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Unveiling the (in)consistencies among the galaxy stellar mass function, star formation histories, satellite abundances and intracluster light from a semi-empirical perspective

Unveiling the (in)consistencies among the galaxy stellar mass function, star formation histories, satellite abundances and intracluster light from a semi-empirical perspective
Unveiling the (in)consistencies among the galaxy stellar mass function, star formation histories, satellite abundances and intracluster light from a semi-empirical perspective
In a hierarchical, dark matter-dominated Universe, stellar mass functions (SMFs), galaxy merger rates, star formation histories (SFHs), satellite abundances, and intracluster light, should all be intimately connected observables. However, the systematics affecting observations still prevent universal and uniform measurements of, for example, the SMF and the SFHs, inevitably preventing theoretical models to compare with multiple data sets robustly and simultaneously. We here present our holistic semi-empirical model DECODE (Discrete statistical sEmi-empiriCal mODEl) that converts via abundance matching dark matter merger trees into galaxy assembly histories, using different SMFs in input and predicting all other observables in output in a fully data-driven and self-consistent fashion with minimal assumptions. We find that: 1) weakly evolving or nearly constant SMFs below the knee (M⋆≲1011M⊙) are the best suited to generate star formation histories aligned with those inferred from MaNGA, SDSS, GAMA, and, more recently, JWST; 2) the evolution of satellites after infall only affects the satellite abundances and star formation histories of massive central galaxies but not their merger histories; 3) the resulting SFR-M⋆ relation is lower in normalization by a factor of ∼2 with respect to observations, with a flattening at high masses more pronounced in the presence of mergers; 4) the latest data on intracluster light can be reproduced if mass loss from mergers is included in the models. Our findings are pivotal in acting as pathfinder to test the self-consistency of the high-quality data from, e.g., JWST and Euclid.
astro-ph.GA, astro-ph.CO
1365-2966
Fu, Hao
09d6267e-c26d-4ac1-a653-2c5886c12b1e
Shankar, Francesco
b10c91e4-85cd-4394-a18a-d4f049fd9cdb
Ayromlou, Mohammadreza
600bc3a0-020c-4a7d-911d-90ff21cdc5f7
Koutsouridou, Ioanna
d6e7c6b2-964b-4a98-8349-49e4ce972bb5
Cattaneo, Andrea
57281cb2-9f71-41c5-8a3a-b238b9a11211
Bertemes, Caroline
d539f613-ab71-4dc7-b88f-d855ce5531dd
Bellstedt, Sabine
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Martín-Navarro, Ignacio
39dd8f48-4a9e-400c-b37d-2d26d106e810
Leja, Joel
dfd95c8e-3577-435b-aec3-c6a106a6cc2e
Allevato, Viola
e74ca535-ee08-485b-a961-09c8376668c2
Bernardi, Mariangela
b142f5a1-727d-42db-842c-df77a93af98b
Boco, Lumen
93c3f9ff-ba52-468f-b627-bc6cdae83e8f
Dimauro, Paola
a2d13aec-153e-4dcd-a439-54e8c7d2c50b
Gruppioni, Carlotta
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Lapi, Andrea
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Menci, Nicola
e68473f0-6f7f-48b8-8b76-088d8752df6a
Rodríguez, Iván Muñoz
5a040d06-81ed-4dc8-b017-b26e93aba47b
Puglisi, Annagrazia
97237841-1e6d-48fb-9133-671b6f3af18b
Alonso-Tetilla, Alba V.
672c0f44-412a-4f1e-a98f-22463585e6ad
Fu, Hao
09d6267e-c26d-4ac1-a653-2c5886c12b1e
Shankar, Francesco
b10c91e4-85cd-4394-a18a-d4f049fd9cdb
Ayromlou, Mohammadreza
600bc3a0-020c-4a7d-911d-90ff21cdc5f7
Koutsouridou, Ioanna
d6e7c6b2-964b-4a98-8349-49e4ce972bb5
Cattaneo, Andrea
57281cb2-9f71-41c5-8a3a-b238b9a11211
Bertemes, Caroline
d539f613-ab71-4dc7-b88f-d855ce5531dd
Bellstedt, Sabine
7dc060b6-cce6-447b-8c45-1b25be16001f
Martín-Navarro, Ignacio
39dd8f48-4a9e-400c-b37d-2d26d106e810
Leja, Joel
dfd95c8e-3577-435b-aec3-c6a106a6cc2e
Allevato, Viola
e74ca535-ee08-485b-a961-09c8376668c2
Bernardi, Mariangela
b142f5a1-727d-42db-842c-df77a93af98b
Boco, Lumen
93c3f9ff-ba52-468f-b627-bc6cdae83e8f
Dimauro, Paola
a2d13aec-153e-4dcd-a439-54e8c7d2c50b
Gruppioni, Carlotta
0fb7cd93-cdd9-48c2-8d4b-465606f80e51
Lapi, Andrea
f696d82a-d82b-451d-9285-e51df4a1b4db
Menci, Nicola
e68473f0-6f7f-48b8-8b76-088d8752df6a
Rodríguez, Iván Muñoz
5a040d06-81ed-4dc8-b017-b26e93aba47b
Puglisi, Annagrazia
97237841-1e6d-48fb-9133-671b6f3af18b
Alonso-Tetilla, Alba V.
672c0f44-412a-4f1e-a98f-22463585e6ad

