
arXiv: 2210.14233
Abstract Quantifying the connection between galaxies and their host dark matter halos has been key for testing cosmological models on various scales. Below M ⋆ ∼ 109 M ⊙, such studies have primarily relied on the satellite galaxy population orbiting the Milky Way (MW). Here we present new constraints on the connection between satellite galaxies and their host dark matter subhalos using the largest sample of satellite galaxies in the Local Volume (D ≲ 12 Mpc) to date. We use 250 confirmed and 71 candidate dwarf satellites around 27 MW-like hosts from the Exploration of Local VolumE Satellites (ELVES) Survey and use the semianalytical SatGen model for predicting the population of dark matter subhalos expected in the same volume. Through a Bayesian model comparison of the observed and the forward-modeled satellite stellar mass functions (SSMFs), we infer the satellite stellar-to-halo mass relation. We find that the observed SSMF is best reproduced when subhalos at the low-mass end are populated by a relation of the form M ⋆ ∝ M peak α , with a moderate slope of α const = 2.10 ± 0.01 and a low scatter, constant as a function of the peak halo mass, of σ const = 0.06 − 0.05 + 0.07 . A model with a steeper slope (α grow = 2.39 ± 0.06) and a scatter that grows with decreasing M peak is also consistent with the observed SSMF but is not required. Our new model for the satellite–subhalo connection, based on hundreds of Local Volume satellite galaxies, is in line with what was previously derived using only MW satellites.
Observational cosmology, QB460-466, Astrophysics of Galaxies (astro-ph.GA), Dark matter, FOS: Physical sciences, Scaling relations, Bayesian statistics, Astrophysics, Observational astronomy, Astrophysics - Astrophysics of Galaxies, Dwarf galaxies
Observational cosmology, QB460-466, Astrophysics of Galaxies (astro-ph.GA), Dark matter, FOS: Physical sciences, Scaling relations, Bayesian statistics, Astrophysics, Observational astronomy, Astrophysics - Astrophysics of Galaxies, Dwarf galaxies
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