April 1
The DREAMS Project: Contextualizing the Milky Way through 1,024 High-Resolution Simulations
Speaker: Dr. Jonah Rose, Princeton
Abstract: In this talk, I will introduce a new suite of 1,024 cosmological hydrodynamical zoom-in simulations of Milky Way-mass halos from the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) Project, designed to systematically disentangle theoretical uncertainties in galaxy formation physics from intrinsic halo-to-halo variance. By varying key astrophysical parameters governing supernova wind energy, wind speed, and AGN feedback efficiency within the IllustrisTNG model, alongside cosmological parameters, we explore a large parameter space of galaxy formation scenarios. To evaluate this high-dimensional space, we introduce a novel observational weighting scheme constrained by the empirical stellar mass-halo mass relation. These constraints reveal broad degeneracies in the fiducial feedback parameters, demonstrating that single-model tuning misses complex parameter interdependencies. Using this weighted dataset, we assess the impact of feedback variations versus accretion history to contextualize the Milky Way. Focusing on the Gaia-Sausage-Enceladus merger, we show that this merger drives lower star formation rates and more compact stellar disks in the central galaxy. However, significant scatter remains in all galactic properties from halo-to-halo variance, suggesting that only modeling major accretion events in the Milky Way's past is insufficient to understand its present-day properties. Extending this methodology beyond the central host, we also examine the surrounding satellite galaxy populations and find that the scatter in their structural and kinematic properties is primarily driven by intrinsic halo-to-halo variance rather than uncertainties in the underlying baryonic physics.
Host: Ankita Bera