A Survey of Galaxy Pairs in the SDSS Photometric Images based on Faster-RCNN

Galaxy pairs hold significant importance in understanding the evolution of galaxies, and the extensive search for a large sample of galaxy pairs is meaningful. In this article, we develop a deep learning-based approach for the search of galaxy pairs and conduct a comprehensive search on Sloan Digita...

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Published inThe Astronomical journal Vol. 168; no. 2; pp. 90 - 104
Main Authors Shi, Chen-hui, Yang, Hai-feng, Cai, Jiang-hui, Zhou, Li-chan, He, Yan-ting, Su, Mei-hong, Zhao, Xu-jun, Xun, Ya-ling
Format Journal Article
LanguageEnglish
Published Madison The American Astronomical Society 01.08.2024
IOP Publishing
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Online AccessGet full text
ISSN0004-6256
1538-3881
DOI10.3847/1538-3881/ad5968

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Abstract Galaxy pairs hold significant importance in understanding the evolution of galaxies, and the extensive search for a large sample of galaxy pairs is meaningful. In this article, we develop a deep learning-based approach for the search of galaxy pairs and conduct a comprehensive search on Sloan Digital Sky Survey (SDSS) images. In nine million photometric images, 17,965 physical galaxy pairs with spectral or photometric redshifts are detected. Four sets of results are provided, including physical pairs determined by two spectral redshifts, two photometric redshifts, one spectral redshift, and one photometric redshift, and visual irregular pairs that have no precise redshift information but can be inferred as physical galaxy pairs based on the morphological changes. Then their morphological and physical characteristics are explored, the redshifts of most targets are around 0.1, and as the redshift difference between two galaxies increases, the number of galaxy pairs gradually reduces. The distributions of star formation rate (SFR) are not the same for different morphologies of galaxy pairs, irregular pairs have higher SFR than the other three types, and statistics indicate that the SFR of galaxies depends on both nearby galaxies and internal properties. Color and stellar mass are also key properties of galaxies which can reflect the status of galaxy pairs. Compared to other surveys, a greater number of galaxy pair targets are detected, and this is also the first extensive detection of galaxy pairs in SDSS images using photometric redshifts. These galaxy pair samples can greatly aid in the study of galaxy evolution.
AbstractList Galaxy pairs hold significant importance in understanding the evolution of galaxies, and the extensive search for a large sample of galaxy pairs is meaningful. In this article, we develop a deep learning-based approach for the search of galaxy pairs and conduct a comprehensive search on Sloan Digital Sky Survey (SDSS) images. In nine million photometric images, 17,965 physical galaxy pairs with spectral or photometric redshifts are detected. Four sets of results are provided, including physical pairs determined by two spectral redshifts, two photometric redshifts, one spectral redshift, and one photometric redshift, and visual irregular pairs that have no precise redshift information but can be inferred as physical galaxy pairs based on the morphological changes. Then their morphological and physical characteristics are explored, the redshifts of most targets are around 0.1, and as the redshift difference between two galaxies increases, the number of galaxy pairs gradually reduces. The distributions of star formation rate (SFR) are not the same for different morphologies of galaxy pairs, irregular pairs have higher SFR than the other three types, and statistics indicate that the SFR of galaxies depends on both nearby galaxies and internal properties. Color and stellar mass are also key properties of galaxies which can reflect the status of galaxy pairs. Compared to other surveys, a greater number of galaxy pair targets are detected, and this is also the first extensive detection of galaxy pairs in SDSS images using photometric redshifts. These galaxy pair samples can greatly aid in the study of galaxy evolution.
Author Shi, Chen-hui
Su, Mei-hong
Yang, Hai-feng
Zhou, Li-chan
Cai, Jiang-hui
Zhao, Xu-jun
Xun, Ya-ling
He, Yan-ting
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SubjectTerms Algorithms
Astronomy data reduction
Detection
Digital imaging
Galactic evolution
Galaxies
Galaxy pairs
Morphology
Photometry
Physical properties
Red shift
Searching
Sky surveys (astronomy)
Star & galaxy formation
Star formation
Star formation rate
Stars & galaxies
Stellar evolution
Stellar mass
Target detection
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Title A Survey of Galaxy Pairs in the SDSS Photometric Images based on Faster-RCNN
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