RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests

doi:10.3847/1538-4365/ab5a7c

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	RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests
	Zhang,Jingyi 1,2; Zhang,Yanxia 2; Zhao,Yongheng 2
刊名	The Astrophysical Journal Supplement Series
	2020
卷号	246 期号:1
关键词	RR Lyrae variable stars Stellar types Astronomy databases Metallicity Random Forests Astrostatistics Astronomy data analysis
ISSN号	0067-0049
DOI	10.3847/1538-4365/ab5a7c
英文摘要	Abstract With the increase of known RR Lyrae stars, it is reliable to create classifiers of RR Lyrae stars based on their photometric data or combined photometric and spectroscopic data. Nevertheless the total number of known RR Lyrae stars is still too small compared with the large survey databases. So classification of RR Lyrae stars and other sources belongs to imbalanced learning. Based on Sloan Digital Sky Survey (SDSS) photometric and spectroscopic data, we apply cost-sensitive Random Forests fit for imbalanced learning to preselect RR Lyrae star candidates. Only with photometric data, is the best input pattern. While also considering physical parameters (Teff, [Fe/H], log(g)), the optimal input pattern is Teff, [Fe/H], log(g), , at this moment for cost-sensitive Random Forests, the performance metrics of completeness, contamination, and Matthews correlation coefficient are 0.975, 0.019, and 0.975, respectively. It indicates that adding stellar physical parameters is helpful for identifying RR Lyrae stars from other stars. We apply the best classifiers on the SDSS photometric data and combined photometric data with physical parameters to select RR Lyrae star candidates. Finally 11,041 photometric candidates with spectral type A and F are obtained, and then 304 candidates with physical parameters are selected out. Among the 304 candidates, a small part are HB stars, BS stars, RGB stars, and peculiar stars, and the rest are unknown in the Simbad database. These candidates may be used as the input catalog for time-series follow-up observations.
语种	英语
出版者	The American Astronomical Society
WOS记录号	IOP:0067-0049-246-1-AB5A7C
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/28524]
专题	中国科学院国家天文台
作者单位	1.University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China 2.Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, People’s Republic of China zyx@bao.ac.cn
推荐引用方式 GB/T 7714	Zhang,Jingyi,Zhang,Yanxia,Zhao,Yongheng. RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests[J]. The Astrophysical Journal Supplement Series,2020,246(1).
APA	Zhang,Jingyi,Zhang,Yanxia,&Zhao,Yongheng.(2020).RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests.The Astrophysical Journal Supplement Series,246(1).
MLA	Zhang,Jingyi,et al."RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests".The Astrophysical Journal Supplement Series 246.1(2020).