Modeling the Connection Between Subhalos and Satellites in Milky Way-like Systems

TL;DR

This paper presents a detailed model linking satellite galaxies to dark matter subhalos in Milky Way-like systems, accounting for various uncertainties and observational effects to better understand satellite populations.

Contribution

It introduces a comprehensive, flexible framework for connecting satellite galaxies with subhalos, incorporating physical and numerical uncertainties, and fits the model to observed satellite data.

Findings

The model successfully reproduces the luminosity distribution of known satellites.

Surface brightness modeling is crucial for interpreting satellite observations.

Predicted satellite populations inform future survey expectations.

Abstract

We develop a comprehensive and flexible model for the connection between satellite galaxies and dark matter subhalos in dark matter-only zoom-in simulations of Milky Way (MW)--mass host halos. We systematically identify the physical and numerical uncertainties in the galaxy--halo connection and simulations underlying our method, including (i) the influence of host halo properties; (ii) the relationship between satellite luminosities and subhalo properties, including the effects of reionization; (iii) the relationship between satellite and subhalo locations; (iv) the relationship between satellite sizes and subhalo properties, including the effects of tidal stripping; (v) satellite and subhalo disruption due to baryonic effects; and (vi) artificial subhalo disruption and orphan satellites. To illustrate our approach, we fit this model to the luminosity distribution of both classical MW satellites and those discovered in the Sloan Digital Sky Survey by performing realistic mock observations that depend on the luminosity, size, and distance of our predicted satellites, and we infer the total satellite population that will be probed by upcoming surveys. We argue that galaxy size and surface brightness modeling will play a key role in interpreting current and future observations, as the expected number of observable satellites depends sensitively on their surface brightness distribution.