Dwarf galaxies provide rich constraints on galaxy formation, reionization, and the nature of dark matter. However, flexible models of their star formation histories in a cosmological context are lacking. We introduce a novel framework for connecting dwarf galaxy dark matter assemblies and star formation histories based on the empirical model UniverseMachine (UM). Our framework is flexible, such that it can be simultaneously constrained by observations over a wide range of galaxy masses, environments, and redshifts. We constrain our model using observations of satellite galaxies around 101 Milky Way analogs, from the Satellite Around Galactic Analogs (SAGA) survey, and field galaxies from SDSS. We find that a strong correlation between halo stripping and satellite quenching is required to reconcile the large difference between satellite and field galaxy quenched fractions at low stellar masses. This framework also enables us to jointly model bright dwarf galaxies with ultra-faint dwarfs in the Local Group (LG), providing a link between the high redshift and very local universe. I will also discuss ongoing work improving subhalo modeling with embedded disk zoom-in simulations and environmental dependence.
BIO
Yunchong Wang obtained his Bachelor of Science degree from Tsinghua University in 2019. He moved on to a PhD program in Physics at Stanford University where he was a Gregory and Mary Chabolla Fellow in the School of Humanities and Sciences. His research interests span a range of topics in galaxy formation and cosmology, including galaxy-halo connection, environmental quenching, dwarf galaxy populations in the Local Group and Local Volume, galaxy clustering and large scale structure.
