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• W3100336469 abstract "Large-scale and deep sky survey missions are rapidly collecting a large amount of stellar spectra, which necessitate the estimation of atmospheric parameters directly from spectra and make it feasible to statistically investigate latent principles in a large data set. We present a technique for estimating parameters Teff, log g, and [Fe/H] from stellar spectra. With this technique, we first extract features from stellar spectra using the LASSO algorithm; then, the parameters are estimated from the extracted features using the support vector regression. On a subsample of 20,000 stellar spectra from the Sloan Digital Sky Survey (SDSS) with reference parameters provided by the SDSS/SEGUE Spectroscopic Parameter Pipeline, estimation consistency are 0.007458 dex for log Teff (101.609921 K for Teff), 0.189557 dex for log g, and 0.182060 for [Fe/H], where the consistency is evaluated by mean absolute error. Prominent characteristics of the proposed scheme are sparseness, locality, and physical interpretability. In this work, each spectrum consists of 3821 fluxes, and 10, 19, and 14 typical wavelength positions are detected, respectively, for estimating Teff, log g, and [Fe/H]. It is shown that the positions are related to typical lines of stellar spectra. This characteristic is important in investigating physical indications from analysis results. Then, stellar spectra can be described by the individual fluxes on the detected positions (PD) or local integration of fluxes near them (LI). The aforementioned consistency is the result based on features described by LI. If features are described by PD, consistency is 0.009092 dex for log Teff (124.545075 K for Teff), 0.198928 dex for log g, and 0.206814 dex for [Fe/H]." @default.
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• W3100336469 date "2014-07-10" @default.
• W3100336469 modified "2023-10-16" @default.
• W3100336469 title "SDSS/SEGUE SPECTRAL FEATURE ANALYSIS FOR STELLAR ATMOSPHERIC PARAMETER ESTIMATION" @default.
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• W3100336469 doi "https://doi.org/10.1088/0004-637x/790/2/105" @default.
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