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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
Bu, Yude1,2; Zeng, Jingjing3; Lei, Zhenxin2,4; Yi, Zhenping5
2019-12-01
Source PublicationASTROPHYSICAL JOURNAL
ISSN0004-637X
Volume886Issue:2Pages:10
AbstractHot 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.
Keywordmethods: data analysis stars: statistics subdwarfs
Funding OrganizationNational 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
DOI10.3847/1538-4357/ab4c47
WOS KeywordSUPPORT VECTOR MACHINES ; 1ST DATA RELEASE ; WHITE-DWARF ; SELECTION ; GALAXIES ; CATALOG
Language英语
Funding ProjectNational 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]
Funding OrganizationNational 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
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000515070100006
PublisherIOP PUBLISHING LTD
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Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/28635
Collection中国科学院国家天文台
Corresponding AuthorBu, Yude
Affiliation1.Shandong Univ, Sch Math & Stat, Weihai 264209, Shandong, Peoples R China
2.Chinese Acad Sci, Natl Astron Observ, Key Lab Opt Astron, Beijing 100012, Peoples R China
3.Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Shanxi, Peoples R China
4.Univ Xiangtan, Phys Dept, Xiangtan 411105, Hunan, Peoples R China
5.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Shandong, Peoples R China
Recommended Citation
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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