Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification

Fuente: arXiv
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Autori principali: Bowden, Haley, Behroozi, Peter
Natura: Preprint
Pubblicazione: 2025
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author Bowden, Haley
Behroozi, Peter
author_facet Bowden, Haley
Behroozi, Peter
contents A physical understanding of galaxy formation and evolution benefits from an understanding of the connections between galaxies, their host dark matter halos, and their environments. In particular, interactions with more-massive neighbors can leave lasting imprints on both galaxies and their hosts. Distinguishing between populations of galaxies with differing environments and interaction histories is therefore essential for isolating the role of environment in shaping galaxy properties. We present a novel neural-network based method, which takes advantage of observable measures of a galaxy and its environment to recover whether it (1) is a central or a satellite, (2) has experienced an interaction with a more massive neighbor, and (3) is currently orbiting or infalling onto such a neighbor. We find that projected distances to, redshift separations of, and relative stellar masses with respect to a galaxy's 25 nearest neighbors are sufficient to distinguish central from satellite halos in $> 90\%$ of cases, with projection effects accounting for most classification errors. Our method also achieves high accuracy in recovering interaction history and orbital status, though the network struggles to distinguish between splashback and infalling systems in some cases due to the lack of velocity information. With careful treatment of the uncertainties introduced by projection and other observational limitations, this method offers a new avenue for studying the role of environment in galaxy formation and evolution.
format Preprint
id arxiv_https___arxiv_org_abs_2509_25312
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification
Bowden, Haley
Behroozi, Peter
Astrophysics of Galaxies
Cosmology and Nongalactic Astrophysics
A physical understanding of galaxy formation and evolution benefits from an understanding of the connections between galaxies, their host dark matter halos, and their environments. In particular, interactions with more-massive neighbors can leave lasting imprints on both galaxies and their hosts. Distinguishing between populations of galaxies with differing environments and interaction histories is therefore essential for isolating the role of environment in shaping galaxy properties. We present a novel neural-network based method, which takes advantage of observable measures of a galaxy and its environment to recover whether it (1) is a central or a satellite, (2) has experienced an interaction with a more massive neighbor, and (3) is currently orbiting or infalling onto such a neighbor. We find that projected distances to, redshift separations of, and relative stellar masses with respect to a galaxy's 25 nearest neighbors are sufficient to distinguish central from satellite halos in $> 90\%$ of cases, with projection effects accounting for most classification errors. Our method also achieves high accuracy in recovering interaction history and orbital status, though the network struggles to distinguish between splashback and infalling systems in some cases due to the lack of velocity information. With careful treatment of the uncertainties introduced by projection and other observational limitations, this method offers a new avenue for studying the role of environment in galaxy formation and evolution.
title Halo Properties from Observable Measures of Environment: II. Central versus Satellite Classification
topic Astrophysics of Galaxies
Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2509.25312