PyAutoLens swMATH ID: 38806 Software Authors: Nightingale, J. W.; Hayes, R.; Kelly, A.; Amvrosiadis, A.; Etherington, A.; He, Q.; Li, N.; Cao, X.; Frawley, J.; Cole, S.; Enia, A.; Frenk, C.; Harvey, D.; Li, R.; Massey, R.; Negrello, M.; Robertson, A Description: PyAutoLens: Open-Source Strong Gravitational Lensing. Strong gravitational lensing, which can make a background source galaxy appears multiple times due to its light rays being de ected by the mass of one or more foreground lens galaxies, provides astronomers with a powerful tool to study dark matter, cosmology and the most distant Universe. PyAutoLens is an open-source Python 3.6+ package for strong gravitational lensing, with core features including fully automated strong lens modeling of galaxies and galaxy clusters, support for direct imaging and interferometer datasets and comprehensive tools for simulating samples of strong lenses. The API allows users to perform ray-tracing by using analytic light and mass pro les to build strong lens systems. Accompanying PyAutoLens is the autolens workspace, which includes example scripts, lens datasets and the HowToLens lectures in Jupyter notebook format which introduce non-experts to strong lensing using PyAutoLens. Readers can try PyAutoLens right now by going to the introduction Jupyter notebook on Binder or checkout the readthedocs for a complete overview of PyAutoLens’s features. Homepage: https://www.theoj.org/joss-papers/joss.02825/10.21105.joss.02825.pdf Source Code: https://github.com/Jammy2211/PyAutoLens Dependencies: Python 3 Keywords: Journal of Open Source Software; Python; Open-Source; Strong Gravitational Lensing; PyAutoLens; Python 3 package Related Software: Python; Astropy; gravlens; lenstronomy; visilens; Jupyter; PyMultiNest; PyAutoFit; NumPy; Numba; Matplotlib; emcee; dynesty; corner.py; COLOSSUS; pyquad; PySwarms; scikit-image; Scikit; SciPy Cited in: 0 Documents Standard Articles 1 Publication describing the Software Year PyAutoLens: Open-Source Strong Gravitational Lensing Link Nightingale, J. W., Hayes, R., Kelly, A., Amvrosiadis, A., Etherington, A., He, Q., Li, N., Cao, X., Frawley, J., Cole, S., Enia, A., Frenk, C., Harvey, D., Li, R., Massey, R., Negrello, M., Robertson, A 2021