ASTEROSEISMIC-BASED ESTIMATION OF THE SURFACE GRAVITY FOR THE LAMOST GIANT STARS
- Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, 20 A Datun Road, Beijing 100012 (China)
- Departamento de Física Teórica, Facultad de Ciencias, Universidad Autonóma de Madrid, E-28049 Cantoblanco, Madrid (Spain)
- Department of Astronomy, Beijing Normal University, 19 Avenue Xinjiekouwai, Beijing 100875 (China)
- Nanjing Institute of Astronomical Optics and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042 (China)
Asteroseismology is one of the most accurate approaches to estimate the surface gravity of a star. However, most of the data from the current spectroscopic surveys do not have asteroseismic measurements, which is very expensive and time consuming. In order to improve the spectroscopic surface gravity estimates for a large amount of survey data with the help of the small subset of the data with seismic measurements, we set up a support vector regression (SVR) model for the estimation of the surface gravity supervised by 1374 Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) giant stars with Kepler seismic surface gravity. The new approach can reduce the uncertainty of the estimates down to about 0.1 dex, which is better than the LAMOST pipeline by at least a factor of 2, for the spectra with signal-to-noise ratio higher than 20. Compared with the log g estimated from the LAMOST pipeline, the revised log g values provide a significantly improved match to the expected distribution of red clump and red giant branch stars from stellar isochrones. Moreover, even the red bump stars, which extend to only about 0.1 dex in log g, can be discriminated from the new estimated surface gravity. The method is then applied to about 350,000 LAMOST metal-rich giant stars to provide improved surface gravity estimates. In general, the uncertainty of the distance estimate based on the SVR surface gravity can be reduced to about 12% for the LAMOST data.
- OSTI ID:
- 22522233
- Journal Information:
- Astrophysical Journal, Vol. 807, Issue 1; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0004-637X
- Country of Publication:
- United States
- Language:
- English
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