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Title: The K giant stars from the LAMOST survey data. I. Identification, metallicity, and distance

Abstract

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about two million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with an uncertainty of 0.13 ∼ 0.29 dex based on the equivalent widths of Mg{sub b} and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at K = 11 mag, which is the median brightness of the K giant sample, is about 0.6 mag, corresponding to ∼30% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample.more » Moreover, at about 80 kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.« less

Authors:
; ; ; ; ; ; ; ;  [1]; ;  [2];  [3];  [4];  [5]
  1. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Datun Road 20A, Beijing 100012 (China)
  2. Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180 (United States)
  3. Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030 (China)
  4. Max Planck Institute for Astronomy, Königstuhl 17, Heidelberg D-69117 (Germany)
  5. University of Science and Technology of China, Hefei 230026 (China)
Publication Date:
OSTI Identifier:
22365515
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 790; Journal Issue: 2; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ABUNDANCE; BRIGHTNESS; CLASSIFICATION; DETECTION; GIANT STARS; IRON; METALLICITY; MILKY WAY; PHOTOMETRY; PROBABILITY; SPECTRA; STREAMS; SUN

Citation Formats

Liu, Chao, Deng, Li-Cai, Li, Jing, Gao, Shuang, Yang, Fan, Xu, Yan, Zhang, Yue-Yang, Xin, Yu, Wu, Yue, Carlin, Jeffrey L., Newberg, Heidi Jo, Smith, Martin C., Xue, Xiang-Xiang, and Jin, Ge, E-mail: liuchao@nao.cas.cn. The K giant stars from the LAMOST survey data. I. Identification, metallicity, and distance. United States: N. p., 2014. Web. doi:10.1088/0004-637X/790/2/110.
Liu, Chao, Deng, Li-Cai, Li, Jing, Gao, Shuang, Yang, Fan, Xu, Yan, Zhang, Yue-Yang, Xin, Yu, Wu, Yue, Carlin, Jeffrey L., Newberg, Heidi Jo, Smith, Martin C., Xue, Xiang-Xiang, & Jin, Ge, E-mail: liuchao@nao.cas.cn. The K giant stars from the LAMOST survey data. I. Identification, metallicity, and distance. United States. doi:10.1088/0004-637X/790/2/110.
Liu, Chao, Deng, Li-Cai, Li, Jing, Gao, Shuang, Yang, Fan, Xu, Yan, Zhang, Yue-Yang, Xin, Yu, Wu, Yue, Carlin, Jeffrey L., Newberg, Heidi Jo, Smith, Martin C., Xue, Xiang-Xiang, and Jin, Ge, E-mail: liuchao@nao.cas.cn. Fri . "The K giant stars from the LAMOST survey data. I. Identification, metallicity, and distance". United States. doi:10.1088/0004-637X/790/2/110.
@article{osti_22365515,
title = {The K giant stars from the LAMOST survey data. I. Identification, metallicity, and distance},
author = {Liu, Chao and Deng, Li-Cai and Li, Jing and Gao, Shuang and Yang, Fan and Xu, Yan and Zhang, Yue-Yang and Xin, Yu and Wu, Yue and Carlin, Jeffrey L. and Newberg, Heidi Jo and Smith, Martin C. and Xue, Xiang-Xiang and Jin, Ge, E-mail: liuchao@nao.cas.cn},
abstractNote = {We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about two million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with an uncertainty of 0.13 ∼ 0.29 dex based on the equivalent widths of Mg{sub b} and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at K = 11 mag, which is the median brightness of the K giant sample, is about 0.6 mag, corresponding to ∼30% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample. Moreover, at about 80 kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.},
doi = {10.1088/0004-637X/790/2/110},
journal = {Astrophysical Journal},
number = 2,
volume = 790,
place = {United States},
year = {Fri Aug 01 00:00:00 EDT 2014},
month = {Fri Aug 01 00:00:00 EDT 2014}
}