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Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning

Turner, S, Siudek, M, Salim, S, Baldry, IK, Pollo, A, Longmore, SN, Małek, K, Collins, CA, Lisboa, PJ, Krywult, J, Moutard, T, Vergani, D and Fritz, A Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning. Monthly Notices of the Royal Astronomical Society. ISSN 0035-8711 (Accepted)

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Abstract

The colour bimodality of galaxies provides an empirical basis for theories of galaxy evolution. However, the balance of processes that begets this bimodality has not yet been constrained. A more detailed view of the galaxy population is needed, which we achieve in this paper by using unsupervised machine learning to combine multi-dimensional data at two different epochs. We aim to understand the cosmic evolution of galaxy subpopulations by uncovering substructures within the colour bimodality. We choose a clustering algorithm that models clusters using only the most discriminative data available, and apply it to two galaxy samples: one from the second edition of the GALEX-SDSS-WISE Legacy Catalogue (GSWLC-2; $z \sim 0.06$), and the other from the VIMOS Public Extragalactic Redshift Survey (VIPERS; $z \sim 0.65$). We cluster within a nine-dimensional feature space defined purely by rest-frame ultraviolet-through-near-infrared colours. Both samples are similarly partitioned into seven clusters, breaking down into four of mostly star-forming galaxies (including the vast majority of green valley galaxies) and three of mostly passive galaxies. The separation between these two families of clusters suggests differences in the evolution of their galaxies, and that these differences are strongly expressed in their colours alone. The samples are closely related, with star-forming/green-valley clusters at both epochs forming morphological sequences, capturing the gradual internally-driven growth of galaxy bulges. At high stellar masses, this growth is linked with quenching. However, it is only in our low-redshift sample that additional, environmental processes appear to be involved in the evolution of low-mass passive galaxies.

Item Type: Article
Additional Information: This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Sebastian Turner, Malgorzata Siudek, Samir Salim, Ivan K Baldry, Agnieszka Pollo, Steven N Longmore, Katarzyna Malek, Chris A Collins, Paulo J Lisboa, Janusz Krywult, Thibaud Moutard, Daniela Vergani, Alexander Fritz, Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning, Monthly Notices of the Royal Astronomical Society, 2021;, stab653, is available online at: https://doi.org/10.1093/mnras/stab653
Uncontrolled Keywords: astro-ph.GA; astro-ph.GA
Subjects: Q Science > QB Astronomy
Q Science > QC Physics
Divisions: Astrophysics Research Institute
Publisher: Oxford University Press
Related URLs:
Date Deposited: 16 Mar 2021 12:05
Last Modified: 16 Mar 2021 12:15
URI: https://researchonline.ljmu.ac.uk/id/eprint/14459

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