Princeton University Dark Cosmos Seminar

Abstract: The Lambda-CDM cosmological model predicts a wealth of small-scale structures, including dark matter subhalos residing within more massive halos such as that of our own Milky Way Galaxy. Some of these subhalos may be massive enough to host faint galaxies, while smaller ones fall below the threshold for galaxy formation and remain dark. The abundance and survivability of both luminous and dark subhalos offer powerful tests of the Lambda-CDM paradigm and models of galaxy formation at the smallest scales. While numerical simulations are essential for quantifying these substructures, the suitability of standard tools, such as halo finders and merger trees, for identifying and tracking subhalos in simulations is increasingly questioned, especially for low-mass subhalos orbiting deep within a host halo’s potential. I present Bloodhound, a next-generation subhalo tracking algorithm designed to improve the accuracy and consistency of subhalo tracking, even in the densest regions of host halos. I will discuss the current status of key small-scale challenges to Lambda-CDM and highlight Bloodhound’s contributions to refining the statistical predictions of subhalo populations in cosmological simulations. Finally, I will explore the scientific implications of these improvements for constraining alternative dark matter models and the low-mass threshold for galaxy formation. These results are especially timely in light of upcoming observational breakthroughs from surveys including Euclid, JWST, SDSS, and Rubin, which promise to probe the structure of the nearby universe at the smallest galactic scales.