Abstract

Abstract The identification and analysis of different variable sources is a hot topic in astrophysical research. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic survey has accumulated a mass of 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 present a statistical modeling approach to identify variable source candidates. We first cross-match the Kepler, Sloan Digital Sky Survey, and Zwicky Transient Facility catalogs to obtain light-curve data of variable and nonvariable sources. The data are then modeled statistically using commonly used variability parameters. Then, an optimal variable source identification model is determined using the Receiver Operating Characteristic curve and four credible evaluation indices such as precision, accuracy, recall, and F1-score. 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 perform a two-by-two cross-comparison with the Gaia catalog and other published variable source catalogs. We achieve 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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call