BornRaytrace’s Documentation

Simulating weak gravitational lensing effects

https://github.com/NiallJeffrey/BornRaytrace

• Raytrace through overdensity Healpix maps to return convergence maps

• Include shear-kappa transformation on the full sphere

• Include intrinsic alignments (NLA model)

Requirements (python3): numpy, scipy, astropy, healpy

• Simple example notebook

• Full example notebook

Contents:

• bornraytrace

• Index

• Search Page

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Citation:

If you find this code useful, please cite: “Likelihood-free inference with neural compression of DES SV weak lensing map statistics”, Jeffrey, Alsing, Lanusse 2020

article{2020, title={Likelihood-free inference with neural compression of DES SV weak lensing map statistics}, volume={501}, ISSN={1365-2966}, url={http://dx.doi.org/10.1093/mnras/staa3594}, DOI={10.1093/mnras/staa3594}, number={1}, journal={Monthly Notices of the Royal Astronomical Society}, publisher={Oxford University Press (OUP)}, author={Jeffrey, Niall and Alsing, Justin and Lanusse, François}, year={2020}, month={Nov}, pages={954–969}}