A profile in FIRE: resolving the radial distributions of satellite galaxies in the Local Group with simulations

Abstract

While many tensions between Local Group (LG) satellite galaxies and ΛCDM cosmology have been alleviated through recent cosmological simulations, the spatial distribution of satellites remains an important test of physical models and physical versus numerical disruption in simulations. Using the FIRE-2 cosmological zoom-in baryonic simulations, we examine the radial distributions of satellites with M * > 10 5 M around 8 isolated Milky Way-(MW) mass host galaxies and 4 hosts in LG-like pairs. We demonstrate that these simulations resolve the survival and physical destruction of satellites with M * 10 5 M . The simulations broadly agree with LG observations, spanning the radial profiles around the MW and M31. This agreement does not depend strongly on satellite mass, even at distances 100 kpc. Host-to-host variation dominates the scatter in satellite counts within 300 kpc of the hosts, while time variation dominates scatter within 50 kpc. More massive host galaxies within our sample have fewer satellites at small distances, likely because of enhanced tidal destruction of satellites via the baryonic disks of host galaxies. Furthermore, we quantify and provide fits to the tidal depletion of subhalos in baryonic relative to dark matter-only simulations as a function of distance. Our simulated profiles imply observational incompleteness in the LG even at M * 10 5 M : we predict 2-10 such satellites to be discovered around the MW and possibly 6-9 around M31. To provide cosmological context, we compare our results with the radial profiles of satellites around MW analogs in the SAGA survey, finding that our simulations are broadly consistent with most SAGA systems.

Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1

“…Semi-empirical models that account for these effectsalong with realistic satellite detection criteria-find that the observed satellite population is consistent with cold, collisionless dark matter (e.g., Jethwa et al 2018;Kim et al 2018;Newton et al 2018;Bose et al 2019;Nadler et al 2019aNadler et al , 2019b. Likewise, hydrodynamic simulations that self-consistently model galaxy formation in a cosmological context produce luminosity functions and radial distributions of satellites that are broadly consistent with observations of the Milky Way system (e.g., Wetzel et al 2016;Garrison-Kimmel et al 2019;Samuel et al 2020). In concert, extremely high-resolution simulations of isolated ultra-faint systems suggest that low-mass dwarfs may be abundant (Wheeler et al 2019).…”

“…Such an assumption breaks down if a large population of extremely low-surface-brightness systems exists (e.g., satellites like Crater II and Antlia II). A population of large, luminous, and distant Milky Way satellites has been suggested to resolve the observed radial distribution discrepancy between the satellite populations of the Milky Way and Andromeda (e.g., Yniguez et al 2014;Samuel et al 2020). In addition, we assumed that the intrinsic properties of satellites (e.g., luminosity and half-light radius) are independent of heliocentric distance.…”

Can cosmological simulations capture the diverse satellite populations of observed Milky Way analogues?

“…• Tensions between the observed and predicted radial distributions of satellites. The radial distribution of Milky Way satellites appears to stand in contrast with the predictions of ΛCDM models, in the sense that it appears to be more centrally-concentrated than typical simulated Milky Way-mass systems (Kravtsov et al 2004;Yniguez et al 2014;Samuel et al 2020). Previous studies have shown that the incorporation of important baryonic physics can help to reconcile this tension (e.g., Kravtsov et al 2004;Macciò et al 2010;Font et al 2011;Starkenburg et al 2013).…”

SatGen: a semi-analytical satellite galaxy generator – I. The model and its application to Local-Group satellite statistics

“…This highlights the importance of having a large sample if we hope to distinguish between feedback models. Hydro-simulation suites that consist of on the order of ten MW/M31 analogues would struggle in revealing the aforementioned differences (Samuel et al 2020). Similarly, on the observational side, surveys of more MW/M31 analogues are needed.…”