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A machine-learning method to derive the parameters of contact binaries
Ding X(丁旭)1,2,3,4; Ji KF(季凯帆)1,2,3,4; Li XZ(李旭志)1,2,3,4
发表期刊PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN
2021-08
卷号73期号:4页码:786-794
DOI10.1093/pasj/psab042
产权排序第1完成单位
收录类别SCI ; EI
关键词binaries: eclipsing methods: data analysis methods: statistical
摘要

Contact binary stars are important research objects in astrophysics. The calculation speed of deriving the parameters of contact binaries with the Wilson-Devinney program and the Phoebe with Markov chain Monte Carlo (MCMC) program is relatively slow. It is unrealistic to derive the parameters in batches with the program for sky survey data. We obtain a neural network model of supervised learning with the training of synthetic light curves with Phoebe. We calculate the parameters of eight special targets from the simulated data and the Kepler data. Then, we generate the new light curve to fit the light curve of the special target base on these parameters. The correlation index R-2 of the fitting result is more than 0.98. The method can be used to fit the target which has orbital inclinations greater than 50 . By fitting the Kepler data and the observed data on the ground, the method has a good generalization ability to these targets, which have some noise and some starspots. The calculation speed of one light curve with this method is less than seconds. We can derive the parameters quickly in batches to undertake some statistical work for sky survey data with the method.

资助项目Chinese Natural Science FoundationNational Natural Science Foundation of China (NSFC)[12073077] ; Chinese Natural Science FoundationNational Natural Science Foundation of China (NSFC)[11873027] ; Chinese Natural Science FoundationNational Natural Science Foundation of China (NSFC)[11803087] ; Chinese Academy of SciencesChinese Academy of Sciences[Y8XB018001] ; project of Yunnan Science and Technology Department[202003AD150003]
项目资助者Chinese Natural Science FoundationNational Natural Science Foundation of China (NSFC)[12073077, 11873027, 11803087] ; Chinese Academy of SciencesChinese Academy of Sciences[Y8XB018001] ; project of Yunnan Science and Technology Department[202003AD150003]
语种英语
学科领域天文学 ; 恒星与银河系 ; 计算机科学技术 ; 人工智能 ; 计算机应用
学科门类理学 ; 理学::天文学 ; 工学 ; 工学::计算机科学与技术(可授工学、理学学位)
文章类型Article
出版者OXFORD UNIV PRESS
出版地GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
ISSN0004-6264
URL查看原文
WOS记录号WOS:000728400300003
WOS研究方向Astronomy & Astrophysics
WOS类目Astronomy & Astrophysics
关键词[WOS]LIGHT CURVES ; STARS
EI入藏号20220411500462
EI主题词Astrophysics
EI分类号657.2 Extraterrestrial Physics and Stellar Phenomena - 922.1 Probability Theory
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
版本出版稿
条目标识符http://ir.ynao.ac.cn/handle/114a53/24723
专题南方基地
双星与变星研究组
中国科学院天体结构与演化重点实验室
天文技术实验室
通讯作者Ji KF(季凯帆)
作者单位1.Yunnan Observatories, Chinese Academy of Sciences (CAS), P.O. Box 110, 650216 Kunming, China;
2.Key Laboratory of the Structure and Evolution of Celestial Objects, Chinese Academy of Sciences, P.O. Box 110, 650216 Kunming, China;
3.Center for Astronomical Mega-Science, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing, 100012, China;
4.University of the Chinese Academy of Sciences, Yuquan Road 19#, Shijingshan Block, 100049 Beijing, China
第一作者单位中国科学院云南天文台
通讯作者单位中国科学院云南天文台
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Ding X,Ji KF,Li XZ. A machine-learning method to derive the parameters of contact binaries[J]. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN,2021,73(4):786-794.
APA Ding X,Ji KF,&Li XZ.(2021).A machine-learning method to derive the parameters of contact binaries.PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN,73(4),786-794.
MLA Ding X,et al."A machine-learning method to derive the parameters of contact binaries".PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN 73.4(2021):786-794.
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