Zhijia Tian1 , Xiaowei Liu2 , Haibo Yuan3 , Xuan Fang4,5 , Bingqiu Chen2 , Maosheng Xiang6 , Yang Huang2 , Shaolan Bi3 , Wuming Yang3 , Yaqian Wu7 , Chun Wang8,10, Huawei Zhang8 , Zhiying Huo7 , Yong Yang2 , Gaochao Liu9 , Jincheng Guo8,10 , and Meng Zhang8
1 Department of Astronomy, Key Laboratory of Astroparticle Physics of Yunnan Province, Yunnan University, Kunming 650200, Peopleʼs Republic of China tianzhijia@ynu.edu.cn 2 South-Western Institute for Astronomy Research, Yunnan University, Chenggong District, Kunming 650500, Peopleʼs Republic of China; x.liu@pku.edu.cn 3 Department of Astronomy, Beijing Normal University, Beijing 100875, Peopleʼs Republic of China 4 Key Laboratory of Optical Astronomy, National Astronomical Observatories of Chinese Academy of Sciences (NAOC), 20A Datun Road, Chaoyang District, Beijing 100101, Peopleʼs Republic of China 5 Department of Physics, Faculty of Science, The University of Hong Kong, Pokfulam Road, Hong Kong, Peopleʼs Republic of China 6 Max-Planck Institute for Astronomy, Heidelberg, Germany 7 National Astronomy Observatories, Chinese Academy of Sciences, Beijing 100012, Peopleʼs Republic of China 8 Department of Astronomy, Peking University, Beijing 100871, Peopleʼs Republic of China 9 China Three Gorges University, Yichang 443002, Peopleʼs Republic of China Received 2019 February 19; revised 2020 May 28; accepted 2020 May 29; published 2020 July 28
Abstract
Radial velocity (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 RV variations with simulated ones. We build a catalog of 80,702 RV variable candidates with probability greater than 0.60 by analyzing the multi-epoch sources covered by LAMOST DR4. Simulations and cross-identififications 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. 3138 RV variables are classifified through cross-identififications with published results in literatures. By using the 3138 sources common in both LAMOST and a collection of published RV variable catalogs, we are able to analyze LAMOST’s RV variable detection rate. The effificiency of the method adopted in this work relies not only on the sampling frequency of observations but also periods and amplitudes of RV variables. With the progress of LAMOST, Gaia, and other surveys, more and more RV variables will be confifirmed and classifified. This catalog is valuable for other large-scale surveys, especially for RV variable searches. The catalog will be released according to the LAMOST Data Policy via......
