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A statistical semi-empirical model: satellite galaxies in groups and clusters

A statistical semi-empirical model: satellite galaxies in groups and clusters
A statistical semi-empirical model: satellite galaxies in groups and clusters
We present STEEL, a STatistical sEmi-Empirical modeL, designed to probe the distribution of satellite galaxies in groups and clusters. Our fast statistical methodology relies on tracing the abundances of central and satellite haloes via their mass functions at all cosmic epochs with virtually no limitation on cosmic volume and mass resolution. From mean halo accretion histories and subhalo mass functions, the satellite mass function is progressively built in time via abundance matching techniques constrained by number densities of centrals in the local Universe. By enforcing dynamical merging time-scales as predicted by high-resolution N-body simulations, we obtain satellite distributions as a function of stellar mass and halo mass consistent with current data. We show that stellar stripping, star formation, and quenching play all a secondary role in setting the number densities of massive satellites above M∗≳3×1010M⊙⁠. We further show that observed star formation rates used in our empirical model over predict low-mass satellites below M∗≲3×1010M⊙⁠, whereas star formation rates derived from a continuity equation approach yield the correct abundances similar to previous results for centrals.
1365-2966
2506-2523
Grylls, Philip J
dff3e462-df6d-46cd-8366-91a75abc9a9e
Shankar, F
b10c91e4-85cd-4394-a18a-d4f049fd9cdb
Zanisi, L
87405729-1792-4919-a0de-fc92ea450edb
Bernardi, M
54b8a017-8b86-4c7d-87b3-a2ebda0b4e56
Grylls, Philip J
dff3e462-df6d-46cd-8366-91a75abc9a9e
Shankar, F
b10c91e4-85cd-4394-a18a-d4f049fd9cdb
Zanisi, L
87405729-1792-4919-a0de-fc92ea450edb
Bernardi, M
54b8a017-8b86-4c7d-87b3-a2ebda0b4e56

Grylls, Philip J, Shankar, F, Zanisi, L and Bernardi, M (2019) A statistical semi-empirical model: satellite galaxies in groups and clusters. Monthly Notices of the Royal Astronomical Society, 483 (2), 2506-2523. (doi:10.1093/mnras/sty3281).

Record type: Article

Abstract

We present STEEL, a STatistical sEmi-Empirical modeL, designed to probe the distribution of satellite galaxies in groups and clusters. Our fast statistical methodology relies on tracing the abundances of central and satellite haloes via their mass functions at all cosmic epochs with virtually no limitation on cosmic volume and mass resolution. From mean halo accretion histories and subhalo mass functions, the satellite mass function is progressively built in time via abundance matching techniques constrained by number densities of centrals in the local Universe. By enforcing dynamical merging time-scales as predicted by high-resolution N-body simulations, we obtain satellite distributions as a function of stellar mass and halo mass consistent with current data. We show that stellar stripping, star formation, and quenching play all a secondary role in setting the number densities of massive satellites above M∗≳3×1010M⊙⁠. We further show that observed star formation rates used in our empirical model over predict low-mass satellites below M∗≲3×1010M⊙⁠, whereas star formation rates derived from a continuity equation approach yield the correct abundances similar to previous results for centrals.

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A Statistical Semi-Empirical Model Satellite galaxies in Groups and Clusters - Accepted Manuscript
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Accepted/In Press date: 28 November 2018
e-pub ahead of print date: 3 December 2018
Published date: 21 February 2019

Identifiers

Local EPrints ID: 430276
URI: http://eprints.soton.ac.uk/id/eprint/430276
ISSN: 1365-2966
PURE UUID: 66aa10de-40d3-4f3b-bfac-3eacd591ac15
ORCID for Philip J Grylls: ORCID iD orcid.org/0000-0001-9677-5852

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Date deposited: 24 Apr 2019 16:30
Last modified: 16 Mar 2024 01:27

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Contributors

Author: Philip J Grylls ORCID iD
Author: F Shankar
Author: L Zanisi
Author: M Bernardi

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