MAGGPY

Multimessenger Astronomy for GRBs and Gravitational waves in PYthon

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Overview

MAGGPY is a MCMC framework for simulating and fitting short gamma-ray burst (sGRB) populations against Fermi/GBM catalogue data. It forward-models GRB jet emission, both top-hat and structured jet profiles, to infer population-level parameters such as the jet fraction $f_j$, opening-angle distributions, and luminosity functions. It also supports joint GW + EM detection predictions using GWFish.

Key capabilities

• Forward Monte Carlo simulation of sGRB observables (peak flux, T90, fluence, peak energy)
• MCMC inference with emcee using a Cramér–von Mises goodness-of-fit likelihood
• Top-hat and structured jet angular profiles
• Merger rate density models from population synthesis (multiple $\alpha_{\rm CE}$ values, multiple channels)
• GW detection efficiency and sky-localisation forecasts via GWFish (Einstein Telescope, Cosmic Explorer, LIGO)
• Posterior predictive checks with CDF comparisons

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Installation

I really reccomend you create a new environment as the multiple libraries that are being juggled in this code don't play well with too old or too new versions of python

conda create -n acme_env python=3.10 -y
conda activate acme_env

You can then easily install all relevant libraries or by running Tutorials_ACME/setup.ipynb.

git clone https://github.com/LudoDe/MAGGPY.git
cd MAGGPY
pip install -r requirements.txt

Key dependencies

Package	Role
emcee	Affine-invariant MCMC sampler
astropy	Cosmology (Planck18), units
GWFish	GW Fisher-matrix detector simulation
astro-gdt-fermi	Fermi Gamma-ray Data Tools
corner	Posterior corner plots
h5py	HDF5 chain storage
healpy	HEALPix sky maps

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Tutorials (ACME)

#	Notebook	Description
0	tutorial0_data_preparation	Load & filter the Fermi/GBM catalogue; prepare MRD redshift samples
1	tutorial1_tophat	Top-hat jet model: prior setup, short MCMC, CDF visualisation, $f_j$ posterior
2	tutorial2_structured_jet	Structured jet (7 params): MCMC, convergence diagnostics, posterior predictive checks
3	tutorial3_gwfish_joint_detections	GW detection efficiency with GWFish (ET + CE networks)
4	tutorial4_gwfish_skyloc	Sky localisation & Fisher-matrix parameter estimation

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Citation

If you use this code, please cite:

@misc{desantis2026constrainingbinaryneutronstar,
      title={Constraining Binary Neutron Star Populations using Short Gamma-Ray Burst Observations},
      author={Alessio Ludovico De Santis and Samuele Ronchini and Filippo Santoliquido and Marica Branchesi},
      year={2026},
      eprint={2602.13391},
      archivePrefix={arXiv},
      primaryClass={astro-ph.HE},
      url={https://arxiv.org/abs/2602.13391},
}

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License

This work is licensed under a Creative Commons Attribution 4.0 International License.