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Low surface brightness structures from annotated deep CFHT images: effects of the host galaxy’s properties and environment

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Peer-reviewed

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Abstract

ABSTRACT Hierarchical galactic evolution models predict that mergers drive galaxy growth, producing low surface brightness (LSB) tidal features that trace galaxies’ late assembly. These faint structures encode information about past mergers and are sensitive to the properties and environment of the host galaxy. We investigated the relationships between LSB features and their hosts in a sample of 475 nearby massive galaxies spanning diverse environments (field, groups, Virgo cluster) using deep optical imaging from the Canada–France–Hawaii Telescope (MATLAS, UNIONS/CFIS, VESTIGE, NGVS). Using Jafar, an online annotation tool, we manually annotated tidal features, including 199 tidal tails and 100 streams. Geometric and photometric measurements were extracted to analyse their dependence on galaxy mass, environment, and internal kinematics. At our surface brightness limit of 29 mag arcsec$^{-2}$, tidal features contribute 2  per cent of total galaxy luminosity. They are detected in 36  per cent of galaxies, with none fainter than 27.8 mag arcsec$^{-2}$. The most massive galaxies are twice as likely to host tidal debris. Although small-scale interactions increase the frequency of tidal features, the large-scale environment (Virgo cluster versus field/group) does not influence it. An anticorrelation between this frequency and rotational support is found, but may reflect the mass-driven effect. We release our data base of annotated features for deep learning applications. Our findings confirm that galaxy mass is the dominant factor influencing tidal feature prevalence, consistent with hierarchical formation models.

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Journal Title

Monthly Notices of the Royal Astronomical Society

Conference Name

Journal ISSN

0035-8711
1365-2966

Volume Title

541

Publisher

Oxford University Press (OUP)

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Except where otherwised noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/
Sponsorship
Leverhulme Trust (RPG-2021-205)
Academy of Finland (347089)
Swiss National Science Foundation (PZ00P2_202104)
INAF (12–2022)