Kavli Affiliate: Feng Wang
| First 5 Authors: Tingting Xu, Chao Liu, Feng Wang, Weirong Huang, Hui Deng
| Summary:
The identification and analysis of different variable sources is a hot issue
in astrophysical research. The Large Sky Area Multi-Object Fiber Spectroscopic
Telescope (LAMOST) spectroscopic survey has accumulated massive spectral data
but contains no information about variable sources. Although a few related
studies present variable source catalogs for the LAMOST, the studies still have
a few deficiencies regarding the type and number of variable sources
identified. In this study, we presented a statistical modeling approach to
identify variable source candidates. We first crossed the Kepler, Sloan Digital
Sky Survey (SDSS), and Zwicky Transient Facility (ZTF) catalogs to obtain light
curves data of variable and non-variable sources. The data are then modeled
statistically using commonly used variability parameters, respectively. And
then, an optimal variable source identification model is determined using the
Receiver Operating Characteristic (ROC) curve and four credible evaluation
indices such as precision, accuracy, recall, and F1score. Based on this
identification model, a catalog of LAMOST variable sources (including 631,769
variable source candidates with a probability greater than 95% and so on) is
obtained. To validate the correctness of the catalog, we performed a two-by-two
cross-comparison with the GAIA catalog and other published variable source
catalogs. We achieved the correct rate ranging from 50% to 100%. Among the
123,756 sources cross-matched, our variable source catalog identifies 85,669
with a correct rate of 69%, which indicates that the variable source catalog
presented in this study is credible.
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