16 July 2008 Automated stellar spectral analysis software for survey spectra
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A spectral analysis pipeline of LAMOST (Large sky Area Multi-Object fiber Spectroscopic Telescope), which produces archived spectral type data, is introduced. By studying observational and theoretical stellar spectra, spectral features within medium resolution are discussed, those lines and bands with high sensitivity to stellar atmospheric parameters, viz. effective temperature (Teff), surface gravity (logg) and metallicity ([Fe/H]), were selected. According to the research, selected features were put into different objective algorithms to extract parameters. The application of three algorithms to SDSS/SEGUE spectra, namely radial basis function neural network (RBFN), back propagation neural network (BPN) and non-parameter regression (NPR), shows intrinsic statistical consistency. Based on the above research, a stellar atmospheric parameter pipeline for LAMOST is designed.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A-Li Luo, A-Li Luo, Yue Wu, Yue Wu, Jingkun Zhao, Jingkun Zhao, Gang Zhao, Gang Zhao, } "Automated stellar spectral analysis software for survey spectra", Proc. SPIE 7019, Advanced Software and Control for Astronomy II, 701935 (16 July 2008); doi: 10.1117/12.788251; https://doi.org/10.1117/12.788251


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