A Catalog of RV Variable Star Candidates from LAMOST
Zhijia Tian, Xiaowei Liu, Haibo Yuan, Xuan Fang, Bingqiu Chen,, Maosheng Xiang, Yang Huang, Shaolan Bi, Wuming Yang, Yaqian Wu, Chun Wang,, Huawei Zhang, Zhiying Huo, Yong Yang, Gaochao Liu, Jincheng Guo, Meng, Zhang

TL;DR
This paper presents a catalog of 80,702 candidate RV variable stars identified from LAMOST DR4 data, using radial velocity variations to estimate variability probabilities, with over 80% purity, aiding large-scale stellar variability studies.
Contribution
The study introduces a new catalog of RV variable star candidates from LAMOST DR4, with a novel probability estimation method and validation through cross-identification, enhancing large-scale variability detection.
Findings
Catalog of 80,702 RV candidates with >80% purity
77% binary systems and 7% pulsating stars identified
Detection rate analysis based on cross-matched data
Abstract
RV variable stars are important in astrophysics. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has provided ~ 6.5 million stellar spectra in its Data Release 4 (DR4). During the survey, ~ 4.7 million unique sources were targeted and ~ 1 million stars observed repeatedly. The probabilities of stars being RV variables are estimated by comparing the observed radial velocity variations with the simulated ones. We build a catalog of 80,702 RV variable candidates with probability greater than 0.60 by analyzing the duplicate-observed multi-epoch sources covered by the LAMOST DR4. Simulations and cross-identifications show that the purity of the catalog is higher than 80%. The catalog consists of 77% binary systems and 7% pulsating stars as well as 16% pollution by single stars. 3,138 RV variables are classified through cross-identifications with…
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