Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Bent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intracluster medium. A combined method, which involves a deep learning-based radio source finder...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal Supplement Series |
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| Online Access: | https://doi.org/10.3847/1538-4365/ad9c6d |
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| author | Baoqiang Lao Heinz Andernach Xiaolong Yang Xiang Zhang Rushuang Zhao Zhen Zhao Yun Yu Xiaohui Sun Sheng-Li Qin |
| author_facet | Baoqiang Lao Heinz Andernach Xiaolong Yang Xiang Zhang Rushuang Zhao Zhen Zhao Yun Yu Xiaohui Sun Sheng-Li Qin |
| author_sort | Baoqiang Lao |
| collection | DOAJ |
| description | Bent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intracluster medium. A combined method, which involves a deep learning-based radio source finder along with visual inspection, has been utilized to search for BTRGs from the Faint Images of the Radio Sky at Twenty cm survey images. Consequently, a catalog of 4876 BTRGs has been constructed, among which 3871 are newly discovered. Based on the classification scheme of the opening angle between the two jets of the galaxy, BTRGs are typically classified as either wide-angle-tail (WAT) sources or narrow-angle-tail (NAT) sources. Our catalog comprises 4424 WATs and 652 NATs. Among these, optical counterparts are identified for 4193 BTRGs. This catalog covers luminosities in the range of 1.91 × 10 ^20 ≤ L _1.4 GHz ≤ 1.45 × 10 ^28 W Hz ^−1 and redshifts from z = 0.0023 to z = 3.43. Various physical properties of these BTRGs and their statistics are presented. Particularly, by the nearest neighbor method, we found that 1825 BTRGs in this catalog belong to galaxy clusters reported in literature. |
| format | Article |
| id | doaj-art-41828ea2fea44dc8bcac7b0d4847baf5 |
| institution | DOAJ |
| issn | 0067-0049 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astrophysical Journal Supplement Series |
| spelling | doaj-art-41828ea2fea44dc8bcac7b0d4847baf52025-08-20T03:09:28ZengIOP PublishingThe Astrophysical Journal Supplement Series0067-00492025-01-0127624610.3847/1538-4365/ad9c6dIdentification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual InspectionBaoqiang Lao0https://orcid.org/0000-0002-3426-3269Heinz Andernach1https://orcid.org/0000-0003-4873-1681Xiaolong Yang2https://orcid.org/0000-0002-4439-5580Xiang Zhang3https://orcid.org/0000-0002-2218-5638Rushuang Zhao4https://orcid.org/0000-0002-1243-0476Zhen Zhao5https://orcid.org/0000-0002-0796-4078Yun Yu6https://orcid.org/0009-0001-3764-4307Xiaohui Sun7https://orcid.org/0000-0002-3464-5128Sheng-Li Qin8https://orcid.org/0000-0003-2302-0613School of Physics and Astronomy, Yunnan University , Kunming 650091, People’s Republic of China ; lbq19881213@gmail.comThüringer Landessternwarte , Sternwarte 5, D-07778 Tautenburg, Germany; Depto. de Astronomía, Univ. de Guanajuato , Callejón de Jalisco s/n, Guanajuato, C.P. 36023, GTO, MexicoShanghai Astronomical Observatory, Chinese Academy of Sciences , Shanghai 200030, People’s Republic of ChinaLESIA, Observatoire de Paris, Université PSL , CNRS, Sorbonne Université, Université Paris Cité, 5 place Jules Janssen, 92195 Meudon, FranceSchool of Physics and Electronic Science, Guizhou Normal University , Guiyang 550001, People’s Republic of ChinaShanghai AI Laboratory , Shanghai 200003, People’s Republic of ChinaShanghai Astronomical Observatory, Chinese Academy of Sciences , Shanghai 200030, People’s Republic of ChinaSchool of Physics and Astronomy, Yunnan University , Kunming 650091, People’s Republic of China ; lbq19881213@gmail.comSchool of Physics and Astronomy, Yunnan University , Kunming 650091, People’s Republic of China ; lbq19881213@gmail.comBent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio jets are deflected by the intracluster medium. A combined method, which involves a deep learning-based radio source finder along with visual inspection, has been utilized to search for BTRGs from the Faint Images of the Radio Sky at Twenty cm survey images. Consequently, a catalog of 4876 BTRGs has been constructed, among which 3871 are newly discovered. Based on the classification scheme of the opening angle between the two jets of the galaxy, BTRGs are typically classified as either wide-angle-tail (WAT) sources or narrow-angle-tail (NAT) sources. Our catalog comprises 4424 WATs and 652 NATs. Among these, optical counterparts are identified for 4193 BTRGs. This catalog covers luminosities in the range of 1.91 × 10 ^20 ≤ L _1.4 GHz ≤ 1.45 × 10 ^28 W Hz ^−1 and redshifts from z = 0.0023 to z = 3.43. Various physical properties of these BTRGs and their statistics are presented. Particularly, by the nearest neighbor method, we found that 1825 BTRGs in this catalog belong to galaxy clusters reported in literature.https://doi.org/10.3847/1538-4365/ad9c6dRadio astronomyRadio galaxiesExtragalactic radio sourcesActive galactic nuclei |
| spellingShingle | Baoqiang Lao Heinz Andernach Xiaolong Yang Xiang Zhang Rushuang Zhao Zhen Zhao Yun Yu Xiaohui Sun Sheng-Li Qin Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection The Astrophysical Journal Supplement Series Radio astronomy Radio galaxies Extragalactic radio sources Active galactic nuclei |
| title | Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection |
| title_full | Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection |
| title_fullStr | Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection |
| title_full_unstemmed | Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection |
| title_short | Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection |
| title_sort | identification of 4876 bent tail radio galaxies in the first survey using deep learning combined with visual inspection |
| topic | Radio astronomy Radio galaxies Extragalactic radio sources Active galactic nuclei |
| url | https://doi.org/10.3847/1538-4365/ad9c6d |
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