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From Pixels to Cosmology: An End-to-End Analysis of Galaxy Clusters and Their Properties

Creative Commons 'BY-NC-ND' version 4.0 license

This work is centered around two themes: (1) a focus on establishing a robust pipeline for deep HST image-to-catalog data reduction; and (2) using the generated catalog data to bridge themes in cosmology and astrophysics to understand and connect these two scales. I have developed a pipeline to efficiently create catalogs of deep and crowded, space-based data for the Hubble Frontier Fields and BUFFALO. These catalogs included source detection and extraction, intracluster light+bright cluster galaxy modeling, and multi-waveband homogenization.

Using these datasets, I have worked on two projects which aim to answer questions about large scale structure and galaxy formation and evolution. Within the BUFFALO collaboration, I am working on using the catalogs and our data products to understand how galaxies cluster in the very early universe (redshift > 5). Furthermore, my data products include models of the intracluster light (ICL) and I am using these to probe the underlying dark matter distribution in clusters and examine if we can use these observables to constrain dark matter modeling at these scales. By studying the correlations between ICL maps and the best self-reported lens maps, we may be able to use the ICL maps as a prior to inform the construction of new, more reliable, lens maps.

Finally, I am also particularly interested in combining different data in interesting ways to understand the connection between properties at large and small scales, specifically as it relates to the relationship between light and dark matter. Combining multi-resolution ground- and space-based data with various techniques will become key to maximize the performance and synergies between current and upcoming surveys from JWST, Roman, Rubin, and Euclid.

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