UC Santa Cruz

Our Universe is puzzling. According to the canonical cosmological model, the Lambda Cold Dark Matter (LCDM) model, around 95\% of the Universe consists of unknown dark matter and dark energy. Despite the unknown nature of these forms of matter and energy, LCDM provides accurate predictions for a variety of observations. One of the main cosmological pillars is the large-scale distribution of galaxies and the underlying dark matter halos, as probed by surveys like The Dark Energy Spectroscopic Instrument (DESI). This Thesis aims to understand the structure and properties of dark matter halos and apply innovative techniques to test the LCDM cosmological paradigm with state-of-the-art surveys like DESI. First, I will show how various halo properties (e.g., halo mass and mass accretion rate) can be inferred from weak lensing observations of cluster-sized halos. Moreover, I will talk about the splashback feature -- a distinct drop in mass density beyond the virial radius predicted by simulations -- and the accuracy and precision with which we can detect it in real data. Finally, I will demonstrate how the most massive galaxies in the Universe present an excellent avenue for performing precision cosmology with DESI. As we enter the era of DESI, millions of galaxies in the nearby Universe will be complete down to 11.5 solar masses. I will show how this dataset will constrain key cosmological parameters while also minimizing systematics plaguing current studies.