstVX4MHD3Yor9dee82wWCxO9z98+HCntnT+I8Yz3MUXxuHChQvd0ndAQIBx3333GdXV1S75Xq1bt870HC17v9q1a2fs2LHDJTnBP7l73P3xa+XKlQ7lyFyIhszXxiDzIBqjKVOmuG3cxcXFGatWrXI6R+ZC/+H4xy0AAD7h2Wef1cyZMxUaGurQ/YGBgXrsscf0zjvvOPUpPKAx6dWrl3766ac6V17aKyUlRStWrFCbNm2civHdd9+pZcuWLskJ8Ae33nqrPvnkE0VFRTkcY+LEifriiy/UpEkTl+TEeAbs07FjR61YsULPPPOMAgMDXRLz7LPP1rp16xQfH+9wjHPOOUdpaWnq3LmzS3IC3IW5EPBvzINojAICAnTrrbdqy5YtGjx4sNPxmAv9B+88A0ADMHnyZGVmZuryyy+3q6h4wQUX6KefftLUqVOtzhAAGoq//OUvuuuuu9S7d2+niu4BAQG6+OKL9cUXXyg9PV09e/Z0YZbSueeeq+zsbN19991q1qyZzfclJCToww8/1KJFixQZGenSnAB/MHr0aGVnZ2vChAl2bWGTnJys5cuXKzU11eVb3zCe0VD169dPDz74oM455xwFBwc7Feu8887T/Pnz9euvv7rkjag/69q1qzIyMvTUU0/Z9SZO+/bt9frrr+vbb7916g0kwJOYCwHPYB5EY/Too4/q3Xff1bXXXqvTTjvNqVht27bV/fffr61bt+q1115z6c955kL/wBmSANDA7Nq1SwsWLNDq1au1ZcsWHTx4UOXl5WrSpIlatWqlrl276vzzz9eoUaPsPiwa8He/n6Wanp6urKws7dmzR3v37tXhw4dVWlqq48ePKzQ0VC1atFDz5s0VExOjfv36aeDAgRo4cKBiYmI8kmdhYaEWLVqkZcuWadOmTdq7d69KSkoUFBSk5s2b68wzz1RycrIuvfRSDR48mA8UAP9fXl6eFi5cqBUrVigzM1O5ubkqLS1VSEiIoqOjlZCQoIEDB2rkyJHq37+/R3JiPKOhKisr06ZNm5Senq7MzEzt3r1be/bsUV5ensrKylReXq6goKATc2qrVq1OnOEzcOBAnX766R7Ltby8XJ999pm+/vprbdy4Ubt27VJxcbEsFouioqLUpUsX9e3bV3/961/1l7/8RUFBQR7LDXA15kLAM5gH0Vjt2LFDaWlp2rhxo3bu3KmcnBwdPHhQJSUlJ+abyMhIRUVFKTo6Wt27d1ffvn1PfLl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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -66,7 +66,7 @@ "t_step = 10\n", "\n", "# Prepare the figure and plot the V(T) from the sscha data\n", - "plt.figure(dpi = 300)\n", + "plt.figure(dpi = 100)\n", "# plt.scatter(temperatures, (volumes-volumes2)/(volumes2*t_step), label = \"SSCHA data\")\n", "plt.scatter(temperatures, volumes, label = \"SSCHA data\")\n", "\n", @@ -80,39 +80,11 @@ "plt.ylabel(r\"Volume [$\\AA^3$]\")\n", "plt.legend()" ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5.439671260411459" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(volumes[0]*4)**(1/3)\n", - "(40.24*4)**(1/3)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3.8.12 ('aiida')", + "display_name": "base", "language": "python", "name": "python3" }, @@ -126,14 +98,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.18" + "version": "3.10.18" }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "ad8f63c217015a5132ad55bc66b40838ad2ef6ce473dcbccdf600c93ceb49af4" - } - } + "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 diff --git a/Examples/sscha_and_aiida/flare_config.yaml b/Examples/sscha_and_aiida/flare_config.yaml new file mode 100644 index 00000000..3104198d --- /dev/null +++ b/Examples/sscha_and_aiida/flare_config.yaml @@ -0,0 +1,32 @@ +# ======================= SGP ML ========================= # +# See also the official FLARE documentation for more details: +# - Docs: https://mir-group.github.io/flare/ +# - GitHub: https://github.com/mir-group/flare/ +# ======================================================== # +gp: SGP_Wrapper +kernels: + - name: NormalizedDotProduct + sigma: 2.0 + power: 2 +descriptors: + - name: B2 + nmax: 8 + lmax: 3 + cutoff_function: quadratic + radial_basis: chebyshev +energy_noise: 0.01 +forces_noise: 0.05 +stress_noise: 0.0001 +species: + - 14 # Si +single_atom_energies: + - -154.272015018195 # Si +cutoff: 4.0 +variance_type: local +opt_algorithm: L-BFGS-B +bounds: [[0.1,6.0],[0.01,1.0],[0.01,1.00],[0.0001,0.005]] +max_iterations: 100 +use_mapping: False +energy_training: True +force_training: True +stress_training: True diff --git a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py index 19b1bc75..3cfcb5b5 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py @@ -17,7 +17,6 @@ load_profile() -# PID: 1013277 def main(): """Run with AiiDA-QuantumESPRESSO + FLARE some ensemble configuration for testing.""" diff --git a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py index c60af2d8..d8b60aaa 100644 --- a/Examples/sscha_and_aiida/run_aiida_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_flare_sscha.py @@ -16,36 +16,46 @@ from aiida_quantumespresso.common.types import ElectronicType from flare.bffs.sgp.calculator import SGP_Calculator -from get_sgp import get_empty_sgp +from sscha.ml.flare import get_model load_profile() +structure_filename = 'Si.pwi' +supercell = [2,2,2] +temperature = 300 +pressure = 0 +number_of_configurations = 50 +flare_config_filename = 'flare_config.yaml' +std_tolerance_factor = -0.01 +update_threshold = abs(std_tolerance_factor * 0.1) +seed_number = 0 +batch_number = number_of_configurations +check_time = 3 +max_iterations = 10 +meaningful_factor = 0.01 +kong_liu_ratio = 0.5 +minimization_step = 0.1 + + def main(): """Run with AiiDA-QuantumESPRESSO + FLARE + SSCHA @ NPT.""" # =========== GENERAL INPUTS =============== # - np.random.seed(0) - number_of_configurations = 50 - batch_number = 1 - check_time = 3 - max_iterations = 10 - temperature = 0 - pressure = 0 - meaningful_factor = 0.5 - kong_liu_ratio = 0.5 - minimization_step = 0.1 - supercell = [2,2,2] - - atoms = read('./Si.pwi') # bulk('Si') - structure = Structure() - structure.generate_from_ase_atoms(atoms) + np.random.seed(seed_number) + atoms = read(structure_filename) # =========== FLARE MODEL =============== # - flare_calc, _ = SGP_Calculator.from_file('./model.json') - # flare_calc = SGP_Calculator(get_empty_sgp(n_types=1, the_map={14: 0}, the_atom_energies={0: -154.272015018195})) + # flare_calc, _ = SGP_Calculator.from_file('./model.json') # if you already have a model + flare_calc, _ = get_model(flare_config_filename) # =========== DYNAMICAL MATRIX =============== # - dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) + dyn = Phonons("Si-dynamical-matrix", nqirr=3) + + # (*) If you have a pre-existing model, you can compute the dynamical matrix with it + # structure = Structure() + # structure.generate_from_ase_atoms(atoms) + # dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) + dyn.Symmetrize() dyn.ForcePositiveDefinite() @@ -53,10 +63,11 @@ def main(): ensemble = AiiDAEnsemble(dyn, temperature) ensemble.set_otf( flare_calc, - std_tolerance_factor=-0.9, + std_tolerance_factor=std_tolerance_factor, max_atoms_added=-1, - update_threshold=0.5, + update_threshold=update_threshold, update_style="threshold", + train_hyps=(1,np.inf), ) # =========== AiiDA INPUTS =============== # diff --git a/Examples/sscha_and_aiida/run_flare_sscha.py b/Examples/sscha_and_aiida/run_flare_sscha.py index 277befb0..a9963d6d 100644 --- a/Examples/sscha_and_aiida/run_flare_sscha.py +++ b/Examples/sscha_and_aiida/run_flare_sscha.py @@ -17,28 +17,33 @@ def main(): """Run with FLARE + SSCHA @ NPT.""" # =========== GENERAL INPUTS =============== # np.random.seed(0) - number_of_configurations = 50 - max_iterations = 10 - temperature_i = 0 - temperature_f = 0 - temperature_step = 10 - pressure = 0 - meaningful_factor = 0.5 - kong_liu_ratio = 0.5 - minimization_step = 0.1 - supercell = [2,2,2] - restart_from_previous_dyn = False - restart_from_ens = False + structure_filename = 'Si.pwi' + number_of_configurations = 50 + max_iterations = 10 + temperature_i = 300 + temperature_f = 300 + temperature_step = 10 + pressure = 0 + meaningful_factor = 0.01 + kong_liu_ratio = 0.5 + minimization_step = 0.1 + supercell = [2,2,2] + restart_from_previous_dyn = True + restart_from_ens = False - atoms = read('./Si.pwi') - structure = Structure() - structure.generate_from_ase_atoms(atoms) + atoms = read(structure_filename) # =========== FLARE MODEL =============== # - flare_calc, _ = SGP_Calculator.from_file('./model.json') + flare_calc, _ = SGP_Calculator.from_file('./otf_run_flare.json') # =========== DYNAMICAL MATRIX =============== # - dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) + dyn = Phonons("Si-dynamical-matrix", nqirr=3) + + # (*) If you have a pre-existing model, you can compute the dynamical matrix with it + # structure = Structure() + # structure.generate_from_ase_atoms(atoms) + # dyn = compute_phonons_finite_displacements(structure, flare_calc, supercell=supercell) + dyn.Symmetrize() dyn.ForcePositiveDefinite() From 6eb1ce35efa5c56a7bb7190dd229d66e10369088 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Wed, 21 Jan 2026 12:00:47 +0000 Subject: [PATCH 17/22] Examples: update active learning installation instructions --- Examples/sscha_and_aiida/README.md | 44 +++++++++++++++++++++++++----- 1 file changed, 37 insertions(+), 7 deletions(-) diff --git a/Examples/sscha_and_aiida/README.md b/Examples/sscha_and_aiida/README.md index 4bbe9bed..7ffff922 100644 --- a/Examples/sscha_and_aiida/README.md +++ b/Examples/sscha_and_aiida/README.md @@ -1,20 +1,31 @@ # Instructions -We provide here the script `run_aiida_sscha.py`, which performs a thermal expansion calculation using SSCHA and aiida-quantumespresso. +We provide here some scripts to run SSCHA using AiiDA, FLARE machine-learning potential, and a combination of the two as on-the-fly active learning. -It is preferable to execute the example that you already have some experience with both the SSCHA and AiiDA-QuantumEspresso codes. Nevertheless, you can try following the instructions and to run the example. +* `run_aiida_sscha.py`, which performs a thermal expansion calculation using SSCHA and aiida-quantumespresso. +* `run_flare_sscha.py`, which performs a thermal expansion calculation using SSCHA and FLARE machine-learning interatomic potential. +* `run_aiida_flare_sscha.py`, which performs an on-the-fly active learning SSCHA calculation using aiida-quantumespresso for DFT and FLARE as the ML potential. + +It is preferable to execute the example that you already have some experience with both the SSCHA and AiiDA-QuantumESPRESSO codes. Nevertheless, you can try following the instructions and to run the example. ## Installation -We recommend to install all the packages via `mamba` (which is based on top of `conda`). After having installed `mamba`, you can simply run the following: +We recommend to install all the packages via `mamba` (which is based on `conda`). After having installed `mamba`, you can simply run the following: ```console -> mamba create -n aiida-sscha -c conda-forge python gfortran libblas lapack openmpi julia openmpi-mpicc pip numpy scipy spglib aiida-core -> pip install ase quippy-ase cellconstructor python-sscha aiida-quantumespresso aiida-pseudo -> mamba activate aiida-sscha +> mamba create -n sscha-aiida -c conda-forge python gfortran "blas=*=openblas" openblas lapack julia pip numpy scipy spglib pkg-config aiida-core +> pip install ase cellconstructor python-sscha aiida-quantumespresso aiida-pseudo +> mamba activate sscha-aiida ``` +Then, you should configure an AiiDA profile and the pw.x code in order to use the example script (see also Prerequisites section). -Then, you should configure an AiiDA profile in order to use the example script (see also Prerequisites section). +For on-the-fly active learning you also need the FLARE package: + +```console +> git clone --depth 1 https://github.com/mir-group/flare.git +> cd flare +> pip install . +``` ## Prerequisites @@ -23,6 +34,7 @@ You need to have installed in the same environment: - `cellconstructor` - `aiida-core` - `aiida-quantumespresso` +- (optional, for active learning) `mir-flare` For the AiiDA part, it is essential the dameon is running and you have: 1. Configured a computer where to run the code (e.g. on your own laptop; see `aiida-core` docs for further details) @@ -33,6 +45,8 @@ Please refer to the aiida-core and aiida-quantumespresso for further installatio ## How-to run +### SSCHA with the aiida-quantumespresso interface + Open the `run_aiida_sscha.py` and change the data according to your needs and local installation. Then simply ```console @@ -45,4 +59,20 @@ Usually an actual production run would take a while. We suggest to use instead > nohup python run_aiida_sscha.py > run_aiida_sscha.log & ``` +or a submit script at glance. + +### On-the-fly active learning SSCHA with aiida-quantumespresso and FLARE interface + +Open the `run_aiida_flare_sscha.py` and change the data according to your needs and local installation. Then simply + +```console +> python run_aiida_flare_sscha.py > run_aiida_sscha.log +``` + +Usually an actual production run would take a while. We suggest to use instead + +```console +> nohup python run_aiida_sscha.py > run_aiida_sscha.log & +``` + or a submit script at glance. \ No newline at end of file From 4aa395423187bba75046c8afc7ceb37ee11fd498 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Fri, 17 Apr 2026 23:16:39 +0000 Subject: [PATCH 18/22] Add quasi-harmonic approximation scripts and notebooks --- Examples/sscha_and_aiida/model.ipynb | 38 ++ Examples/sscha_and_aiida/qha.ipynb | 535 ++++++++++++++++++++++++++ Examples/sscha_and_aiida/qha.py | 143 +++++++ Examples/sscha_and_aiida/qha_flare.py | 172 +++++++++ 4 files changed, 888 insertions(+) create mode 100644 Examples/sscha_and_aiida/qha.ipynb create mode 100644 Examples/sscha_and_aiida/qha.py create mode 100644 Examples/sscha_and_aiida/qha_flare.py diff --git a/Examples/sscha_and_aiida/model.ipynb b/Examples/sscha_and_aiida/model.ipynb index e0ca4f27..f90e1ef9 100644 --- a/Examples/sscha_and_aiida/model.ipynb +++ b/Examples/sscha_and_aiida/model.ipynb @@ -38,6 +38,44 @@ "})" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "from aiida import load_profile\n", + "from aiida.orm import *\n", + "\n", + "from qe_tools import CONSTANTS as C\n", + "\n", + "from ase.io import write, read\n", + "from ase import units\n", + "from ase.calculators.singlepoint import SinglePointCalculator\n", + "\n", + "from flare.atoms import FLARE_Atoms\n", + "from flare.learners.utils import is_std_in_bound, get_env_indices\n", + "from flare.bffs.sgp.calculator import SGP_Calculator\n", + "from flare.bffs.sgp._C_flare import Structure\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "load_profile()\n", + "\n", + "\n", + "plt.rcParams.update({\n", + " 'text.usetex': False,\n", + " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", + " 'pdf.fonttype':42,\n", + " 'font.family':'sans-serif',\n", + " 'font.sans-serif':'Arial',\n", + " 'font.size':14,\n", + " 'mathtext.fontset': 'stixsans',\n", + "})" + ] + }, { "cell_type": "code", "execution_count": 2, diff --git a/Examples/sscha_and_aiida/qha.ipynb b/Examples/sscha_and_aiida/qha.ipynb new file mode 100644 index 00000000..75fa608f --- /dev/null +++ b/Examples/sscha_and_aiida/qha.ipynb @@ -0,0 +1,535 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "from ase import units, Atoms\n", + "from ase.io import read, write\n", + "\n", + "from flare.atoms import FLARE_Atoms\n", + "from flare.bffs.sgp.calculator import SGP_Calculator\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.rcParams.update({\n", + " 'text.usetex': False,\n", + " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", + " 'pdf.fonttype':42,\n", + " 'font.family':'sans-serif',\n", + " 'font.sans-serif':'Arial',\n", + " 'font.size':14,\n", + " 'mathtext.fontset': 'stixsans',\n", + "})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load existing FLARE SGP model" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "flare_calc, _ = SGP_Calculator.from_file('./model.json')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Relax using model" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initial volume: 40.04698463143717\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:44 -308.491702 0.1428\n", + "BFGS: 1 08:47:44 -308.492054 0.0277\n", + "BFGS: 2 08:47:44 -308.492068 0.0000\n", + "Final volume 40.25289096824065\n" + ] + } + ], + "source": [ + "from ase.optimize import BFGS\n", + "from ase.constraints import ExpCellFilter\n", + "\n", + "vc_relax = True\n", + "filepath = './Si.pwi'\n", + "\n", + "atoms = read(filepath)\n", + "atoms.calc = flare_calc\n", + "print(\"Initial volume: \", atoms.get_volume())\n", + "\n", + "if vc_relax:\n", + " ecf = ExpCellFilter(atoms, scalar_pressure=0) # 0.05 -> 8 GPa\n", + " optimizer = BFGS(ecf)\n", + "else:\n", + " optimizer = BFGS(atoms=atoms)\n", + "\n", + "optimizer.run(fmax=0.001)\n", + "\n", + "if vc_relax:\n", + " print(\"Final volume\", optimizer.atoms.atoms.get_volume())\n", + "else:\n", + " print(\"Final volume\", optimizer.atoms.get_volume())\n", + "# print(optimizer.atoms.atoms.cell)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Atoms(symbols='Si2', pbc=True, cell=[[2.72012603415998, 2.7201260341956384, -8.24495629964982e-10], [2.720126032977409, 3.580758583191355e-10, 2.7201260339410593], [-6.165867862508355e-10, 2.72012603398773, 2.7201260349157224]], initial_magmoms=..., calculator=SGP_Calculator(...))" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "optimizer.atoms.atoms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Scale and relax" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "def scale_and_relax(atoms: Atoms, scale_factor: float, fmax: float = 0.001) -> Atoms:\n", + " \"\"\"Scale and relax the atoms of an ASE Atoms object.\"\"\"\n", + " ase = atoms.copy()\n", + " ase.calc = atoms.calc\n", + " ase.set_cell(ase.get_cell() * float(scale_factor) ** (1 / 3), scale_atoms=True)\n", + " \n", + " optimizer = BFGS(atoms=ase)\n", + " optimizer.run(fmax=fmax)\n", + " \n", + " return optimizer.atoms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## EOS" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Step Time Energy fmax\n", + "BFGS: 0 08:47:47 -307.917760 0.0000\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.047158 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.162612 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.262466 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.345277 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.409976 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.455967 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.483180 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.492068 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.483570 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.459045 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.420192 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.368954 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.307415 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.237695 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.161849 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -308.081758 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -307.999028 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -307.914883 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -307.830063 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:47:48 -307.744717 0.0000\n", + "Minimum at: 40.25289096824065\n" + ] + } + ], + "source": [ + "scale_factors = np.arange(0.8,1.325,0.025)\n", + "\n", + "energies = []\n", + "volumes = []\n", + "for scale_factor in scale_factors:\n", + " scaled_atoms = scale_and_relax(atoms, scale_factor)\n", + " energies.append(scaled_atoms.get_potential_energy())\n", + " volumes.append(scaled_atoms.get_volume())\n", + "\n", + "print(\"Minimum at: \", volumes[energies.index(min(energies))])" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "np.savetxt('./e-v.dat', np.array([volumes, energies]).T)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1,1)\n", + "\n", + "# --- Energies\n", + "ax.plot(volumes, energies, 'bo')\n", + "\n", + "ax.set_xlabel('V (Ang^3)')\n", + "ax.set_ylabel('E (eV)')\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Phonons using Phonopy and FLARE" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "def run_phonons(atoms, filename: str = None):\n", + " \"\"\"Run phonons using Phonopy.\"\"\"\n", + " from ase.atoms import Atoms\n", + " from phonopy import Phonopy\n", + " from phonopy.structure.atoms import PhonopyAtoms\n", + "\n", + " # ================================= INPUTS ======================================= #\n", + " supercell_size = 4\n", + " distance = 0.01 # in Angstrom\n", + " symmetrize = False\n", + " conventional = True\n", + " primitive_matrix = None\n", + " # primitive_matrix = 'auto'\n", + " # ================================================================================ #\n", + "\n", + " supercell_matrix = [supercell_size]*3\n", + " if conventional:\n", + " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", + "\n", + " unitcell = PhonopyAtoms(\n", + " symbols=atoms.get_chemical_symbols(),\n", + " numbers=atoms.get_atomic_numbers(),\n", + " scaled_positions=atoms.get_scaled_positions(),\n", + " cell=atoms.get_cell(),\n", + " pbc=True,\n", + " )\n", + "\n", + " ph = Phonopy(\n", + " unitcell=unitcell,\n", + " primitive_matrix=primitive_matrix,\n", + " supercell_matrix=supercell_matrix,\n", + " )\n", + "\n", + " ph.generate_displacements(distance=distance) \n", + " supercells = ph.supercells_with_displacements\n", + "\n", + " sets_of_forces = []\n", + " for supercell in supercells:\n", + " cell, scaled_positions, numbers = supercell.totuple()\n", + " supercell_atoms = Atoms(\n", + " cell=cell,\n", + " scaled_positions=scaled_positions,\n", + " numbers=numbers,\n", + " calculator=flare_calc\n", + " )\n", + " sets_of_forces.append(supercell_atoms.get_forces())\n", + "\n", + " ph.forces = sets_of_forces\n", + " ph.produce_force_constants()\n", + " return ph" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_71403/3093414531.py:20: DeprecationWarning: PhonopyAtoms.__init__ parameter of pbc is deprecated. It is considered always True.