[Atmospheric parameter estimation for LAMOST/GUOSHOUJING spectra].
It is a key task to estimate the atmospheric parameters from the observed stellar spectra in exploring the nature of stars and universe. With our Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) which begun its formal Sky Survey in September 2012, we are obtaining a mass of stellar spectra in an unprecedented speed. It has brought a new opportunity and a challenge for the research of galaxies. Due to the complexity of the observing system, the noise in the spectrum is relatively large. At the same time, the preprocessing procedures of spectrum are also not ideal, such as the wavelength calibration and the flow calibration. Therefore, there is a slight distortion of the spectrum. They result in the high difficulty of estimating the atmospheric parameters for the measured stellar spectra. It is one of the important issues to estimate the atmospheric parameters for the massive stellar spectra of LAMOST. The key of this study is how to eliminate noise and improve the accuracy and robustness of estimating the atmospheric parameters for the measured stellar spectra. We propose a regression model for estimating the atmospheric parameters of LAMOST stellar(SVM(lasso)). The basic idea of this model is: First, we use the Haar wavelet to filter spectrum, suppress the adverse effects of the spectral noise and retain the most discrimination information of spectrum. Secondly, We use the lasso algorithm for feature selection and extract the features of strongly correlating with the atmospheric parameters. Finally, the features are input to the support vector regression model for estimating the parameters. Because the model has better tolerance to the slight distortion and the noise of the spectrum, the accuracy of the measurement is improved. To evaluate the feasibility of the above scheme, we conduct experiments extensively on the 33 963 pilot surveys spectrums by LAMOST. The accuracy of three atmospheric parameters is log Teff: 0.006 8 dex, log g: 0.155 1 dex, [Fe/H]: 0.104 0 dex.
Yu
Y
Lu
Xiang-Ru
XR
Li
Tan
T
Yang