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Studying Dark Matter at Sub-Galactic Scales with Strong Gravitational Lensing

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2023-05-16

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Sengul, Atinc Cagan. 2023. Studying Dark Matter at Sub-Galactic Scales with Strong Gravitational Lensing. Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.

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The nature of dark matter, despite the mountains of evidence we have of its existence, remains one of the biggest puzzles in modern physics. The Lambda Cold Dark Matter (LambdaCDM) model, which assumes dark matter to consist of a collisionless non-relativistic particle, has been very successful in explaining the large-scale cosmological observations. If dark matter deviates from the (LambdaCDM) paradigm, we expect the effects of this to manifest at sub-galactic scales. This regime remains largely untested, despite being crucial in determining the physics of dark matter, such as its self-interactions, particle mass, and coupling to the standard model particles. We can probe these small scales using strong gravitational lensing, which involves a foreground mass, typically a galaxy, creating multiple distorted and highly magnified images of a background galaxy by deflecting its light. Smaller perturbers, which can be either subhalos orbiting the foreground galaxy or halos along the line-of-sight, cause slight deviations in these bright arcs. For this reason, strong gravitational lenses have become a popular probe of structures at sub-galactic scales. The goal of this dissertation is to explore ways we can use strong lensing to investigate the properties of dark matter. In this work, we (1) develop statistical tools to extract information about the population of perturbers below galactic masses, (2) present the first detection of a line-of-sight halo using strong lensing data, (3) calculate the sensitivity that strong lensing gives to the density profile of a perturber, and (4) present a novel way of detecting and measuring low-mass perturbers in cluster lenses. We conclude by discussing the opportunities that our work will provide in the near future, when large amounts of gravitational lensing data are expected to be collected.

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cosmology: dark matter, galaxies: clusters, gravitational lensing: strong, software: data analysis, Physics

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