\n", + " unitcell = PhonopyAtoms(\n", + "/opt/conda/lib/python3.10/site-packages/seekpath/hpkot/__init__.py:156: DeprecationWarning: dict interface is deprecated. Use attribute interface instead\n", + " conv_lattice = dataset['std_lattice']\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "scaled_atoms = atoms.copy()\n", + "ph = run_phonons(atoms)\n", + "ph.auto_band_structure(plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Quasi-harmonic approximation" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "def run_phonons(atoms, filename: str = None):\n", + " \"\"\"Run phonons using Phonopy.\"\"\"\n", + " from ase.atoms import Atoms\n", + " from phonopy import Phonopy\n", + " from phonopy.structure.atoms import PhonopyAtoms\n", + "\n", + " # ================================= INPUTS ======================================= #\n", + " supercell_size = 4\n", + " distance = 0.01 # in Angstrom\n", + " t_min = 0 # Kelvin\n", + " t_max = 300 # Kelvin\n", + " symmetrize = False\n", + " conventional = True\n", + " primitive_matrix = None\n", + " thermal_properties = True\n", + " # primitive_matrix = 'auto'\n", + " # ================================================================================ #\n", + "\n", + " supercell_matrix = [supercell_size]*3\n", + " if conventional:\n", + " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", + "\n", + " unitcell = PhonopyAtoms(\n", + " symbols=atoms.get_chemical_symbols(),\n", + " numbers=atoms.get_atomic_numbers(),\n", + " scaled_positions=atoms.get_scaled_positions(),\n", + " cell=atoms.get_cell(),\n", + " )\n", + "\n", + " ph = Phonopy(\n", + " unitcell=unitcell,\n", + " primitive_matrix=primitive_matrix,\n", + " supercell_matrix=supercell_matrix,\n", + " )\n", + "\n", + " ph.generate_displacements(distance=distance)\n", + " supercells = ph.supercells_with_displacements\n", + "\n", + " sets_of_forces = []\n", + " for supercell in supercells:\n", + " cell, scaled_positions, numbers = supercell.totuple()\n", + " supercell_atoms = Atoms(\n", + " cell=cell,\n", + " scaled_positions=scaled_positions,\n", + " numbers=numbers,\n", + " calculator=flare_calc\n", + " )\n", + " sets_of_forces.append(supercell_atoms.get_forces())\n", + "\n", + " ph.forces = sets_of_forces\n", + " ph.produce_force_constants()\n", + "\n", + " if symmetrize:\n", + " ph.symmetrize_force_constants()\n", + " ph.symmetrize_force_constants_by_space_group()\n", + " \n", + " if thermal_properties:\n", + " ph.run_mesh(mesh=100)\n", + " ph.run_thermal_properties(t_min=t_min, t_max=t_max)\n", + " ph.thermal_properties.write_yaml(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Step Time Energy fmax\n", + "BFGS: 0 08:48:15 -307.917760 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:18 -308.047158 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:21 -308.162612 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:24 -308.262466 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:27 -308.345277 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:30 -308.409976 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:34 -308.455967 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:37 -308.483180 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:40 -308.492068 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:43 -308.483570 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:46 -308.459045 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:49 -308.420192 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:52 -308.368954 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:56 -308.307415 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:48:59 -308.237695 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:02 -308.161849 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:05 -308.081758 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:08 -307.999028 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:11 -307.914883 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:14 -307.830063 0.0000\n", + " Step Time Energy fmax\n", + "BFGS: 0 08:49:17 -307.744717 0.0000\n" + ] + } + ], + "source": [ + "start_index = -energies.index(min(energies))\n", + "for scale_factor in scale_factors:\n", + " scaled_atoms = scale_and_relax(atoms, scale_factor)\n", + " run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}')\n", + " start_index += 1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.18" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Examples/sscha_and_aiida/qha.py b/Examples/sscha_and_aiida/qha.py new file mode 100644 index 00000000..6c32b4cc --- /dev/null +++ b/Examples/sscha_and_aiida/qha.py @@ -0,0 +1,143 @@ +"""Script to run QHA with FLARE calculator.""" +import numpy as np + +from ase import units, Atoms +from ase.io import read +from ase.optimize import BFGS +from ase.constraints import ExpCellFilter + +from phonopy import Phonopy +from phonopy.structure.atoms import PhonopyAtoms + +from flare.bffs.sgp.calculator import SGP_Calculator +from flare.atoms import FLARE_Atoms + +structure_filepath = 'Si.pwi' +model_filepath = 'model.json' +initial_vcrelax = True +fmax = 0.001 +scale_i = 0.8 +scale_f = 1.2 +scale_step = 12 +supercell_matrix = [4, 4, 4] +distance = 0.01 +t_min = 0 +t_max = 300 +symmetrize = True +primitive_matrix = None +mesh = 100 +unitcell0 = read(structure_filepath) + +flare_calc, _ = SGP_Calculator.from_file(model_filepath) +unitcell0.calc = flare_calc + +def run() -> None: + """Run QHA calculation.""" + # Initial optimization + print("Running initial geometry optimization...", flush=True) + if initial_vcrelax: + print("Initial volume: ", unitcell0.get_volume(), flush=True) + unitcell = geometry_optimization( + unitcell0, + vcrelax=initial_vcrelax, + fmax=fmax, + ) + if initial_vcrelax: + print("Final volume: ", unitcell.get_volume(), flush=True) + + # Run equation of state + print("Running equation of state...", flush=True) + all_scaled_atoms, energies = run_eos(unitcell) + + print("Running phonons for each volume...") + start_index = -energies.index(min(energies)) + for scaled_atoms in all_scaled_atoms: + phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}') + start_index += 1 + print("Run completed") + +def run_eos(unitcell: Atoms) -> tuple[tuple[Atoms], list]: + """Run equation of states.""" + energies, volumes = [], [] + all_scaled_atoms = [] + + scale_factors = np.linspace(scale_i, scale_f, scale_step) + + for scale_factor in scale_factors: + scaled_atoms = scale_and_relax(unitcell, scale_factor, fmax=fmax) + all_scaled_atoms.append(scaled_atoms) + energies.append(scaled_atoms.get_potential_energy()) + volumes.append(scaled_atoms.get_volume()) + + np.savetxt('./e-v.dat', np.array([volumes, energies]).T) + + return all_scaled_atoms, energies + +def phonons(atoms: Atoms, filename: str = None) -> None: + """Run phonons using Phonopy.""" + unitcell = PhonopyAtoms( + symbols=atoms.get_chemical_symbols(), + numbers=atoms.get_atomic_numbers(), + scaled_positions=atoms.get_scaled_positions(), + cell=atoms.get_cell(), + ) + + ph = Phonopy( + unitcell=unitcell, + primitive_matrix=primitive_matrix, + supercell_matrix=supercell_matrix, + ) + + ph.generate_displacements(distance=distance) + supercells = ph.supercells_with_displacements + + sets_of_forces = [] + for supercell in supercells: + cell, scaled_positions, numbers = supercell.totuple() + supercell_atoms = Atoms( + cell=cell, + scaled_positions=scaled_positions, + numbers=numbers, + calculator=flare_calc, + ) + sets_of_forces.append(supercell_atoms.get_forces()) + + ph.forces = sets_of_forces + ph.produce_force_constants() + + if symmetrize: + ph.symmetrize_force_constants() + ph.symmetrize_force_constants_by_space_group() + + ph.run_mesh(mesh=mesh) + ph.run_thermal_properties(t_min=t_min, t_max=t_max) + ph.thermal_properties.write_yaml(filename) + + +def geometry_optimization(atoms: Atoms, vcrelax: bool = False, fmax: float = 0.001) -> Atoms: + """Optimize geometry of the given atoms.""" + if vcrelax: + ecf = ExpCellFilter(atoms, scalar_pressure=0) + optimizer = BFGS(ecf) + else: + optimizer = BFGS(atoms=atoms) + + optimizer.run(fmax=fmax) + + if vcrelax: + return optimizer.atoms.atoms + return optimizer.atoms + + +def scale_and_relax(atoms: Atoms, scale_factor: float, fmax: float = 0.001) -> Atoms: + """Scale and relax the atoms of an ASE Atoms object.""" + ase = atoms.copy() + ase.calc = atoms.calc + ase.set_cell(ase.get_cell() * float(scale_factor) ** (1 / 3), scale_atoms=True) + + return geometry_optimization(ase, vcrelax=False, fmax=fmax) + + +if __name__ == "__main__": + run() + \ No newline at end of file diff --git a/Examples/sscha_and_aiida/qha_flare.py b/Examples/sscha_and_aiida/qha_flare.py new file mode 100644 index 00000000..53d0f7a4 --- /dev/null +++ b/Examples/sscha_and_aiida/qha_flare.py @@ -0,0 +1,172 @@ +"""Script to run QHA with FLARE calculator.""" +import numpy as np + +from ase import units, Atoms +from ase.io import read +from ase.optimize import BFGS +from ase.constraints import ExpCellFilter + +from phonopy import Phonopy +from phonopy.structure.atoms import PhonopyAtoms + +from flare.bffs.sgp.calculator import SGP_Calculator +from flare.atoms import FLARE_Atoms + + +class QHA: + """Run QHA with FLARE calculator.""" + + def __init__( + self, + structure_filepath = 'Si.pwi', + model_filepath = 'model.json', + initial_vcrelax = False, + fmax = 0.001, + unitcell = None, + scale_i = 0.94, + scale_f = 1.06, + scale_step = 12, + supercell_matrix = [2, 2, 2], + distance = 0.01, + t_min = 0, + t_max = 300, + symmetrize = False, + primitive_matrix = None, + mesh = 100, + ): + """Constructor of the class.""" + self.initial_vcrelax = initial_vcrelax + self.fmax = fmax + self.unitcell = FLARE_Atoms.from_ase_atoms(read(structure_filepath)) + self.scale_i = scale_i + self.scale_f = scale_f + self.scale_step = scale_step + self.supercell_matrix = supercell_matrix + self.distance = distance + self.t_min = t_min + self.t_max = t_max + self.symmetrize = symmetrize + self.primitive_matrix = primitive_matrix + self.mesh = mesh + + flare_calc, _ = SGP_Calculator.from_file(model_filepath) + self.unitcell.calc = flare_calc + + def run(self) -> None: + """Run QHA calculation.""" + print(self.unitcell.get_potential_energy(), flush=True) + # Initial optimization + print("Running initial geometry optimization...", flush=True) + if self.initial_vcrelax: + print("Initial volume: ", self.unitcell.get_volume(), flush=True) + self.unitcell = geometry_optimization( + self.unitcell, + vcrelax=self.initial_vcrelax, + fmax=self.fmax, + ) + if self.initial_vcrelax: + print("Final volume: ", self.unitcell.get_volume(), flush=True) + + # Run equation of state + print("Running equation of state...", flush=True) + all_scaled_atoms, energies = self.run_eos() + + print("Running phonons for each volume...") + start_index = -energies.index(min(energies)) + for scaled_atoms in all_scaled_atoms: + self.phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}') + start_index += 1 + + print("Run completed") + + def run_eos(self) -> tuple[tuple[Atoms], list]: + """Run equation of states.""" + energies, volumes = [], [] + all_scaled_atoms = [] + + scale_factors = np.linspace(self.scale_i, self.scale_f, self.scale_step) + + for scale_factor in scale_factors: + scaled_atoms = scale_and_relax(self.unitcell, scale_factor, fmax=self.fmax) + all_scaled_atoms.append(scaled_atoms) + energies.append(scaled_atoms.get_potential_energy()) + volumes.append(scaled_atoms.get_volume()) + + np.savetxt('./e-v.dat', np.array([volumes, energies]).T) + + return all_scaled_atoms, energies + + def phonons(self, atoms: Atoms, filename: str = None) -> None: + """Run phonons using Phonopy.""" + unitcell = PhonopyAtoms( + symbols=atoms.get_chemical_symbols(), + numbers=atoms.get_atomic_numbers(), + scaled_positions=atoms.get_scaled_positions(), + cell=atoms.get_cell(), + ) + + ph = Phonopy( + unitcell=unitcell, + primitive_matrix=self.primitive_matrix, + supercell_matrix=self.supercell_matrix, + ) + + ph.generate_displacements(distance=self.distance) + supercells = ph.supercells_with_displacements + + sets_of_forces = [] + for supercell in supercells: + cell, scaled_positions, numbers = supercell.totuple() + supercell_atoms = Atoms( + cell=cell, + scaled_positions=scaled_positions, + numbers=numbers, + calculator=self.flare_calc, + ) + sets_of_forces.append(supercell_atoms.get_forces()) + + ph.forces = sets_of_forces + ph.produce_force_constants() + + if self.symmetrize: + ph.symmetrize_force_constants() + ph.symmetrize_force_constants_by_space_group() + + ph.run_mesh(mesh=self.mesh) + ph.run_thermal_properties(t_min=self.t_min, t_max=self.t_max) + ph.thermal_properties.write_yaml(filename) + + +def geometry_optimization( + atoms: Atoms, + vcrelax: bool = False, + fmax: float = 0.001, +) -> Atoms: + """Optimize geometry of the given atoms.""" + print("I am in opt", flush=True) + print(atoms.calc) + if vcrelax: + ecf = ExpCellFilter(atoms, scalar_pressure=0) + optimizer = BFGS(ecf) + else: + optimizer = BFGS(atoms=atoms) + print("Running opt", flush=True) + optimizer.run(fmax=fmax) + print("I almost finished in opt", flush=True) + + if vcrelax: + return optimizer.atoms.atoms + return optimizer.atoms + + +def scale_and_relax(atoms: Atoms, scale_factor: float, fmax: float = 0.001) -> Atoms: + """Scale and relax the atoms of an ASE Atoms object.""" + ase = atoms.copy() + ase.calc = atoms.calc + ase.set_cell(ase.get_cell() * float(scale_factor) ** (1 / 3), scale_atoms=True) + + return geometry_optimization(ase, vcrelax=False, fmax=fmax) + + +QHA().run() + \ No newline at end of file From 45977bc27c14477505c0ae66d3d7064204afb5e8 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Fri, 17 Apr 2026 23:50:46 +0000 Subject: [PATCH 19/22] Install mir-flare after installing BLAS library --- .github/workflows/python-testsuite.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/python-testsuite.yml b/.github/workflows/python-testsuite.yml index 263bd209..5742c3b9 100644 --- a/.github/workflows/python-testsuite.yml +++ b/.github/workflows/python-testsuite.yml @@ -36,7 +36,6 @@ jobs: run: | python -m pip install --upgrade pip pip install flake8 pytest~=6.0 pgtest~=1.3 aiida-core~=2.3 aiida-quantumespresso~=4.3 - pip install git+https://github.com/mir-group/flare.git@development if [ ${{matrix.python-version}} -eq 2.7 ]; then pip install -r requirements2.txt; else pip install -r requirements.txt; fi aiida-pseudo install @@ -52,6 +51,7 @@ jobs: run: | sudo apt-get update sudo apt-get install git gfortran libblas-dev liblapack-dev + pip install mir-flare git clone https://github.com/SSCHAcode/CellConstructor.git pip install meson meson-python ninja cd CellConstructor From 3aceeac0d1c65e0b7cc5b16fe761cc3f31cdd717 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Fri, 17 Apr 2026 23:55:53 +0000 Subject: [PATCH 20/22] Update protocol names --- Modules/aiida_ensemble.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/Modules/aiida_ensemble.py b/Modules/aiida_ensemble.py index 6dad6768..25cba124 100644 --- a/Modules/aiida_ensemble.py +++ b/Modules/aiida_ensemble.py @@ -2,6 +2,7 @@ """Module for handling automated calculation via aiida-quantumespresso.""" from __future__ import annotations +from typing import Literal from copy import copy, deepcopy import time import sys @@ -37,7 +38,7 @@ class AiiDAEnsemble(Ensemble): def compute_ensemble( # pylint: disable=arguments-renamed self, pw_code: str, - protocol: str['fast', 'moderate', 'precise'] = 'moderate', + protocol: Literal['fast', 'balanced', 'stringent'] = 'balanced', options: dict | None = None, overrides: dict | None = None, group_label: str | None = None, @@ -51,7 +52,7 @@ def compute_ensemble( # pylint: disable=arguments-renamed Args: ---- pw_code: The string associated with the AiiDA code for `pw.x` - protocol: The protocol to be used; available protocols are 'fast', 'moderate' and 'precise' + protocol: The protocol to be used; available protocols are 'fast', 'balanced' and 'stringent' options: The options for the calculations, such as the resources, wall-time, etc. overrides: The overrides for the :func:`aiida_quantumespresso.workflows.pw.base.PwBaseWorkChain.get_builder_from_protocol` group_label: The group label where to add the submitted nodes for eventual future inspection From 769ddc1653070f5113806202ab59201f88ea7920 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Fri, 17 Apr 2026 23:59:37 +0000 Subject: [PATCH 21/22] Fix example --- Examples/sscha_and_aiida/run_aiida_sscha.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/Examples/sscha_and_aiida/run_aiida_sscha.py b/Examples/sscha_and_aiida/run_aiida_sscha.py index 363bbad2..646e61d6 100644 --- a/Examples/sscha_and_aiida/run_aiida_sscha.py +++ b/Examples/sscha_and_aiida/run_aiida_sscha.py @@ -1,10 +1,4 @@ -start_index = -energies.index(min(energies)) -for scale_factor in scale_factors: - scaled_atoms = atoms.copy() - scaled_atoms.calc = flare_calc - scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True) - run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}') - start_index += 1"""Example of an actual AiiDA-powered SSCHA run.""" +"""Example of an actual AiiDA-powered SSCHA run.""" import os import numpy as np From 0dc0b991d468a087172f0471a4ceaac2c418e326 Mon Sep 17 00:00:00 2001 From: Lorenzo <79980269+bastonero@users.noreply.github.com> Date: Sun, 19 Apr 2026 12:51:22 +0000 Subject: [PATCH 22/22] Remove unnecessary files and notebooks --- .pre-commit-config.yaml | 54 -- Examples/sscha_and_aiida/analysis.ipynb | 107 --- Examples/sscha_and_aiida/debug.ipynb | 211 ------ Examples/sscha_and_aiida/get_sgp.py | 175 ----- Examples/sscha_and_aiida/model.ipynb | 613 ------------------ Examples/sscha_and_aiida/qha.ipynb | 535 --------------- Examples/sscha_and_aiida/qha_flare.py | 172 ----- .../run_aiida_flare_ensemble.py | 85 --- Examples/sscha_and_aiida/write_xyz.ipynb | 377 ----------- 9 files changed, 2329 deletions(-) delete mode 100644 .pre-commit-config.yaml delete mode 100644 Examples/sscha_and_aiida/analysis.ipynb delete mode 100644 Examples/sscha_and_aiida/debug.ipynb delete mode 100644 Examples/sscha_and_aiida/get_sgp.py delete mode 100644 Examples/sscha_and_aiida/model.ipynb delete mode 100644 Examples/sscha_and_aiida/qha.ipynb delete mode 100644 Examples/sscha_and_aiida/qha_flare.py delete mode 100644 Examples/sscha_and_aiida/run_aiida_flare_ensemble.py delete mode 100644 Examples/sscha_and_aiida/write_xyz.ipynb diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml deleted file mode 100644 index 09a819de..00000000 --- a/.pre-commit-config.yaml +++ /dev/null @@ -1,54 +0,0 @@ -repos: -- repo: https://github.com/pre-commit/pre-commit-hooks - rev: 'v4.1.0' - hooks: - - id: double-quote-string-fixer - - id: end-of-file-fixer - - id: fix-encoding-pragma - - id: mixed-line-ending - - id: trailing-whitespace - exclude: >- - (?x)^( - tests/.*.*out| - tests/.*.in$ - )$ - -- repo: https://github.com/ikamensh/flynt/ - rev: '0.76' - hooks: - - id: flynt - -- repo: https://github.com/pycqa/isort - rev: '5.12.0' - hooks: - - id: isort - -- repo: https://github.com/pre-commit/mirrors-yapf - rev: 'v0.32.0' - hooks: - - id: yapf - name: yapf - types: [python] - args: ['-i'] - exclude: &exclude_files > - (?x)^( - docs/.*| - tests/.*(?" - ] - }, - "execution_count": 117, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import scipy, scipy.optimize\n", - "\n", - "# Load the data from the final data file\n", - "temperatures, volumes = np.loadtxt('./thermal_expansion/thermal_expansion.dat', unpack = True)\n", - "volumes2 = np.array([volumes[0]]+volumes[:-1].tolist())\n", - "t_step = 10\n", - "\n", - "# Prepare the figure and plot the V(T) from the sscha data\n", - "plt.figure(dpi = 100)\n", - "# plt.scatter(temperatures, (volumes-volumes2)/(volumes2*t_step), label = \"SSCHA data\")\n", - "plt.scatter(temperatures, volumes, label = \"SSCHA data\")\n", - "\n", - "\n", - "# Evaluate the volume thermal expansion\n", - "# plt.text(0.6, 0.2, r\"$\\alpha_v = \"+\"{:.1f}\".format(vol_thermal_expansion*1e6)+r\"\\times 10^{-6} $ K$^{-1}$\",\n", - "# transform = plt.gca().transAxes)\n", - "\n", - "# Adjust the plot adding labels, legend, and saving in eps\n", - "plt.xlabel(\"Temperature [K]\")\n", - "plt.ylabel(r\"Volume [$\\AA^3$]\")\n", - "plt.legend()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.18" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Examples/sscha_and_aiida/debug.ipynb b/Examples/sscha_and_aiida/debug.ipynb deleted file mode 100644 index 0a12f4a3..00000000 --- a/Examples/sscha_and_aiida/debug.ipynb +++ /dev/null @@ -1,211 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "\n", - "plt.rcParams.update({\n", - " 'text.usetex': False,\n", - " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", - " 'pdf.fonttype':42,\n", - " 'font.family':'sans-serif',\n", - " 'font.sans-serif':'Arial',\n", - " 'font.size':14,\n", - " 'mathtext.fontset': 'stixsans',\n", - "})" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "e1 = np.load('./ensembles_P0_T0/energies_pop1.npy')\n", - "e1_ref = np.load('./ensembles_P0_T0_flare/energies_pop1.npy')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([1.43868396e-05, 1.43867750e-05, 1.43880794e-05, 1.43880354e-05,\n", - " 1.43876365e-05, 1.43876491e-05, 1.43881572e-05, 1.43880628e-05,\n", - " 1.43881299e-05, 1.43880515e-05, 1.43883702e-05, 1.43884091e-05,\n", - " 1.43877871e-05, 1.43878373e-05, 1.43874900e-05, 1.43878636e-05,\n", - " 1.43875186e-05, 1.43875482e-05, 1.43883338e-05, 1.43881900e-05,\n", - " 1.43863038e-05, 1.43861772e-05, 1.43872463e-05, 1.43872393e-05,\n", - " 1.43875951e-05, 1.43876925e-05, 1.43882204e-05, 