Enhanced pixelated modeling of group and cluster scale lenses: Getting ready for Vera Rubin
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Date
2025
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Abstract
Upcoming wide-field surveys like LSST and Euclid will uncover thousands of strong gravitational lenses, enabling statistical studies of lens properties, tracing mass distributions from galaxies to clusters, and probing cosmology. While automated modeling exists for galaxy-scale lenses, group- and cluster-scale systems remain challenging due to their complexity.We present a fast, automated method for modeling group and cluster strong lenses, optimized for LSST-like data. The approach combines a large-scale halo with subhalos defined by scaling relations and uses a third-order Taylor expansion for subhalo deflections to improve computational efficiency. The method is memory-light and scales independently of cluster richness.We validate the pipeline on 200 LSST-like simulated lenses (100 clusters, 100 groups), recovering unbiased halo parameters and accurate total masses. Performance improves when selecting lenses with bright arcs or radial features. Application to real SGAS systems yields results consistent with previous models.We discuss possible applications of this method, such as constraining the halo mass function, inner slope of clusters, and subhalo properties. We also outline the necessary extensions for modeling Euclid lenses, which require increased source complexity due to the higher resolution.
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Tesis (Master’s degree in Astrophysics)--Pontificia Universidad Católica de Chile, 2025.