SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey | |
Wang,Rui2,4; Luo,A-Li1,2,4,5; Chen,Jian-Jun2; Hou,Wen2; Zhang,Shuo2,4; Zhao,Yong-Heng2,4; Li,Xiang-Ru6; Hou,Yong-Hui3,4 | |
刊名 | The Astrophysical Journal
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2020-02-28 | |
卷号 | 891期号:1 |
关键词 | Stellar atmospheres Astronomical methods Spectroscopy |
ISSN号 | 0004-637X |
DOI | 10.3847/1538-4357/ab6dea |
英文摘要 | Abstract The fundamental stellar atmospheric parameters (Teff and log g) and 13 chemical abundances are derived for medium-resolution spectroscopy from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Medium Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet have precisions of 119 K for Teff and 0.17 dex for log g. The abundance precision of 11 elements including [C/H], [N/H], [O/H], [Mg/H], [Al/H], [Si/H], [S/H], [Ca/H], [Ti/H], [Cr/H], [Fe/H], and [Ni/H] are 0.06?~?0.12 dex, while that of [Cu/H] is 0.19 dex. These precisions can be reached even for spectra with signal-to-noise ratios as low as 10. The results of SPCANet are consistent with those from other surveys such as APOGEE, GALAH, and RAVE, and are also validated with the previous literature values including clusters and field stars. The catalog of the estimated parameters is available at doi:10.12149/101012. |
语种 | 英语 |
出版者 | The American Astronomical Society |
WOS记录号 | IOP:0004-637X-891-1-AB6DEA |
内容类型 | 期刊论文 |
源URL | [http://ir.bao.ac.cn/handle/114a11/53983] ![]() |
专题 | 中国科学院国家天文台 |
作者单位 | 1.Institute for Astronomical Science and School of Information Management, Dezhou University, Dezhou 253023, People's Republic of China 2.Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, People's Republic of China lal@nao.cas.cn 3.Nanjing Institute of Astronomical Optics, & Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042, People's Republic of China 4.University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China 5.Department of Physics and Astronomy, University of Delaware, Newark, DE, 19716, USA 6.South China Normal University, Guangzhou 510631, People's Republic of China |
推荐引用方式 GB/T 7714 | Wang,Rui,Luo,A-Li,Chen,Jian-Jun,et al. SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey[J]. The Astrophysical Journal,2020,891(1). |
APA | Wang,Rui.,Luo,A-Li.,Chen,Jian-Jun.,Hou,Wen.,Zhang,Shuo.,...&Hou,Yong-Hui.(2020).SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey.The Astrophysical Journal,891(1). |
MLA | Wang,Rui,et al."SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey".The Astrophysical Journal 891.1(2020). |
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