Spectral classification of stars based on LAMOST spectra
作者： Chao Liu , Wen-Yuan Cui , Bo Zhang , Jun-Chen Wan , Li-Cai Deng
DOI: 10.1088/1674-4527/15/8/004
关键词: Astrophysics 、 LAMOST 、 Stars 、 Stellar classification 、 G-type main-sequence star 、 Astronomical spectroscopy 、 Physics 、 A-type main-sequence star 、 Spectral line 、 Photometry (optics)
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 prominent lines, which play a similar role as multi-color photometry, form clean stellar locus well ordered by classes. advantage in line indices is that it gives natural continuous classification consistent either broadly used or astrophysical parameters. We also employ an SVM-based algorithm assign spectra. find completenesses classifications are up 90% for A G type stars, but they down about 50% OB K stars. About 40% mis-classified respectively. This likely due difference features between late B early being very weak. relatively poor performance automatic SVM suggests direct use classify more preferable choice.
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