Abstract
A scheme for estimating atmospheric parameters Teff, log g and [Fe/H] is proposed on the basis of the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Haar wavelet. The proposed scheme consists of three processes. A spectrum is decomposed using the Haar wavelet transform and low-frequency components at the fourth level are considered as candidate features. Then, spectral features from the candidate features are detected using the LASSO algorithm to estimate the atmospheric parameters. Finally, atmospheric parameters are estimated from the extracted spectral features using the support-vector regression (SVR) method. The proposed scheme was evaluated using three sets of stellar spectra from the Sloan Digital Sky Survey (SDSS), Large Sky Area Multi-object Fibre Spectroscopic Telescope (LAMOST) and Kurucz’s model, respectively. The mean absolute errors are as follows: for the 40 000 SDSS spectra, 0.0062 dex for log Teff (85.83 K for Teff), 0.2035 dex for log g and 0.1512 dex for [Fe/H]; for the 23 963 LAMOST spectra, 0.0074 dex for log Teff (95.37 K for Teff), 0.1528 dex for log g and 0.1146 dex for [Fe/H]; for the 10 469 synthetic spectra, 0.0010 dex for log Teff (14.42K for Teff), 0.0123 dex for log g and 0.0125 dex for [Fe/H].
Author
Lu, Yu; Li, Xiangru
Journal
Monthly Notices of the Royal Astronomical Society
Paper Publication Date
September 2015
Paper Type
Astrostatistics