1.43884404e-05,\n", - " 1.43877097e-05, 1.43877564e-05, 1.43874619e-05, 1.43873153e-05,\n", - " 1.43875307e-05, 1.43875338e-05, 1.43885549e-05, 1.43885293e-05,\n", - " 1.43879409e-05, 1.43879718e-05, 1.43876421e-05, 1.43876900e-05,\n", - " 1.43871590e-05, 1.43871877e-05, 1.43885125e-05, 1.43885110e-05,\n", - " 1.43882812e-05, 1.43883588e-05, 1.43880605e-05, 1.43880690e-05,\n", - " 1.43875240e-05, 1.43878062e-05])" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "e1-e1_ref" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.0" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.abs(e1-e1_ref).max()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "e1 = np.load('./ensembles_P0_T0/xats_pop1.npy')\n", - "e1_ref = np.load('./ensembles_P0_T0_flare/xats_pop1.npy')" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.0" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.abs(e1-e1_ref).max()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "f1 = np.load('./ensembles_P0_T0/forces_pop1.npy')\n", - "f1_ref = np.load('./ensembles_P0_T0_flare/forces_pop1.npy')" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.1266246074947972e-08" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.abs(f1-f1_ref).max()" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "f1 = np.load('./ensembles_P0_T0/stresses_pop1.npy')\n", - "f1_ref = np.load('./ensembles_P0_T0_flare/stresses_pop1.npy')" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.0972052829011716e-11" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.abs(f1-f1_ref).max()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.9.16 ('aiida-sscha')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.16" - }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "dbf713cbd6c5cb781e360dd03dc580f1c4e0f3272ba8f8d2e6f58f9ae4ed7519" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Examples/sscha_and_aiida/get_sgp.py b/Examples/sscha_and_aiida/get_sgp.py deleted file mode 100644 index 6de6d2c9..00000000 --- a/Examples/sscha_and_aiida/get_sgp.py +++ /dev/null @@ -1,175 +0,0 @@ -import numpy as np -from flare.bffs.sgp._C_flare import NormalizedDotProduct, DotProduct, B2 -from flare.bffs.sgp import SGP_Wrapper -from flare.bffs.sgp.calculator import SGP_Calculator -from flare.atoms import FLARE_Atoms -from ase import Atoms -from ase.calculators.lj import LennardJones -from ase.build import make_supercell - -# Define kernel. -sigma_ = 2.0 -power_ = 2.0 -dotprod_kernel_ = DotProduct(sigma_, power_) -normdotprod_kernel_ = NormalizedDotProduct(sigma_, power_) - -# Define remaining parameters for the SGP wrapper. -sigma_e_ = 0.01 -sigma_f_ = 0.1 -sigma_s_ = 0.005 -species_map_ = {6: 0, 8: 1} -single_atom_energies_ = {0: 0, 1: 0} -variance_type_ = "local" -max_iterations_ = 100 -opt_method_ = "L-BFGS-B" -bounds_ = [(None, None), (sigma_e_, None), (None, None), (None, None)] - - -def get_atoms(a=2.0, sc_size=2, numbers=[6, 8]) -> Atoms: - """Return an ase.Atoms instance.""" - cell = np.eye(3) * a - positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) - unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) - multiplier = np.identity(3) * sc_size - atoms = make_supercell(unit_cell, multiplier) - - return atoms - - -def get_random_atoms(a=2.0, sc_size=2, numbers=[6, 8], set_seed: int = 0) -> FLARE_Atoms: - """Create a random structure.""" - if set_seed: - np.random.seed(set_seed) - - atoms = get_atoms(a, sc_size, numbers) - atoms.positions += (2 * np.random.rand(len(atoms), 3) - 1) * 0.05 - flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) - - return flare_atoms - - -def get_isolated_atoms(numbers=[6, 8]) -> FLARE_Atoms: - """Create a random structure.""" - a = 30.0 - cell = np.eye(3) * a - positions = np.array([[0, 0, 0], [1, 1, 1], [a / 2, a / 2, a / 2]]) - if 8 in numbers: - numbers = [6, 8, 8] - else: - numbers = [6, 6, 6] - unit_cell = Atoms(cell=cell, positions=positions, numbers=numbers, pbc=True) - atoms = unit_cell - flare_atoms = FLARE_Atoms.from_ase_atoms(atoms) - - return flare_atoms - - -def get_empty_sgp( - n_types=2, power=2, multiple_cutoff=False, the_map=None, - the_atom_energies=None, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: - """Return an empty SGP model.""" - if kernel_type == "NormalizedDotProduct": - kernel = normdotprod_kernel_ - elif kernel_type == "DotProduct": - kernel = dotprod_kernel_ - - kernel.power = power - - # Define B2 calculator. - cutoff = 5.0 - cutoff_function = "quadratic" - radial_basis = "chebyshev" - radial_hyps = [0.0, cutoff] - cutoff_hyps = [] - cutoff_matrix = cutoff * np.ones((n_types, n_types)) - if multiple_cutoff: - cutoff_matrix += np.eye(n_types) - 1 - - descriptor_settings = [n_types, 8, 4] - b2_calc = B2( - radial_basis, - cutoff_function, - radial_hyps, - cutoff_hyps, - descriptor_settings, - cutoff_matrix, - ) - - species_map = species_map_ if the_map is None else the_map - single_atom_energies = single_atom_energies_ if the_map is None else the_atom_energies - - empty_sgp = SGP_Wrapper( - [kernel], - [b2_calc], - cutoff, - sigma_e_, - sigma_f_, - sigma_s_, - species_map, - single_atom_energies=single_atom_energies, - variance_type=variance_type_, - opt_method=opt_method_, - bounds=bounds_, - max_iterations=max_iterations_, - ) - - return empty_sgp - - -def get_updated_sgp(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Wrapper: - """Return the SGP updated with the new structure properties.""" - if n_types == 1: - numbers = [6, 6] - elif n_types == 2: - numbers = [6, 8] - - sgp = get_empty_sgp(n_types, power, multiple_cutoff, kernel_type) - - # add a random structure to the training set - training_structure = get_random_atoms(numbers=numbers) - training_structure.calc = LennardJones() - - forces = training_structure.get_forces() - energy = training_structure.get_potential_energy() - stress = training_structure.get_stress() - - sgp.update_db( - training_structure, - forces, - custom_range=(1, 2, 3, 4, 5), - energy=energy, - stress=stress, - mode="specific", - rel_e_noise=0.1, - rel_f_noise=0.2, - rel_s_noise=0.1, - ) - - # add an isolated atom to the training data - training_structure = get_isolated_atoms(numbers=numbers) - training_structure.calc = LennardJones() - - forces = training_structure.get_forces() - energy = training_structure.get_potential_energy() - stress = training_structure.get_stress() - - custom_range = [0] - sgp.update_db( - training_structure, - forces, - custom_range=custom_range, - energy=energy, - stress=stress, - mode="specific", - ) - - print("sparse_indices", sgp.sparse_gp.sparse_indices) - - return sgp - - -def get_sgp_calc(n_types=2, power=2, multiple_cutoff=False, kernel_type="NormalizedDotProduct") -> SGP_Calculator: - """Return an SGP calculator, ASE type.""" - sgp = get_updated_sgp(n_types, power, multiple_cutoff, kernel_type) - - return SGP_Calculator(sgp) diff --git a/Examples/sscha_and_aiida/model.ipynb b/Examples/sscha_and_aiida/model.ipynb deleted file mode 100644 index f90e1ef9..00000000 --- a/Examples/sscha_and_aiida/model.ipynb +++ /dev/null @@ -1,613 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "from aiida import load_profile\n", - "from aiida.orm import *\n", - "\n", - "from qe_tools import CONSTANTS as C\n", - "\n", - "from ase.io import write, read\n", - "from ase import units\n", - "from ase.calculators.singlepoint import SinglePointCalculator\n", - "\n", - "from flare.atoms import FLARE_Atoms\n", - "from flare.learners.utils import is_std_in_bound, get_env_indices\n", - "from flare.bffs.sgp.calculator import SGP_Calculator\n", - "from flare.bffs.sgp._C_flare import Structure\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "load_profile()\n", - "\n", - "\n", - "plt.rcParams.update({\n", - " 'text.usetex': False,\n", - " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", - " 'pdf.fonttype':42,\n", - " 'font.family':'sans-serif',\n", - " 'font.sans-serif':'Arial',\n", - " 'font.size':14,\n", - " 'mathtext.fontset': 'stixsans',\n", - "})" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "from aiida import load_profile\n", - "from aiida.orm import *\n", - "\n", - "from qe_tools import CONSTANTS as C\n", - "\n", - "from ase.io import write, read\n", - "from ase import units\n", - "from ase.calculators.singlepoint import SinglePointCalculator\n", - "\n", - "from flare.atoms import FLARE_Atoms\n", - "from flare.learners.utils import is_std_in_bound, get_env_indices\n", - "from flare.bffs.sgp.calculator import SGP_Calculator\n", - "from flare.bffs.sgp._C_flare import Structure\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "load_profile()\n", - "\n", - "\n", - "plt.rcParams.update({\n", - " 'text.usetex': False,\n", - " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", - " 'pdf.fonttype':42,\n", - " 'font.family':'sans-serif',\n", - " 'font.sans-serif':'Arial',\n", - " 'font.size':14,\n", - " 'mathtext.fontset': 'stixsans',\n", - "})" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "!export OMP_NUM_THREADS=1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Evaluate a model" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of frames in the set: 91\n" - ] - } - ], - "source": [ - "flare_calc, _ = SGP_Calculator.from_file('./model.json')\n", - "\n", - "atoms_test = read(\"./dataset-sscha.xyz\", index=':')\n", - "atoms_flare = [FLARE_Atoms.from_ase_atoms(atoms) for atoms in atoms_test]\n", - "\n", - "for atoms in atoms_flare:\n", - " atoms.calc = flare_calc\n", - "\n", - "print(f\"Number of frames in the set: {len(atoms_test)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", - " -0.01507365])" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "atoms_flare[0].get_stress(voigt=False)\n", - "at_fl = atoms_flare[0]\n", - "at_fl.stress" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-0.01628743, -0.01507365, -0.00761871],\n", - " [-0.01507365, -0.0065395 , 0.01573904],\n", - " [-0.00761871, 0.01573904, -0.00436347]])" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "at = atoms_test[0]\n", - "at.calc = flare_calc\n", - "at.get_stress(voigt=False)\n", - "# at" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MAE energy: 0.3489 eV\n", - "MAE forces: 0.1379 eV ang-1\n", - "MAE stress: 0.0021 eV ang-3\n" - ] - } - ], - "source": [ - "ref_energy = np.array([atoms.get_potential_energy() for atoms in atoms_test])\n", - "ref_forces = np.array([atoms.get_forces() for atoms in atoms_test])\n", - "ref_stress = np.array([atoms.get_stress() for atoms in atoms_test])\n", - "\n", - "model_energy = np.array([atoms.get_potential_energy() for atoms in atoms_flare])\n", - "model_forces = np.array([atoms.get_forces() for atoms in atoms_flare])\n", - "model_stress = np.array([atoms.get_stress() for atoms in atoms_flare])\n", - "\n", - "mae_energy = np.abs(ref_energy-model_energy).mean()\n", - "mae_forces = np.abs(ref_forces-model_forces).mean()\n", - "mae_stress = np.abs(ref_stress-model_stress).mean()\n", - "\n", - "print(f'MAE energy: {mae_energy:.4f} eV')\n", - "print(f'MAE forces: {mae_forces:.4f} eV ang-1')\n", - "print(f'MAE stress: {mae_stress:.4f} eV ang-3')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", - " -0.01507365]),\n", - " array([-0.01628743, -0.0065395 , -0.00436347, 0.01573904, -0.00761871,\n", - " -0.01507365]))" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "index = 0\n", - "model_stress[index], ref_stress[index]\n", - "# model_forces[index]-ref_forces[index]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot statistics" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans.