Spectral classification of stars based on LAMOST spectra  

作　　者：Chao Liu Wen-Yuan Cui Bo Zhang Jun-Chen Wan Li-Cai Deng Yong-Hui Hou Yue-Fei Wang Ming Yang Yong Zhang 

机构地区：[1]Key Laboratory of Optical Astronomy,National Astronomical Observatories,Chinese Academy of Sciences [2]Department of Physics,Hebei Normal University [3]Nanjing Institute of Astronomical Optics & Technology,National Astronomical Observatories,Chinese Academy of Sciences

出　　处：《Research in Astronomy and Astrophysics》2015年第8期1137-1153,共17页天文和天体物理学研究（英文版）

基　　金：supported by the Strategic Priority Research Program "The Emergence of Cosmological Structures" of the Chinese Academy of Sciences (Grant No. XDB09000000);the National Key Basic Research Program of China (2014CB845700);CL acknowledges the National Natural Science Foundation of China (NSFC, Grant Nos. 11373032, 11333003 and U1231119)

摘　　要：In this work, we select spectra of stars with high signal-to-noise ratio from LAMOST data and map their MK classes to the spectral features. The equivalent widths of prominent spectral lines, which play a similar role as multi-color photometry, form a clean stellar locus well ordered by MK classes. The advantage of the stellar locus in line indices is that it gives a natural and continuous classification of stars consistent with either broadly used MK classes or stellar astrophysical parameters. We also employ an SVM-based classification algorithm to assign MK classes to LAMOST stellar spectra. We find that the completenesses of the classifications are up to 90% for A and G type stars, but they are down to about 50% for OB and K type stars. About 40% of the OB and K type stars are mis-classified as A and G type stars,respectively. This is likely due to the difference in the spectral features between late B type and early A type stars or between late G and early K type stars being very weak. The relatively poor performance of the automatic MK classification with SVM suggests that the direct use of line indices to classify stars is likely a more preferable choice.In this work, we select spectra of stars with high signal-to-noise ratio from LAMOST data and map their MK classes to the spectral features. The equivalent widths of prominent spectral lines, which play a similar role as multi-color photometry, form a clean stellar locus well ordered by MK classes. The advantage of the stellar locus in line indices is that it gives a natural and continuous classification of stars consistent with either broadly used MK classes or stellar astrophysical parameters. We also employ an SVM-based classification algorithm to assign MK classes to LAMOST stellar spectra. We find that the completenesses of the classifications are up to 90% for A and G type stars, but they are down to about 50% for OB and K type stars. About 40% of the OB and K type stars are mis-classified as A and G type stars,respectively. This is likely due to the difference in the spectral features between late B type and early A type stars or between late G and early K type stars being very weak. The relatively poor performance of the automatic MK classification with SVM suggests that the direct use of line indices to classify stars is likely a more preferable choice.

关 键 词：techniques： spectroscopic—stars： general—stars： fundamental parameters—stars： statistics—Galaxy： stellar contents 

分 类 号：P144.1[天文地球—天体物理]