Shear Mapping in Python (SMPy): Modular, Extensible, and Accessible Dark Matter Mapping

Understanding the Universe's large-scale distribution of dark matter is a central objective in the era of precision cosmology.A key technique for the study of dark matter is weak gravitational lensing: a phenomenon where light from distant galaxies is sheared as it passes through the gravitational field of a massive object, like a galaxy cluster.This shear, which manifests as a slight (weak) distortion of shapes over thousands of galaxies, allows astrophysicists to infer the distribution of total matter, including both luminous and dark matter.Obtaining a mass distribution from a catalog of galaxy shears involves reconstructing the convergence (𝜅), which describes how gravitational lensing changes the apparent sizes of background galaxies.Convergence is the projected surface mass density divided by the critical surface density for the lens-source system, allowing it to trace the projected mass distribution.For a comprehensive review of weak gravitational lensing, refer to Umetsu (2020).