Machine-learning Regression of Extinction in the Second Gaia Data Release
文献类型：期刊论文
| 作者 | Bai,Yu1 ; Liu,JiFeng1,2; Wang,YiLun1,2; Wang,Song1
|
| 刊名 | The Astronomical Journal
 |
| 出版日期 | 2020-02-03 |
| 卷号 | 159期号:3 |
| 关键词 | Interstellar dust extinction Analytical mathematics |
| ISSN号 | 0004-6256 |
| DOI | 10.3847/1538-3881/ab63d5 |
| 英文摘要 | Abstract Machine learning has become a popular tool to help us make better decisions and predictions, based on experiences, observations, and analyzing patterns, within a given data set without explicit functions. In this paper, we describe an application of the supervised machine-learning algorithm to the extinction regression for the second Gaia data release, based on the combination of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, Sloan Extension for Galactic Understanding and Exploration, and the Apache Point Observatory Galactic Evolution Experiment. The derived extinction in our training sample is consistent with other spectrum-based estimates, and its standard deviation of the cross-validations is 0.0127 mag. A blind test is carried out using the RAdial Velocity Experiment catalog, and the standard deviation is 0.0372 mag. Such a precise training sample enables us to regress the extinction, E(BP–RP), for 133 million stars in the second Gaia data release. Of these, 106 million stars have the uncertainties less than 0.1 mag, which suffer less bias from the external regression. We also find that there are high deviations between the extinctions from photometry-based methods, and between spectrum- and photometry-based methods. This implies that the spectrum-based method could bring more signal to a regressing model than multiband photometry, and a higher signal-to-noise ratio would acquire a more reliable result. |
| 语种 | 英语 |
| WOS记录号 | IOP:0004-6256-159-3-AB63D5 |
| 出版者 | The American Astronomical Society |
| 源URL | [http://ir.bao.ac.cn/handle/114a11/53938]  |
| 专题 | 中国科学院国家天文台 |
| 作者单位 | 1.Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100012, People's Republic of China; ybai@nao.cas.cn 2.College of Astronomy and Space Sciences, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China |
| 推荐引用方式 GB/T 7714 | Bai,Yu,Liu,JiFeng,Wang,YiLun,et al. Machine-learning Regression of Extinction in the Second Gaia Data Release[J]. The Astronomical Journal,2020,159(3). |
| APA | Bai,Yu,Liu,JiFeng,Wang,YiLun,&Wang,Song.(2020).Machine-learning Regression of Extinction in the Second Gaia Data Release.The Astronomical Journal,159(3). |
| MLA | Bai,Yu,et al."Machine-learning Regression of Extinction in the Second Gaia Data Release".The Astronomical Journal 159.3(2020). |
入库方式： OAI收割
来源：国家天文台
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