Modeling Strong-Lensing Galaxy Clusters Using DES and HST with Nested Sampling

We utilize a combination of Dark Energy Survey (DES) data and Hubble Space Telescope (HST) imaging to model strong-lensing galaxy cluster systems with a dynamic nested sampling approach implemented via dynesty. We evaluate the consistency of lensing properties and mass distributions of clusters with similar redshifts and physical scales, and we assess the performance of our nested sampler. We compare our results with related works, which have modeled similar clusters using alternative methods, and we present an analysis of the optimization of our sampler as our results approached a stable convergence.