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Searching for Hot Subdwarf Stars from the LAMOST Spectra. III. Classification of Hot Subdwarf Stars in the Fourth Data Release of LAMOST Using a Deep Learning Method

文献类型：期刊论文

作者Bu, Yude2,3; Zeng, Jingjing4; Lei, Zhenxin1,3; Yi, Zhenping5
刊名ASTROPHYSICAL JOURNAL
出版日期2019-12-01
卷号886期号:2页码:10
ISSN号0004-637X
关键词methods: data analysis stars: statistics subdwarfs
DOI10.3847/1538-4357/ab4c47
英文摘要Hot subdwarf stars are core He burning stars located at the blue end of the horizontal branch, which is also known as the extreme horizontal branch. The spectra of hot subdwarf stars can provide detailed information on stellar atmospheric parameters, such as the effective temperature, gravity, and abundances of helium, which can help clarify the astrophysical and statistical properties of hot subdwarf stars. These properties provide important constraints on the theoretical models of stars. The identification of hot subdwarf stars from the spectral data obtained by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) can significantly increase the sample size and help us to better understand the nature of hot subdwarf stars. In this study, we propose a new method to select hot subdwarf stars from LAMOST spectra using convolutional neural networks and a support vector machine (CNN + SVM). By applying CNN+SVM to sample data selected from LAMOST Data Release 4 we obtain an F1 score of 76.98%. A comparison with other machine-learning algorithms, such as linear discriminant analysis and k-nearest neighbors, demonstrates that an approach based on CNN+SVM obtains better results than the others. Therefore it is a method well suited to the problem of searching for hot subdwarf stars in large spectroscopic surveys. Finally, we include an extensive discussion on how we determined the optimal hyperparameters of our proposed method.
WOS关键词SUPPORT VECTOR MACHINES ; 1ST DATA RELEASE ; WHITE-DWARF ; SELECTION ; GALAXIES ; CATALOG
资助项目National Natural Science Foundation of China[11873037] ; National Natural Science Foundation of China[11603012] ; National Natural Science Foundation of China[11603014] ; National Natural Science Foundation of China[11803016] ; National Natural Science Foundation of China[U1931209] ; Young Scholars Program of Shandong University, Weihai[2016WHWLJH09] ; Natural Science Foundation of Shandong Province, China[ZR2015AQ011] ; China Postdoctoral Science Foundation[2015M571124] ; Natural Science Foundation of Hunan province[2017JJ3283] ; Strategic Priority Research Program (The Emergence of Cosmological Structures) of the Chinese Academy of Sciences[XDB09000000]
WOS研究方向Astronomy & Astrophysics
语种英语
出版者IOP PUBLISHING LTD
WOS记录号WOS:000515070100006
资助机构National Natural Science Foundation of China ; Young Scholars Program of Shandong University, Weihai ; Natural Science Foundation of Shandong Province, China ; China Postdoctoral Science Foundation ; Natural Science Foundation of Hunan province ; Strategic Priority Research Program (The Emergence of Cosmological Structures) of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Young Scholars Program of Shandong University, Weihai ; Natural Science Foundation of Shandong Province, China ; China Postdoctoral Science Foundation ; Natural Science Foundation of Hunan province ; Strategic Priority Research Program (The Emergence of Cosmological Structures) of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Young Scholars Program of Shandong University, Weihai ; Natural Science Foundation of Shandong Province, China ; China Postdoctoral Science Foundation ; Natural Science Foundation of Hunan province ; Strategic Priority Research Program (The Emergence of Cosmological Structures) of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Young Scholars Program of Shandong University, Weihai ; Natural Science Foundation of Shandong Province, China ; China Postdoctoral Science Foundation ; Natural Science Foundation of Hunan province ; Strategic Priority Research Program (The Emergence of Cosmological Structures) of the Chinese Academy of Sciences
源URL[http://ir.bao.ac.cn/handle/114a11/28634]  
专题中国科学院国家天文台
通讯作者Bu, Yude
作者单位1.Univ Xiangtan, Phys Dept, Xiangtan 411105, Hunan, Peoples R China
2.Shandong Univ, Sch Math & Stat, Weihai 264209, Shandong, Peoples R China
3.Chinese Acad Sci, Natl Astron Observ, Key Lab Opt Astron, Beijing 100012, Peoples R China
4.Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Shanxi, Peoples R China
5.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Shandong, Peoples R China
推荐引用方式
GB/T 7714		 Bu, Yude,Zeng, Jingjing,Lei, Zhenxin,et al. Searching for Hot Subdwarf Stars from the LAMOST Spectra. III. Classification of Hot Subdwarf Stars in the Fourth Data Release of LAMOST Using a Deep Learning Method[J]. ASTROPHYSICAL JOURNAL,2019,886(2):10.
APA Bu, Yude,Zeng, Jingjing,Lei, Zhenxin,&Yi, Zhenping.(2019).Searching for Hot Subdwarf Stars from the LAMOST Spectra. III. Classification of Hot Subdwarf Stars in the Fourth Data Release of LAMOST Using a Deep Learning Method.ASTROPHYSICAL JOURNAL,886(2),10.
MLA Bu, Yude,et al."Searching for Hot Subdwarf Stars from the LAMOST Spectra. III. Classification of Hot Subdwarf Stars in the Fourth Data Release of LAMOST Using a Deep Learning Method".ASTROPHYSICAL JOURNAL 886.2(2019):10.

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