| Minute-cadence observations of the LAMOST Fields with the TMTS - V. Machine learning classification of TMTS catalogues of periodic variable stars | |
Guo, Fangzhou1; Lin, Jie1,2,3; Wang, Xiaofeng1,4; Chen, Xiaodian5; Li, Tanda6,7,8; Chen, Liyang1; Xia, Qiqi1; Mo, Jun1; Xi, Gaobo1; Zhang, Jicheng7; Liu, Qichun1; Jiang, Xiaojun9,10; Yan, Shengyu1; Peng, Haowei1; Liu, Jialian1; Li, Wenxiong11; Lin, Weili1; Xiang, Danfeng1; Ma, Xiaoran1; Cai YZ(蔡永志)1,12,13,14
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| 发表期刊 | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
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| 2024-02-15 | |
| 卷号 | 528期号:4页码:6997-7015 |
| DOI | 10.1093/mnras/stae404 |
| 产权排序 | 第12完成单位 |
| 收录类别 | SCI ; EI |
| 关键词 | surveys binaries: eclipsing stars: oscillations (including pulsations) stars: variables: Scuti |
| 摘要 | Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variable stars has experienced substantial growth for several decades, which significantly deepened our comprehension of stellar structure and binary evolution. The Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) has started to monitor the LAMOST sky areas since 2020, with a cadence of 1 min. During the period from 2020 to 2022, this survey has resulted in densely sampled light curves for similar to 30 000 variables of the maximum powers in the Lomb-Scargle periodogram above the 5 sigma threshold. In this paper, we classified 11 638 variable stars into six main types using xgboost and Random Forest classifiers with accuracies of 98.83 per cent and 98.73 per cent, respectively. Among them, 5301 (45.55 per cent) variables are newly discovered, primarily consisting of delta Scuti stars, demonstrating the capability of TMTS in searching for short-period variables. We cross-matched the catalogue with Gaia's second Data Release and LAMOST's seventh Data Release to obtain important physical parameters of the variables. We identified 5504 delta Scuti stars (including 4876 typical delta Scuti stars and 628 high-amplitude delta Scuti stars), 5899 eclipsing binaries (including EA-, EB-, and EW-type), and 226 candidates of RS Canum Venaticorum. Leveraging the metal abundance data provided by LAMOST and the Galactic latitude, we discovered eight candidates of SX Phe stars within the class of 'delta Scuti stars'. Moreover, with the help of Gaia colour-magnitude diagram, we identified nine ZZ Ceti stars. |
| 资助项目 | National Science Foundation of China[12033003]; National Science Foundation of China[12288102]; National Science Foundation of China; Ma Huateng Foundation[DZ:BS202002]; Scholar Program of Beijing Academy of Science and Technology; New Cornerstone Science Foundation; Cyrus Chun Ying Tang Foundations[12373031]; Cyrus Chun Ying Tang Foundations[12090040]; Cyrus Chun Ying Tang Foundations[12090042]; Cyrus Chun Ying Tang Foundations[U2031203]; National Natural Science Foundation of China[202302AN360001]; International Centre of Supernovae, Yunnan Key Laboratory; National Natural Science Foundation of China (NSFC); Chinese Academy of Sciences (CAS); China Space Station Telescope (CSST) project; Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST); National Development and Reform Commission; Chinese Academy of Sciences; Optical Gravitational Lensing Experiment (OGLE)[MAESTRO 2014/14/A/ST9/00121]; National Science Centre, Poland[GBMF5490]; Ohio State University by the Gordon and Betty Moore Foundation[AST-1908570]; National Science Foundation; Massachusetts, USA |
| 项目资助者 | National Science Foundation of China[12033003, 12288102] ; National Science Foundation of China ; Ma Huateng Foundation[DZ:BS202002] ; Scholar Program of Beijing Academy of Science and Technology ; New Cornerstone Science Foundation ; Cyrus Chun Ying Tang Foundations[12373031, 12090040, 12090042, U2031203] ; National Natural Science Foundation of China[202302AN360001] ; International Centre of Supernovae, Yunnan Key Laboratory ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; China Space Station Telescope (CSST) project ; Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST) ; National Development and Reform Commission ; Chinese Academy of Sciences ; Optical Gravitational Lensing Experiment (OGLE)[MAESTRO 2014/14/A/ST9/00121] ; National Science Centre, Poland[GBMF5490] ; Ohio State University by the Gordon and Betty Moore Foundation[AST-1908570] ; National Science Foundation ; Massachusetts, USA |
| 语种 | 英语 |
| 学科领域 | 天文学 ; 恒星与银河系 |
| 文章类型 | Article |
| 出版者 | OXFORD UNIV PRESS |
| 出版地 | GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND |
| ISSN | 0035-8711 |
| URL | 查看原文 |
| WOS记录号 | WOS:001184933600002 |
| WOS研究方向 | Astronomy & Astrophysics |
| WOS类目 | Astronomy & Astrophysics |
| 关键词[WOS] | DELTA-SCUTI STARS ; ASAS-SN CATALOG ; RR LYRAE STARS ; AUTOMATED CLASSIFICATION ; CONTACT BINARIES ; GALACTIC BULGE ; SX PHOENICIS ; WHITE-DWARF ; GAIA ; EVOLUTION |
| EI入藏号 | 20240915649880 |
| EI主题词 | Stars |
| EI分类号 | 657.2 Extraterrestrial Physics and Stellar Phenomena - 821 Agricultural Equipment and Methods ; Vegetation and Pest Control |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ynao.ac.cn/handle/114a53/26494 |
| 专题 | 南方基地 中国科学院天体结构与演化重点实验室 |
| 作者单位 | 1.Department of Physics and Tsinghua Center for Astrophysics (THCA), Tsinghua University, Haidian District, Beijing 100084, China; 2.CAS Key laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology of China, Hefei 230026, China; 3.School of Astronomy and Space Sciences, University of Science and Technology of China, Hefei 230026, China; 4.Beijing Planetarium, Beijing Academy of Sciences and Technology, Beijing 100044, China; 5.CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China; 6.Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University, Beijing 102206, China; 7.Department of Astronomy, Beijing Normal University, Beijing 100875, China; 8.School of Physics and Astronomy, The University of Birmingham, Birmingham B15 2TT, UK; 9.National Astronomical Observatories of China, Chinese Academy of Sciences, Beijing 100012, China; 10.School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China; 11.The School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel; 12.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, China; 13.Key Laboratory for the Structure and Evolution of Celestial Objects, Chinese Academy of Sciences, Kunming 650216, China; 14.International Centre of Supernovae, Yunnan Key Laboratory, Kunming 650216, China |
| 推荐引用方式 GB/T 7714 | Guo, Fangzhou,Lin, Jie,Wang, Xiaofeng,et al. Minute-cadence observations of the LAMOST Fields with the TMTS - V. Machine learning classification of TMTS catalogues of periodic variable stars[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2024,528(4):6997-7015. |
| APA | Guo, Fangzhou.,Lin, Jie.,Wang, Xiaofeng.,Chen, Xiaodian.,Li, Tanda.,...&蔡永志.(2024).Minute-cadence observations of the LAMOST Fields with the TMTS - V. Machine learning classification of TMTS catalogues of periodic variable stars.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,528(4),6997-7015. |
| MLA | Guo, Fangzhou,et al."Minute-cadence observations of the LAMOST Fields with the TMTS - V. Machine learning classification of TMTS catalogues of periodic variable stars".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 528.4(2024):6997-7015. |
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