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Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation

文献类型：期刊论文

作者Li MY(李敏榆)3; Qian, Sheng-Bang2; Zhu LY(朱俐颖)1,3; Liao WP(廖文萍)1,3; Chang, Lin-Feng2; Zhao EG(赵二刚)3; Shi XD(施相东)3; Li, Fu-Xing2; Sun, Qi-Bin2; Li P(李平)1,3
刊名ASTRONOMICAL JOURNAL
出版日期2025-09-01
卷号170期号:3
ISSN号0004-6256
DOI10.3847/1538-3881/aded86
产权排序第1完成单位
文献子类Article
英文摘要Since the variety of their light curve morphologies, the vast majority of the known heartbeat stars (HBSs) have been discovered by manual inspection. Machine learning, which has already been successfully applied to the classification of variable stars based on light curves, offers another possibility for the automatic detection of HBSs. We propose a novel feature extraction approach for HBSs. First, the orbital frequencies are calculated automatically according to the Fourier spectra of the light curves. Then, the amplitudes of the first 100 harmonics are extracted. Finally, these harmonics are normalized as feature vectors of the light curve. A training data set of synthetic light curves is constructed using ELLC, and their features are fed into recurrent neural networks (RNNs) for supervised learning, with the expected output being the eccentricity of these light curves. The performance of the RNNs is evaluated using a test data set of synthetic light curves, achieving 95% accuracy. When applied to known HBSs from the Optical Gravitational Lensing Experiment, Kepler, and Transiting Exoplanet Survey Satellite surveys, the networks achieve an average accuracy of 86%. This method successfully identifies four new HBSs within the eclipsing binary catalog of Kirk et al. The use of orbital harmonics as features for HBSs proves to be a practical approach that significantly reduces the computational cost of neural networks. RNNs show excellent performance in recognizing this type of time series data. This method not only allows efficient identification of HBSs but can also be extended to recognize other types of periodic variable stars.
学科主题天文学 ; 恒星与银河系
URL标识查看原文
出版地TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
WOS关键词TIDALLY EXCITED OSCILLATIONS ; LIGHT-CURVE SOLUTIONS ; ECCENTRIC KEPLER BINARIES ; ECLIPSING BINARY ; VARIABLE-STARS ; GIANT STARS ; RED GIANTS ; TESS DATA ; CLASSIFICATION ; SYSTEMS
资助项目International Corporation Project of the National Key R&D Program of China[202501AS070055]; International Corporation Project of the National Key R&D Program of China[202401AS070046]; International Corporation Project of the National Key R&D Program of China[202503AP140013]; International Corporation Project of the National Key R&D Program of China[202301AT070352]; Yunnan Fundamental Research Projects[020GJHZ2023030GC]; International Partnership Program of Chinese Academy of Sciences[CMS-CSST-2025-A16]; China Manned Space Program; CAS ``Light of West China Program[202201AT070092]; Basic Research Project of Yunnan Province; Yunnan Revitalization Talent Support Program[2025M773194]; China Postdoctoral Science Foundation[GZC20252095]; Postdoctoral Fellowship Program of CPSF; NASA Explorer Program
WOS研究方向Astronomy & Astrophysics
语种英语
WOS记录号WOS:001549236300001
出版者IOP Publishing Ltd
资助机构International Corporation Project of the National Key R&D Program of China[202501AS070055, 202401AS070046, 202503AP140013, 202301AT070352] ; Yunnan Fundamental Research Projects[020GJHZ2023030GC] ; International Partnership Program of Chinese Academy of Sciences[CMS-CSST-2025-A16] ; China Manned Space Program ; CAS ``Light of West China Program[202201AT070092] ; Basic Research Project of Yunnan Province ; Yunnan Revitalization Talent Support Program[2025M773194] ; China Postdoctoral Science Foundation[GZC20252095] ; Postdoctoral Fellowship Program of CPSF ; NASA Explorer Program
版本出版稿
源URL[http://ir.ynao.ac.cn/handle/114a53/28509]  
专题云南天文台_双星与变星研究组
通讯作者Qian, Sheng-Bang; Zhu LY(朱俐颖)
作者单位1.University of Chinese Academy of Sciences, No.1 Yanqihu East Road, Huairou District, Beijing 101408, People’s Republic of China
2.Department of Astronomy, School of Physics and Astronomy, Key Laboratory of Astroparticle Physics of Yunnan Province, Yunnan University, Kunming 650091, People’s Republic of China; qiansb@ynu.edu.cn;
3.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, People’s Republic of China; zhuly@ynao.ac.cn;
推荐引用方式
GB/T 7714		 Li MY,Qian, Sheng-Bang,Zhu LY,et al. Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation[J]. ASTRONOMICAL JOURNAL,2025,170(3).
APA 李敏榆.,Qian, Sheng-Bang.,朱俐颖.,廖文萍.,Chang, Lin-Feng.,...&李平.(2025).Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation.ASTRONOMICAL JOURNAL,170(3).
MLA 李敏榆,et al."Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation".ASTRONOMICAL JOURNAL 170.3(2025).

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来源：云南天文台

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