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Galaxy and mass assembly (GAMA): Self-Organizing Map application on nearby galaxies

Holwerda, Benne W.; Smith, Dominic; Porter, Lori; Henry, Chris; Porter-Temple, Ren; Cook, Kyle; Pimbblet, Kevin A.; Hopkins, Andrew M; Bilicki, Maciej; Turner, Sebastian; Acquaviva, Viviana; Wang, Lingyu; Wright, Angus H.; Kelvin, Lee S.; Grootes, Meiert W

Authors

Benne W. Holwerda

Dominic Smith

Lori Porter

Chris Henry

Ren Porter-Temple

Kyle Cook

Andrew M Hopkins

Maciej Bilicki

Sebastian Turner

Viviana Acquaviva

Lingyu Wang

Angus H. Wright

Lee S. Kelvin

Meiert W Grootes



Abstract

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and Sérsic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between two and six clusters. Here we use Self-Organizing Maps (SOM), an unsupervised learning technique that can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these 5D clusters in the feature space on to 2D projections. To further analyse these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped on to three or five clusters. We explore where the 'green valley' galaxies are mapped on to the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped on to the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or 'featured' can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough.

Citation

Holwerda, B. W., Smith, D., Porter, L., Henry, C., Porter-Temple, R., Cook, K., …Grootes, M. W. (2022). Galaxy and mass assembly (GAMA): Self-Organizing Map application on nearby galaxies. Monthly notices of the Royal Astronomical Society, 513(2), 1972-1984. https://doi.org/10.1093/mnras/stac889

Journal Article Type Article
Acceptance Date Mar 29, 2022
Online Publication Date Apr 14, 2022
Publication Date Jun 1, 2022
Deposit Date Jun 16, 2022
Publicly Available Date Oct 27, 2022
Journal Monthly Notices of the Royal Astronomical Society
Print ISSN 0035-8711
Electronic ISSN 1365-2966
Publisher Oxford University Press
Peer Reviewed Peer Reviewed
Volume 513
Issue 2
Pages 1972-1984
DOI https://doi.org/10.1093/mnras/stac889
Keywords Catalogues; Surveys; Galaxies: evolution; Galaxies: fundamental parameters; Galaxies: star formation; Galaxies: statistics
Public URL https://hull-repository.worktribe.com/output/3970443

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Copyright Statement
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2022 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.





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