Constraining the Inner Dark Matter Profiles of Strong-Lensing Galaxy Clusters

We model the mass distributions of several strong gravitational lensing galaxy cluster systems using imaging data from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey and the Hubble Space Telescope (HST). The modeling is performed using PyAutoLens with custom conjugate-image position constraints to infer lensing properties and mass components. Focusing on clusters with redshifts between 0.38 and 0.56, we model the inner dark matter slope (𝛾) to further our understanding of the dark matter distribution and substructure in comparable systems. We compare our results both against previous studies that utilize alternative modeling techniques and internally across our sample to assess the consistency of our method.