\n", - "findfont: Generic family 'sans-serif' not found because none of the following families were found: Arial\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(1,2)\n", - "\n", - "# --- Energies\n", - "axs[0].plot(model_energy, ref_energy, 'bo')\n", - "axs[0].plot([ref_energy.min()*1.01, ref_energy.max()*0.99], [ref_energy.min()*1.01, ref_energy.max()*0.99], ls='--', c='gray')\n", - "\n", - "axs[0].set_xlabel('E$_{SGP}}$ (eV)')\n", - "axs[0].set_ylabel('E$_{DFT}$ (eV)')\n", - "\n", - "# --- Forces\n", - "axs[1].plot(model_forces.flatten(), ref_forces.flatten(), 'bo')\n", - "# axs[1].plot([ref_energy.min()*1.01, ref_energy.max()*0.99], [ref_energy.min()*1.01, ref_energy.max()*0.99], ls='--', c='gray')\n", - "\n", - "axs[1].set_xlabel('|F$_{SGP}}$| (eV/Ang)')\n", - "axs[1].set_ylabel('|F$_{DFT}$| (eV/Ang)')\n", - "\n", - "fig.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Relax using model" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Initial volume: 40.04698463143717\n", - " Step Time Energy fmax\n", - "BFGS: 0 09:14:25 -308.491702 0.0000\n" - ] - }, - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from ase.optimize import BFGS\n", - "from ase.constraints import ExpCellFilter\n", - "\n", - "vc_relax = False\n", - "filepath = './Si.pwi'\n", - "\n", - "atoms = read(filepath)\n", - "atoms.calc = flare_calc\n", - "print(\"Initial volume: \", atoms.get_volume())\n", - "\n", - "if vc_relax:\n", - " ecf = ExpCellFilter(atoms, scalar_pressure=0.1) # 0.05 -> 8 GPa\n", - " optimizer = BFGS(ecf)\n", - "else:\n", - " optimizer = BFGS(atoms=atoms)\n", - "\n", - "optimizer.run(fmax=0.001)\n", - "\n", - "# print(\"Final cell\")\n", - "# print(optimizer.atoms.atoms.cell)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## EOS" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Minimum at: 40.04698463143717\n" - ] - } - ], - "source": [ - "scale_factors = np.arange(0.8,1.325,0.025)\n", - "atoms = read(filepath)\n", - "\n", - "energies = []\n", - "volumes = []\n", - "for scale_factor in scale_factors:\n", - " scaled_atoms = atoms.copy()\n", - " scaled_atoms.calc = flare_calc\n", - " scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True)\n", - " energies.append(scaled_atoms.get_potential_energy())\n", - " volumes.append(scaled_atoms.get_volume())\n", - "\n", - "print(\"Minimum at: \", volumes[energies.index(min(energies))])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "np.savetxt('./e-v.dat', np.array([volumes, energies]).T)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1,1)\n", - "\n", - "# --- Energies\n", - "ax.plot(volumes, energies, 'bo')\n", - "\n", - "ax.set_xlabel('V (Ang^3)')\n", - "ax.set_ylabel('E (eV)')\n", - "\n", - "fig.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Phonons using Phonopy and FLARE" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "def run_phonons(atoms, filename: str = None):\n", - " \"\"\"Run phonons using Phonopy.\"\"\"\n", - " from ase.atoms import Atoms\n", - " from phonopy import Phonopy\n", - " from phonopy.structure.atoms import PhonopyAtoms\n", - "\n", - " # ================================= INPUTS ======================================= #\n", - " supercell_size = 4\n", - " distance = 0.01 # in Angstrom\n", - " t_max = 300 # Kelvin\n", - " symmetrize = False\n", - " conventional = True\n", - " primitive_matrix = None\n", - " thermal_properties = True\n", - " # primitive_matrix = 'auto'\n", - " # ================================================================================ #\n", - "\n", - " supercell_matrix = [supercell_size]*3\n", - " if conventional:\n", - " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", - "\n", - " unitcell = PhonopyAtoms(\n", - " symbols=atoms.get_chemical_symbols(),\n", - " numbers=atoms.get_atomic_numbers(),\n", - " scaled_positions=atoms.get_scaled_positions(),\n", - " cell=atoms.get_cell(),\n", - " )\n", - "\n", - " ph = Phonopy(\n", - " unitcell=unitcell,\n", - " primitive_matrix=primitive_matrix,\n", - " supercell_matrix=supercell_matrix,\n", - " )\n", - "\n", - " ph.generate_displacements(distance=distance)\n", - " supercells = ph.get_supercells_with_displacements()\n", - "\n", - " sets_of_forces = []\n", - " for supercell in supercells:\n", - " cell, scaled_positions, numbers = supercell.totuple()\n", - " supercell_atoms = Atoms(\n", - " cell=cell,\n", - " scaled_positions=scaled_positions,\n", - " numbers=numbers,\n", - " calculator=flare_calc\n", - " )\n", - " sets_of_forces.append(supercell_atoms.get_forces())\n", - "\n", - " ph.set_forces(sets_of_forces=sets_of_forces)\n", - " ph.produce_force_constants()\n", - "\n", - " if symmetrize:\n", - " ph.symmetrize_force_constants()\n", - " ph.symmetrize_force_constants_by_space_group()\n", - " \n", - " if thermal_properties:\n", - " ph.run_mesh(mesh=300)\n", - " ph.run_thermal_properties()#t_max=t_max)\n", - " ph.thermal_properties.write_yaml(filename)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "start_index = -energies.index(min(energies))\n", - "for scale_factor in scale_factors:\n", - " scaled_atoms = atoms.copy()\n", - " scaled_atoms.calc = flare_calc\n", - " scaled_atoms.set_cell(scaled_atoms.get_cell() * scale_factor ** (1 / 3), scale_atoms=True)\n", - " run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}')\n", - " start_index += 1" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "def run_phonons(atoms, filename: str = None):\n", - " \"\"\"Run phonons using Phonopy.\"\"\"\n", - " from ase.atoms import Atoms\n", - " from phonopy import Phonopy\n", - " from phonopy.structure.atoms import PhonopyAtoms\n", - "\n", - " # ================================= INPUTS ======================================= #\n", - " supercell_size = 4\n", - " distance = 0.01 # in Angstrom\n", - " symmetrize = False\n", - " conventional = True\n", - " primitive_matrix = None\n", - " # primitive_matrix = 'auto'\n", - " # ================================================================================ #\n", - "\n", - " supercell_matrix = [supercell_size]*3\n", - " if conventional:\n", - " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", - "\n", - " unitcell = PhonopyAtoms(\n", - " symbols=atoms.get_chemical_symbols(),\n", - " numbers=atoms.get_atomic_numbers(),\n", - " scaled_positions=atoms.get_scaled_positions(),\n", - " cell=atoms.get_cell(),\n", - " )\n", - "\n", - " ph = Phonopy(\n", - " unitcell=unitcell,\n", - " primitive_matrix=primitive_matrix,\n", - " supercell_matrix=supercell_matrix,\n", - " )\n", - "\n", - " ph.generate_displacements(distance=distance)\n", - " supercells = ph.get_supercells_with_displacements()\n", - "\n", - " sets_of_forces = []\n", - " for supercell in supercells:\n", - " cell, scaled_positions, numbers = supercell.totuple()\n", - " supercell_atoms = Atoms(\n", - " cell=cell,\n", - " scaled_positions=scaled_positions,\n", - " numbers=numbers,\n", - " calculator=flare_calc\n", - " )\n", - " sets_of_forces.append(supercell_atoms.get_forces())\n", - "\n", - " ph.set_forces(sets_of_forces=sets_of_forces)\n", - " ph.produce_force_constants()\n", - " return ph\n", - "\n", - "scaled_atoms = atoms.copy()\n", - "ph = run_phonons(atoms)\n", - "ph.auto_band_structure(plot=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.8.18 ('base')", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.18" - }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "d4d1e4263499bec80672ea0156c357c1ee493ec2b1c70f0acce89fc37c4a6abe" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Examples/sscha_and_aiida/qha.ipynb b/Examples/sscha_and_aiida/qha.ipynb deleted file mode 100644 index 75fa608f..00000000 --- a/Examples/sscha_and_aiida/qha.ipynb +++ /dev/null @@ -1,535 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "from ase import units, Atoms\n", - "from ase.io import read, write\n", - "\n", - "from flare.atoms import FLARE_Atoms\n", - "from flare.bffs.sgp.calculator import SGP_Calculator\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "plt.rcParams.update({\n", - " 'text.usetex': False,\n", - " # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n", - " 'pdf.fonttype':42,\n", - " 'font.family':'sans-serif',\n", - " 'font.sans-serif':'Arial',\n", - " 'font.size':14,\n", - " 'mathtext.fontset': 'stixsans',\n", - "})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Load existing FLARE SGP model" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "flare_calc, _ = SGP_Calculator.from_file('./model.json')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Relax using model" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Initial volume: 40.04698463143717\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:44 -308.491702 0.1428\n", - "BFGS: 1 08:47:44 -308.492054 0.0277\n", - "BFGS: 2 08:47:44 -308.492068 0.0000\n", - "Final volume 40.25289096824065\n" - ] - } - ], - "source": [ - "from ase.optimize import BFGS\n", - "from ase.constraints import ExpCellFilter\n", - "\n", - "vc_relax = True\n", - "filepath = './Si.pwi'\n", - "\n", - "atoms = read(filepath)\n", - "atoms.calc = flare_calc\n", - "print(\"Initial volume: \", atoms.get_volume())\n", - "\n", - "if vc_relax:\n", - " ecf = ExpCellFilter(atoms, scalar_pressure=0) # 0.05 -> 8 GPa\n", - " optimizer = BFGS(ecf)\n", - "else:\n", - " optimizer = BFGS(atoms=atoms)\n", - "\n", - "optimizer.run(fmax=0.001)\n", - "\n", - "if vc_relax:\n", - " print(\"Final volume\", optimizer.atoms.atoms.get_volume())\n", - "else:\n", - " print(\"Final volume\", optimizer.atoms.get_volume())\n", - "# print(optimizer.atoms.atoms.cell)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Atoms(symbols='Si2', pbc=True, cell=[[2.72012603415998, 2.7201260341956384, -8.24495629964982e-10], [2.720126032977409, 3.580758583191355e-10, 2.7201260339410593], [-6.165867862508355e-10, 2.72012603398773, 2.7201260349157224]], initial_magmoms=..., calculator=SGP_Calculator(...))" