Poster Abstract

P.6 Richard Hayes (University of Durham)

PyAutoLens: Open-source software for modeling strong gravitational lenses

When two or more galaxies are aligned perfectly down our line-of-sight, the background galaxy is strongly lensed and appears multiple times. Detailed modeling of a strong lens provides an unrivalled view of dark matter, cosmic expansion and the most distant Universe. Unfortunately, the involved and labour intensive nature of this analysis currently limits it to samples of just tens of objects. With Euclid and LSST, the era of 100 000 strong lenses is dawning and a sudden revolution in our analysis of strong lenses is paramount. To this aim, I present PyAutoLens, an open-source framework for performing fully-automated strong lens modeling. I demonstrate the method’s core features using three specific case-studies: (i) reconstructing HST imaging of star-forming and highly-magnified lensed source galaxies on an amorphous pixel-grid; (ii) decomposing each lens galaxy into its luminous and dark matter structures via Bayesian model comparison and; (iii) performing a unified analysis of 100 strong lenses, using just 20 lines of Python code.