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题名: ASTEROSEISMIC-BASED ESTIMATION OF THE SURFACE GRAVITY FOR THE LAMOST GIANT STARS
作者: Liu, Chao1; Fang Min(房敏)2, 3, 4; Wu, Yue1; Deng, Li-Cai1; Wang, Liang1; Wang, Wei1; Fu, Jian-Ning5; Hou, Yong-Hui6; Li, Guang-Wei1; Zhang, Yong6
刊名: ASTROPHYSICAL JOURNAL
出版日期: 2015-07-01
卷号: 807, 期号:1, 页码:4
关键词: asteroseismology ; methods: data analysis ; methods: statistical ; stars: fundamental parameters
学科分类: 天文和天体物理
DOI: 10.1088/0004-637X/807/1/4
文章类型: Article
英文摘要: 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.
WOS标题词: Science & Technology ; Physical Sciences
类目[WOS]: Astronomy & Astrophysics
研究领域[WOS]: Astronomy & Astrophysics
关键词[WOS]: SUPPORT VECTOR REGRESSION ; STELLAR POPULATIONS ; GALACTIC HALO ; ATMOSPHERIC PARAMETERS ; TELESCOPE LAMOST ; SOLAR-TYPE ; KEPLER ; IDENTIFICATION ; METALLICITY ; MACHINES
收录类别: SCI
所属项目名称: PMO_LIB-IR
语种: 英语
WOS记录号: WOS:000358945200004
Citation statistics:
内容类型: 期刊论文
URI标识: http://libir.pmo.ac.cn/handle/332002/14848
Appears in Collections:星系中的恒星形成研究团组_期刊论文

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作者单位: 1.Chinese Acad Sci, Natl Astron Observ, Key Lab Opt Astron, Beijing 100012, Peoples R China
2.Univ Autonoma Madrid, Fac Ciencias, Dept Fis Teor, E-28049 Madrid, Spain
3.Purple Mt Observ, Nanjing 210008, Jiangsu, Peoples R China
4.Key Lab Radio Astron, Nanjing 210008, Jiangsu, Peoples R China
5.Beijing Normal Univ, Dept Astron, Beijing 100875, Peoples R China
6.Chinese Acad Sci, Nanjing Inst Astron Opt & Technol, Natl Astron Observ, Nanjing 210042, Jiangsu, Peoples R China
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