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "optimizer.atoms.atoms" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Scale and relax" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [], - "source": [ - "def scale_and_relax(atoms: Atoms, scale_factor: float, fmax: float = 0.001) -> Atoms:\n", - " \"\"\"Scale and relax the atoms of an ASE Atoms object.\"\"\"\n", - " ase = atoms.copy()\n", - " ase.calc = atoms.calc\n", - " ase.set_cell(ase.get_cell() * float(scale_factor) ** (1 / 3), scale_atoms=True)\n", - " \n", - " optimizer = BFGS(atoms=ase)\n", - " optimizer.run(fmax=fmax)\n", - " \n", - " return optimizer.atoms" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## EOS" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Step Time Energy fmax\n", - "BFGS: 0 08:47:47 -307.917760 0.0000\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.047158 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.162612 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.262466 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.345277 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.409976 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.455967 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.483180 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.492068 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.483570 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.459045 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.420192 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.368954 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.307415 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.237695 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.161849 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -308.081758 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -307.999028 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -307.914883 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -307.830063 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:47:48 -307.744717 0.0000\n", - "Minimum at: 40.25289096824065\n" - ] - } - ], - "source": [ - "scale_factors = np.arange(0.8,1.325,0.025)\n", - "\n", - "energies = []\n", - "volumes = []\n", - "for scale_factor in scale_factors:\n", - " scaled_atoms = scale_and_relax(atoms, scale_factor)\n", - " energies.append(scaled_atoms.get_potential_energy())\n", - " volumes.append(scaled_atoms.get_volume())\n", - "\n", - "print(\"Minimum at: \", volumes[energies.index(min(energies))])" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [], - "source": [ - "np.savetxt('./e-v.dat', np.array([volumes, energies]).T)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1,1)\n", - "\n", - "# --- Energies\n", - "ax.plot(volumes, energies, 'bo')\n", - "\n", - "ax.set_xlabel('V (Ang^3)')\n", - "ax.set_ylabel('E (eV)')\n", - "\n", - "fig.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Phonons using Phonopy and FLARE" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [], - "source": [ - "def run_phonons(atoms, filename: str = None):\n", - " \"\"\"Run phonons using Phonopy.\"\"\"\n", - " from ase.atoms import Atoms\n", - " from phonopy import Phonopy\n", - " from phonopy.structure.atoms import PhonopyAtoms\n", - "\n", - " # ================================= INPUTS ======================================= #\n", - " supercell_size = 4\n", - " distance = 0.01 # in Angstrom\n", - " symmetrize = False\n", - " conventional = True\n", - " primitive_matrix = None\n", - " # primitive_matrix = 'auto'\n", - " # ================================================================================ #\n", - "\n", - " supercell_matrix = [supercell_size]*3\n", - " if conventional:\n", - " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", - "\n", - " unitcell = PhonopyAtoms(\n", - " symbols=atoms.get_chemical_symbols(),\n", - " numbers=atoms.get_atomic_numbers(),\n", - " scaled_positions=atoms.get_scaled_positions(),\n", - " cell=atoms.get_cell(),\n", - " pbc=True,\n", - " )\n", - "\n", - " ph = Phonopy(\n", - " unitcell=unitcell,\n", - " primitive_matrix=primitive_matrix,\n", - " supercell_matrix=supercell_matrix,\n", - " )\n", - "\n", - " ph.generate_displacements(distance=distance) \n", - " supercells = ph.supercells_with_displacements\n", - "\n", - " sets_of_forces = []\n", - " for supercell in supercells:\n", - " cell, scaled_positions, numbers = supercell.totuple()\n", - " supercell_atoms = Atoms(\n", - " cell=cell,\n", - " scaled_positions=scaled_positions,\n", - " numbers=numbers,\n", - " calculator=flare_calc\n", - " )\n", - " sets_of_forces.append(supercell_atoms.get_forces())\n", - "\n", - " ph.forces = sets_of_forces\n", - " ph.produce_force_constants()\n", - " return ph" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_71403/3093414531.py:20: DeprecationWarning: PhonopyAtoms.__init__ parameter of pbc is deprecated. It is considered always True.\n", - " unitcell = PhonopyAtoms(\n", - "/opt/conda/lib/python3.10/site-packages/seekpath/hpkot/__init__.py:156: DeprecationWarning: dict interface is deprecated. Use attribute interface instead\n", - " conv_lattice = dataset['std_lattice']\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "scaled_atoms = atoms.copy()\n", - "ph = run_phonons(atoms)\n", - "ph.auto_band_structure(plot=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Quasi-harmonic approximation" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "def run_phonons(atoms, filename: str = None):\n", - " \"\"\"Run phonons using Phonopy.\"\"\"\n", - " from ase.atoms import Atoms\n", - " from phonopy import Phonopy\n", - " from phonopy.structure.atoms import PhonopyAtoms\n", - "\n", - " # ================================= INPUTS ======================================= #\n", - " supercell_size = 4\n", - " distance = 0.01 # in Angstrom\n", - " t_min = 0 # Kelvin\n", - " t_max = 300 # Kelvin\n", - " symmetrize = False\n", - " conventional = True\n", - " primitive_matrix = None\n", - " thermal_properties = True\n", - " # primitive_matrix = 'auto'\n", - " # ================================================================================ #\n", - "\n", - " supercell_matrix = [supercell_size]*3\n", - " if conventional:\n", - " supercell_matrix = np.dot(supercell_size*np.eye(3), -np.array([[1,1,-1],[1,-1,1],[-1,1,1]]) ) # conventional cell\n", - "\n", - " unitcell = PhonopyAtoms(\n", - " symbols=atoms.get_chemical_symbols(),\n", - " numbers=atoms.get_atomic_numbers(),\n", - " scaled_positions=atoms.get_scaled_positions(),\n", - " cell=atoms.get_cell(),\n", - " )\n", - "\n", - " ph = Phonopy(\n", - " unitcell=unitcell,\n", - " primitive_matrix=primitive_matrix,\n", - " supercell_matrix=supercell_matrix,\n", - " )\n", - "\n", - " ph.generate_displacements(distance=distance)\n", - " supercells = ph.supercells_with_displacements\n", - "\n", - " sets_of_forces = []\n", - " for supercell in supercells:\n", - " cell, scaled_positions, numbers = supercell.totuple()\n", - " supercell_atoms = Atoms(\n", - " cell=cell,\n", - " scaled_positions=scaled_positions,\n", - " numbers=numbers,\n", - " calculator=flare_calc\n", - " )\n", - " sets_of_forces.append(supercell_atoms.get_forces())\n", - "\n", - " ph.forces = sets_of_forces\n", - " ph.produce_force_constants()\n", - "\n", - " if symmetrize:\n", - " ph.symmetrize_force_constants()\n", - " ph.symmetrize_force_constants_by_space_group()\n", - " \n", - " if thermal_properties:\n", - " ph.run_mesh(mesh=100)\n", - " ph.run_thermal_properties(t_min=t_min, t_max=t_max)\n", - " ph.thermal_properties.write_yaml(filename)" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Step Time Energy fmax\n", - "BFGS: 0 08:48:15 -307.917760 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:18 -308.047158 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:21 -308.162612 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:24 -308.262466 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:27 -308.345277 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:30 -308.409976 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:34 -308.455967 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:37 -308.483180 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:40 -308.492068 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:43 -308.483570 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:46 -308.459045 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:49 -308.420192 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:52 -308.368954 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:56 -308.307415 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:48:59 -308.237695 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:02 -308.161849 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:05 -308.081758 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:08 -307.999028 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:11 -307.914883 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:14 -307.830063 0.0000\n", - " Step Time Energy fmax\n", - "BFGS: 0 08:49:17 -307.744717 0.0000\n" - ] - } - ], - "source": [ - "start_index = -energies.index(min(energies))\n", - "for scale_factor in scale_factors:\n", - " scaled_atoms = scale_and_relax(atoms, scale_factor)\n", - " run_phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}')\n", - " start_index += 1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.18" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Examples/sscha_and_aiida/qha_flare.py b/Examples/sscha_and_aiida/qha_flare.py deleted file mode 100644 index 53d0f7a4..00000000 --- a/Examples/sscha_and_aiida/qha_flare.py +++ /dev/null @@ -1,172 +0,0 @@ -"""Script to run QHA with FLARE calculator.""" -import numpy as np - -from ase import units, Atoms -from ase.io import read -from ase.optimize import BFGS -from ase.constraints import ExpCellFilter - -from phonopy import Phonopy -from phonopy.structure.atoms import PhonopyAtoms - -from flare.bffs.sgp.calculator import SGP_Calculator -from flare.atoms import FLARE_Atoms - - -class QHA: - """Run QHA with FLARE calculator.""" - - def __init__( - self, - structure_filepath = 'Si.pwi', - model_filepath = 'model.json', - initial_vcrelax = False, - fmax = 0.001, - unitcell = None, - scale_i = 0.94, - scale_f = 1.06, - scale_step = 12, - supercell_matrix = [2, 2, 2], - distance = 0.01, - t_min = 0, - t_max = 300, - symmetrize = False, - primitive_matrix = None, - mesh = 100, - ): - """Constructor of the class.""" - self.initial_vcrelax = initial_vcrelax - self.fmax = fmax - self.unitcell = FLARE_Atoms.from_ase_atoms(read(structure_filepath)) - self.scale_i = scale_i - self.scale_f = scale_f - self.scale_step = scale_step - self.supercell_matrix = supercell_matrix - self.distance = distance - self.t_min = t_min - self.t_max = t_max - self.symmetrize = symmetrize - self.primitive_matrix = primitive_matrix - self.mesh = mesh - - flare_calc, _ = SGP_Calculator.from_file(model_filepath) - self.unitcell.calc = flare_calc - - def run(self) -> None: - """Run QHA calculation.""" - print(self.unitcell.get_potential_energy(), flush=True) - # Initial optimization - print("Running initial geometry optimization...", flush=True) - if self.initial_vcrelax: - print("Initial volume: ", self.unitcell.get_volume(), flush=True) - self.unitcell = geometry_optimization( - self.unitcell, - vcrelax=self.initial_vcrelax, - fmax=self.fmax, - ) - if self.initial_vcrelax: - print("Final volume: ", self.unitcell.get_volume(), flush=True) - - # Run equation of state - print("Running equation of state...", flush=True) - all_scaled_atoms, energies = self.run_eos() - - print("Running phonons for each volume...") - start_index = -energies.index(min(energies)) - for scaled_atoms in all_scaled_atoms: - self.phonons(scaled_atoms, filename=f'./thermal_properties.yaml-{start_index}') - start_index += 1 - - print("Run completed") - - def run_eos(self) -> tuple[tuple[Atoms], list]: - """Run equation of states.""" - energies, volumes = [], [] - all_scaled_atoms = [] - - scale_factors = np.linspace(self.scale_i, self.scale_f, self.scale_step) - - for scale_factor in scale_factors: - scaled_atoms = scale_and_relax(self.unitcell, scale_factor, fmax=self.fmax) - all_scaled_atoms.append(scaled_atoms) - energies.append(scaled_atoms.get_potential_energy()) - volumes.append(scaled_atoms.get_volume()) - - np.savetxt('./e-v.dat', np.array([volumes, energies]).T) - - return all_scaled_atoms, energies - - def phonons(self, atoms: Atoms, filename: str = None) -> None: - """Run phonons using Phonopy.""" - unitcell = PhonopyAtoms( - symbols=atoms.get_chemical_symbols(), - numbers=atoms.get_atomic_numbers(), - scaled_positions=atoms.get_scaled_positions(), - cell=atoms.get_cell(), - ) - - ph = Phonopy( - unitcell=unitcell, - primitive_matrix=self.primitive_matrix, - supercell_matrix=self.supercell_matrix, - ) - - ph.generate_displacements(distance=self.distance) - supercells = ph.supercells_with_displacements - - sets_of_forces = [] - for supercell in supercells: - cell, scaled_positions, numbers = supercell.totuple() - supercell_atoms = Atoms( - cell=cell, - scaled_positions=scaled_positions, - numbers=numbers, - calculator=self.flare_calc, - ) - sets_of_forces.append(supercell_atoms.get_forces()) - - ph.forces = sets_of_forces - ph.produce_force_constants() - - if self.symmetrize: - ph.symmetrize_force_constants() - ph.symmetrize_force_constants_by_space_group() - - ph.run_mesh(mesh=self.mesh) - ph.run_thermal_properties(t_min=self.t_min, t_max=self.t_max) - ph.thermal_properties.write_yaml(filename) - - -def geometry_optimization( - atoms: Atoms, - vcrelax: bool = False, - fmax: float = 0.001, -) -> Atoms: - """Optimize geometry of the given atoms.""" - print("I am in opt", flush=True) - print(atoms.calc) - if vcrelax: - ecf = ExpCellFilter(atoms, scalar_pressure=0) - optimizer = BFGS(ecf) - else: - optimizer = BFGS(atoms=atoms) - print("Running opt", flush=True) - optimizer.run(fmax=fmax) - print("I almost finished in opt", flush=True) - - if vcrelax: - return optimizer.atoms.atoms - return optimizer.atoms - - -def scale_and_relax(atoms: Atoms, scale_factor: float, fmax: float = 0.001) -> Atoms: - """Scale and relax the atoms of an ASE Atoms object.""" - ase = atoms.copy() - ase.calc = atoms.calc - ase.set_cell(ase.get_cell() * float(scale_factor) ** (1 / 3), scale_atoms=True) - - return geometry_optimization(ase, vcrelax=False, fmax=fmax) - - -QHA().run() - \ No newline at end of file diff --git a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py b/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py deleted file mode 100644 index 3cfcb5b5..00000000 --- a/Examples/sscha_and_aiida/run_aiida_flare_ensemble.py +++ /dev/null @@ -1,85 +0,0 @@ -"""Test for an actual AiiDA-FLARE-powered ensemble computation.""" -import numpy as np - -from ase import Atoms -from ase.build import make_supercell -from ase.calculators.lj import LennardJones - -from cellconstructor.Phonons import compute_phonons_finite_displacements -from cellconstructor.Structure import Structure -from sscha.aiida_ensemble import AiiDAEnsemble - -from aiida import load_profile -from aiida_quantumespresso.common.types import ElectronicType - -from flare.bffs.sgp.calculator import SGP_Calculator -from get_sgp import get_empty_sgp - -load_profile() - - -def main(): - """Run with AiiDA-QuantumESPRESSO + FLARE some ensemble configuration for testing.""" - # =========== GENERAL INPUTS =============== # - np.random.seed(0) - number_of_configurations = 10 - batch_number = 3 - check_time = 3 - temperature = 0.0 - - # =========== AiiDA ENSEMBLE =============== # - a, sc_size, numbers = 2.0, 1, [6, 8] - cell = np.eye(3) * a - positions = np.array([[0, 0, 0], [0.5 , 0.5, 0.5]]) - unit_cell = Atoms(cell=cell, scaled_positions=positions, numbers=numbers, pbc=True) - multiplier = np.identity(3) * sc_size - atoms = make_supercell(unit_cell, multiplier) - - structure = Structure() - structure.generate_from_ase_atoms(atoms) - - dyn = compute_phonons_finite_displacements(structure, LennardJones(), supercell=[1,1,1]) - dyn.Symmetrize() - dyn.ForcePositiveDefinite() - - ensemble = AiiDAEnsemble(dyn, temperature) - flare_calc = SGP_Calculator(get_empty_sgp()) - ensemble.set_otf(flare_calc) - - # =========== AiiDA INPUTS =============== # - pw_code_label = 'pw@localhost' - aiida_inputs = dict( - pw_code=pw_code_label, - protocol='fast', - overrides={ - 'meta_parameters':{'conv_thr_per_atom': 1e-6}, - 'kpoints_distance': 1000 - }, - options={ - 'resources':{'num_machines': 1, 'num_mpiprocs_per_machine': 2,}, - 'prepend_text':'eval "$(conda shell.bash hook)"\nconda activate aiida-sscha\nexport OMP_NUM_THREADS=1', - }, - electronic_type=ElectronicType.INSULATOR, - batch_number=batch_number, - check_time=check_time, - ) - - # =========== GENERATE & COMPUTE =============== # - ensemble.generate(number_of_configurations) - ensemble.compute_ensemble(**aiida_inputs) # this should include the training too - - print() - print() - print("=============================================") - print("First population has run.") - print("=============================================") - print() - print() - - ensemble.generate(number_of_configurations) # here hopefully the model is called - ensemble.compute_ensemble(**aiida_inputs) - - -if __name__ == '__main__': - main() - diff --git a/Examples/sscha_and_aiida/write_xyz.ipynb b/Examples/sscha_and_aiida/write_xyz.ipynb deleted file mode 100644 index 495bd69e..00000000 --- a/Examples/sscha_and_aiida/write_xyz.ipynb +++ /dev/null @@ -1,377 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Profile" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import numpy as np\n", - "from datetime import datetime\n", - "\n", - "from aiida import load_profile\n", - "from aiida.orm import *\n", - "\n", - "from qe_tools import CONSTANTS as C\n", - "\n", - "from ase.io import write\n", - "from ase import units\n", - "from ase.calculators.singlepoint import SinglePointCalculator\n", - "\n", - "load_profile()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "91" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# group_label = 'CsPbI3/SSCHA/250K'\n", - "\n", - "qb = QueryBuilder()\n", - "# qb.append(Group, filters={'label': group_label}, tag='g')\n", - "# qb.append(WorkChainNode, filters={'attributes.exit_status': 0}, with_group='g', tag='wc')\n", - "qb.append(\n", - " WorkChainNode,\n", - " filters={\n", - " 'attributes.exit_status': 0,\n", - " 'attributes.process_label':'PwBaseWorkChain',\n", - " 'ctime': {'>=': datetime(2024, 4, 4)}, \n", - " },\n", - " tag='wc',\n", - ")\n", - "qb.append(\n", - " TrajectoryData,\n", - " # filters=(Node.fields.attributes.symbols == ['Si']),\n", - " filters={\n", - " 'attributes.symbols': {'contains': ['Si'], 'shorter': 17, 'longer': 15},\n", - " },\n", - " with_incoming='wc',\n", - ")\n", - "\n", - "qb.count()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "results = qb.all(flat=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'symbols': ['Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si',\n", - " 'Si'],\n", - " 'array|cells': [1, 3, 3],\n", - " 'array|steps': [1],\n", - " 'array|energy': [1],\n", - " 'array|forces': [1, 16, 3],\n", - " 'array|stress': [1, 3, 3],\n", - " 'array|energy_xc': [1],\n", - " 'array|positions': [1, 16, 3],\n", - " 'array|total_force': [1],\n", - " 'array|energy_ewald': [1],\n", - " 'array|fermi_energy': [1],\n", - " 'array|scf_accuracy': [9],\n", - " 'array|energy_hartree': [1],\n", - " 'array|scf_iterations': [1],\n", - " 'array|energy_accuracy': [1],\n", - " 'array|energy_smearing': [1],\n", - " 'array|energy_threshold': [1],\n", - " 'array|atomic_species_name': [16],\n", - " 'array|energy_one_electron': [1]}" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results[0].base.attributes.all" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(13.6056917253, 13.605693012183622)" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "C.ry_to_ev, units.Ry" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "stress_units = (-1 * units.Ry / units.Bohr**3)/(C.ry_si / C.bohr_si**3 / 10**9) # convention as in ASE (sign and eV/Ang^3)\n", - "\n", - "filename = './dataset-sscha.xyz'\n", - "\n", - "for res in results:\n", - " index = 0\n", - " atoms = res.get_step_structure(index).get_ase()\n", - " energy = res.get_array('energy')[index]\n", - " s = res.get_array('stress')[index]\n", - "\n", - " calc = SinglePointCalculator(atoms)\n", - "\n", - " calc.results = {\n", - " 'energy': energy,\n", - " 'free_energy': energy,\n", - " 'forces': res.get_array('forces')[index],\n", - " 'stress': stress_units*np.array([s[0,0],s[1,1],s[2,2],s[1,2],s[0,2],s[0,1]]),\n", - " }\n", - "\n", - " atoms.calc = calc\n", - "\n", - " write(filename, atoms, format='extxyz', append=True)\n", - " # break" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 0.03541242, -0.01678025, -0.01865329],\n", - " [-0.01678025, 0.04417991, -0.01289093],\n", - " [-0.01865329, -0.01289093, 0.04192492]])" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "s*stress_units" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25.711031209285363" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from qe_tools import CONSTANTS as C\n", - "\n", - "C.ry_to_ev / C.bohr_to_ang" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "-3.1342698352273604" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "-0.12190370*25.711031209285363" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[ 5.33819603e-01, -3.13426977e+00, 2.21529350e+00],\n", - 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