The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Density Profiles

TL;DR

This study uses the DREAMS simulation suite to analyze how baryonic feedback and halo-to-halo variance influence Milky Way dark matter density profiles, highlighting the dominance of intrinsic variance over feedback effects.

Contribution

It provides a comprehensive quantification of the relative impacts of baryonic feedback and halo variance on dark matter profiles using a large suite of simulated halos.

Findings

Dark matter density profiles are largely insensitive to astrophysics and cosmology variations.

Halo-to-halo variance is the main source of scatter in density profiles.

Strong supernova winds can suppress galaxy formation, making halos nearly collisionless.

Abstract

In this work, we utilize a new suite of Milky Way-mass halos from the DREAMS Project, simulated with Cold Dark Matter (CDM), to quantify the influence of baryon feedback and intrinsic halo-to-halo variance on dark matter density profiles. Our suite of 1024 halos varies over supernova and black hole feedback parameters from the IllustrisTNG model, as well as variations in two cosmological parameters. We find that, for the DREAMS parameter variations, Milky Way-mass dark matter density profiles in the IllustrisTNG model are largely insensitive to astrophysics and cosmology variations, with the dominant source of scatter instead arising from halo-to-halo variance. However, most of the (comparatively minor) feedback-driven variations come from the changes to supernova prescriptions. By comparing to dark matter-only simulations, we find that the strongest supernova wind energies are so effective at preventing galaxy formation that the halos are nearly entirely collisionless dark matter. Finally, regardless of physics variation, all the DREAMS halos are roughly consistent with a halo contracting adiabatically from the presence of baryons, unlike models that have bursty stellar feedback. This work represents a step toward assessing the uncertainty in Milky Way dark matter profiles, with direct implications for dark matter searches where systematic uncertainty in the density profile remains a major challenge.