Fu, Hao, Shankar, Francesco, Ayromlou, Mohammadreza, Koutsouridou, Ioanna, Cattaneo, Andrea, Bertemes, Caroline, Bellstedt, Sabine, Martín-Navarro, Ignacio, Leja, Joel, Allevato, Viola, Bernardi, Mariangela, Boco, Lumen, Dimauro, Paola, Gruppioni, Carlotta, Lapi, Andrea, Menci, Nicola, Rodríguez, Iván Muñoz, Puglisi, Annagrazia and Alonso-Tetilla, Alba V. (2024) Unveiling the (in)consistencies among the galaxy stellar mass function, star formation histories, satellite abundances and intracluster light from a semi-empirical perspective. Monthly Notices of the Royal Astronomical Society. (In Press)

Record type: Article

Abstract

In a hierarchical, dark matter-dominated Universe, stellar mass functions (SMFs), galaxy merger rates, star formation histories (SFHs), satellite abundances, and intracluster light, should all be intimately connected observables. However, the systematics affecting observations still prevent universal and uniform measurements of, for example, the SMF and the SFHs, inevitably preventing theoretical models to compare with multiple data sets robustly and simultaneously. We here present our holistic semi-empirical model DECODE (Discrete statistical sEmi-empiriCal mODEl) that converts via abundance matching dark matter merger trees into galaxy assembly histories, using different SMFs in input and predicting all other observables in output in a fully data-driven and self-consistent fashion with minimal assumptions. We find that: 1) weakly evolving or nearly constant SMFs below the knee (M⋆≲1011M⊙) are the best suited to generate star formation histories aligned with those inferred from MaNGA, SDSS, GAMA, and, more recently, JWST; 2) the evolution of satellites after infall only affects the satellite abundances and star formation histories of massive central galaxies but not their merger histories; 3) the resulting SFR-M⋆ relation is lower in normalization by a factor of ∼2 with respect to observations, with a flattening at high masses more pronounced in the presence of mergers; 4) the latest data on intracluster light can be reproduced if mass loss from mergers is included in the models. Our findings are pivotal in acting as pathfinder to test the self-consistency of the high-quality data from, e.g., JWST and Euclid.

Text
2406.07605v1 - Accepted Manuscript
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More information

Accepted/In Press date: 11 June 2024
Additional Information: 12 figures
Keywords: astro-ph.GA, astro-ph.CO

Identifiers

Local EPrints ID: 492091
URI: http://eprints.soton.ac.uk/id/eprint/492091
ISSN: 1365-2966
PURE UUID: 85ffecad-60ed-40b1-b671-06a19d3539f4

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Date deposited: 16 Jul 2024 16:52
Last modified: 16 Aug 2024 04:01

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Contributors

Author: Hao Fu
Author: Mohammadreza Ayromlou
Author: Ioanna Koutsouridou
Author: Andrea Cattaneo
Author: Caroline Bertemes
Author: Sabine Bellstedt
Author: Ignacio Martín-Navarro
Author: Joel Leja
Author: Viola Allevato
Author: Mariangela Bernardi
Author: Lumen Boco
Author: Paola Dimauro
Author: Carlotta Gruppioni
Author: Andrea Lapi
Author: Nicola Menci
Author: Annagrazia Puglisi
Author: Alba V. Alonso-Tetilla

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