Repo to store code and documentation for the IA infusion method
This repo contains a number of jupyter notebooks meant to validate the various mock data and the predictions. Here is the overall production & validation pipeline, starting with a series of mass sheets from the OuterRim simulation, filling the light-cone up to z = 3.
1-The notebook MiraTitanBorn.ipynb ray-traces the SkySim5000 mass sheets and produces shear and kappa maps.
2-The notebook SkySim5000_IA.ipynb computes projected tidal field maps s11, s22 and s12 from the mass sheets.
3-The notebook PopulateGal.ipynb generates galaxy lensing catalogues given an n(z), n_gal, and an tracer model (random position or linearly tracing the projected matter distribution)
4a-The notebook AddDeltaSij.ipynb adds the delta, s11, s22 and s12 values to the lensing catalogue. 4b-Catalogues are concatenated from indivual mass planes to full tomographic samples.
5-The Infusion_IA.ipynb notebook converts the tidal field quantities s11, s22 and s12 into intrinsic ellipticities, following the NLA, delta-NLA, TT, delta_TT model or any combination of these.
6-The notebook Infusion_postprocessing.ipynb then reads these, reweiths the relative ellipticities with three IA parameters (A_IA, b_TA and C2) and constructs IA-infused mocks.
7-The Treecorr.ipynb notebook computes 2PCFs from these mocks (the GG-noIA, GG, GI and II terms).
8-Predictions are computed with CCL in theo_predictions.ipynb
9-Results are compared in Compare_Mocks_Theory.ipynb
The IA-free data has also been validated with Namaster (see the Namaster notebook). All other notebooks in this repo are unpolished, unfinished work so should not be used for science without thorough validation.