Caustics: A Python Package for Accelerated StrongGravitational Lensing Simulations

Gravitational lensing is the deflection of light rays due to the gravity of intervening masses.This phenomenon is observed at a variety of configurations, involving any non-uniform mass such as planets, stars, galaxies, clusters of galaxies, and even the large-scale structure of the Universe.Strong lensing occurs when the distortions are significant and multiple images of the background source are observed.The lens and lensed object(s) must be aligned closely on the sky.As the discovery of lens systems has grown to the low thousands, these systems have become pivotal for precision measurements in astrophysics, notably for phenomena including dark matter (e.g.Hezaveh et al., 2016;Vegetti & Vogelsberger, 2014), supernovae (e.g.Rodney et al., 2021), quasars (e.g.Peng et al., 2006), the first stars (e.g.Welch et al., 2022), and the Universe's expansion rate (e.g.K. C. Wong et al., 2020).With future surveys expected to discover hundreds of thousands of lensing systems, the modelling and simulation of such systems must be done at orders of magnitude larger scale than ever before.Here we present caustics, a Python package designed to facilitate machine learning and Bayesian methods to handle the extensive computational demands of modelling such a vast number of lensing systems.