UniverseMachine: Predicting Galaxy Star Formation over Seven Decades of Halo Mass with Zoom-in Simulations
Yunchong Wang, Ethan O. Nadler, Yao-Yuan Mao, Susmita Adhikari, Risa, H. Wechsler, Peter Behroozi

TL;DR
This paper extends the UniverseMachine model to ultra-faint dwarf galaxies using zoom-in simulations, providing a detailed stellar mass--halo mass relation and insights into galaxy evolution, but highlights the need for improved quenching physics at low masses.
Contribution
It applies UniverseMachine to high-resolution simulations to predict galaxy properties across a vast mass range, especially in the dwarf galaxy regime, revealing current model limitations.
Findings
UniverseMachine predicts a well-resolved stellar mass--halo mass relation.
Most low-mass galaxies are predicted to be actively star-forming at present.
The model overestimates star formation in dwarf galaxies compared to observations.
Abstract
We apply the empirical galaxy--halo connection model UniverseMachine to dark matter-only zoom-in simulations of isolated Milky Way (MW)--mass halos along with their parent cosmological simulations. This application extends \textsc{UniverseMachine} predictions into the ultra-faint dwarf galaxy regime () and yields a well-resolved stellar mass--halo mass (SMHM) relation over the peak halo mass range to . The extensive dynamic range provided by the zoom-in simulations allows us to assess specific aspects of dwarf galaxy evolution predicted by \textsc{UniverseMachine}. In particular, although UniverseMachine is not constrained for dwarf galaxies with , our predicted SMHM relation is consistent with that inferred…
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