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[ascl:1807.003] PyAutoLens: Strong lens modeling

PyAutoLens models and analyzes galaxy-scale strong gravitational lenses. This automated module suite simultaneously models the lens galaxy's light and mass while reconstructing the extended source galaxy on an adaptive pixel-grid. Source-plane discretization is amorphous, adapting its clustering and regularization to the intrinsic properties of the lensed source. The lens's light is fitted using a superposition of Sersic functions, allowing PyAutoLens to cleanly deblend its light from the source. Bayesian model comparison is used to automatically chose the complexity of the light and mass models. PyAutoLens provides accurate light, mass, and source profiles inferred for data sets representative of both existing Hubble imaging and future Euclid wide-field observations.

Code site:
https://github.com/Jammy2211/PyAutoLens
Described in:
https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.4738N https://ui.adsabs.harvard.edu/abs/2021JOSS....6.2825N
Bibcode:
2018ascl.soft07003N
Preferred citation method:

Please see citation information here: https://pyautolens.readthedocs.io/en/latest/general/citations.html


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ascl:1807.003
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