Reliable Tests of Faint-end UV Luminosity Functions in Strong Lensing Fields
Jiashuo Zhang

TL;DR
This paper uses strong lensing in galaxy clusters and advanced data analysis to test dark matter models, finding no evidence for faint-end turnover and setting constraints on ultralight boson mass.
Contribution
It introduces a method combining deep observations and machine learning to improve faint galaxy sample purity for dark matter model testing.
Findings
No evidence for faint-end turnover in UV luminosity functions.
Sets a lower bound on $$DM particle mass at >2.97×10^{-22} eV.
Demonstrates mitigation of low-z interlopers improves test reliability.
Abstract
Dark matter comprises ~85% of the entire mass of the Universe, but the fundamental nature of its constituent particles remains elusive. In this thesis, I test for two competitive dark matter models: the conventional heavy particle paradigm, and dark matter being ultralight bosons of mass eV (DM). More specifically, I test for the faint-end turnover induced by DM models, exploiting the strong lensing power by massive galaxy clusters to probe intrinsically fainter magnitudes. A key challenge for such an analysis would be contamination by low-z galaxies sharing similar observed SEDs as high-z galaxies. As I will demonstrate, such a contamination issue is generally severe and may wash out the faint-end turnover signatures. I also show that of the purported galaxies within existing photometric redshift catalogs constructed for Hubble…
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Taxonomy
TopicsDark Matter and Cosmic Phenomena · Astronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena
