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Li X.,South China Normal University | Li X.,University of Windsor | Wu Q.M.J.,University of Windsor | Luo A.,CAS National Astronomical Observatories | And 8 more authors.
Astrophysical Journal | Year: 2014

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 T eff, 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 T eff (101.609921 K for T eff), 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 T eff, 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 T eff (124.545075 K for T eff), 0.198928 dex for log g, and 0.206814 dex for [Fe/H]. © 2014. The American Astronomical Society. All rights reserved..


Shao X.,CAS National Astronomical Observatories | Shao X.,University of Chinese Academy of Sciences | Shao X.,Key Laboratory of Optical Astronomy | Shao X.,Hebei Normal University | And 12 more authors.
Proceedings of the International Astronomical Union | Year: 2012

We study and compare the stellar populations of host galaxies of different types of supernovae (SNe): SN Ia and core collapse SN (SN II and SN Ibc) at the same time. The 234 sample galaxies are selected by cross-matching the Asiago Supernova Catalogue (ASC) and the SDSS-DR7 main galaxy sample (MGS). The STARLIGHT software is used to analyze their stellar populations by fitting the continua and absorption lines of the hosts. © 2013 International Astronomical Union.


Du W.,CAS National Astronomical Observatories | Du W.,Key Laboratory of Optical Astronomy | Du W.,University of Chinese Academy of Sciences | Luo A.L.,CAS National Astronomical Observatories | And 3 more authors.
Astronomical Journal | Year: 2012

Adopting the SPECTRUM package, which is a stellar spectral synthesis program, we have synthesized a comprehensive set of 2890 near-infrared (NIR) synthetic spectra with a resolution and wavelength sampling similar to the Sloan Digital Sky Survey (SDSS) and the forthcoming Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectra. During the synthesis, we applied the "New grids of ATLAS9 Model Atmosphere" to develop a grid of local thermodynamic equilibrium model atmospheres for effective temperatures (T eff) ranging from 3500 to 7500K, for surface gravities (log g) from 0.5 to 5.0dex, for metallicities ([Fe/H]) from -4.0 to 0.5dex, and for solar ([α/Fe] = 0.0dex) and non-solar ([α/Fe] = +0.4dex) abundances. This synthetic stellar library is composed of 1350 solar scaled abundance (SSA) and 1530 non-solar scaled abundance (NSSA) spectra, grounding on which we have defined a new set of NIR Ca II triplet indices and an index CaT as the sum of the three. These defined indices were automatically measured on every spectrum of the synthetic stellar library and calibrated with the indices computed on the observational spectra from the INDO-U.S. stellar library. In order to check the effect of α-element enhancement on the so-defined Ca II indices, we compared indices measured on the SSA spectra with those on the NSSA ones at the same trine of stellar parameters (T eff, log g, [Fe/H]); luckily, little influences of α-element enhancement were found. Furthermore, comparisons of our synthetic indices with the observational ones from measurements on the INDO-U.S. stellar library, the SDSS-DR7 and SDSS-DR8 spectroscopic survey are presented, respectively, for dwarfs and giants in specific. For dwarfs, our synthetic indices could well reproduce the behaviors of the observational indices versus stellar parameters, which verifies the validity of our index definitions for dwarfs. For giants, the consistency between our synthetic indices and the observational ones does not appear to be as good. However, a new synthetic library of NIR Ca II indices has been founded for deeper studies on the NIR wave band of stellar spectra, and this library is particularly appropriate for the SDSS and the forthcoming LAMOST stellar spectra. We have regressed the strength of the CaT index as a function of stellar parameters for both dwarfs and giants after a series of experimental investigations into relations of the indices with stellar parameters. For dwarfs, log g has little effect on the indices, while [Fe/H] and T eff play a role together. The leading factor is probably [Fe/H], which changes the strength of the indices by a positive trend. For giants, log g starts to influence the strength of the indices by a negative trend for the metal-poor, and even impact deeply for the metal-rich; besides, [Fe/H] and T eff still matter. In addition, we briefly discussed the major differences between our Ca II triplet indices and the CaHK doublet indices. Ultimately, a supplemental experiment was carried out to show that spectral noises do have effects on our set of NIR Ca II indices. However, the influence is not weak enough to be ignored if the signal-to-noise ratio falls below 20. © 2012. The American Astronomical Society. All rights reserved.


Liang Y.,CAS National Astronomical Observatories | Liang Y.,Key Laboratory of Optical Astronomy | Shao X.,CAS National Astronomical Observatories | Shao X.,Key Laboratory of Optical Astronomy | And 2 more authors.
Proceedings of the International Astronomical Union | Year: 2012

We gather a sample of both metal-rich and metal-poor galaxies. Both samples have oxygen abundances estimated from electron temperature (Te). The calibration of the emission-line ratio, N2(≡log([NII]6583/Hα), to oxygen abundances is then re-derived from this combined sample, finding good agreement for the wide metallicity and line-ratio ranges considered. © 2013 International Astronomical Union.


Du W.,CAS National Astronomical Observatories | Du W.,Key Laboratory of Optical Astronomy | Du W.,University of Chinese Academy of Sciences | Luo A.-L.,CAS National Astronomical Observatories | And 3 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2012

In the present paper, we analysed the effects of spectral resolutions and signal-to-noise ratios (SNRs) on 19 atomic absorption line indices of Lick index system. First of all, adopting method of convolving a spectrum with a Gaussian profile, we transformed spectra into those under different resolutions and then measured the line indices on them. Comparisons of the indices under various resolutions allow to investigate the impact of spectral resolution change on the accuracy of measurements of indices. Secondly, by adding random noises with different Gaussian distribution to a spectrum, the authors transformed theoretical spectra with no noises into those under diverse SNRs and then measured line indices on them. Comparisons of the indices under different SNRs greatly helped analyse the influence of SNR on the precision of the measurements of line indices. It comes from comparisons and analysis that the spectral resolution change can cause an index measurement change depending on the extent of the change of spectral resolution. Such a kind of change relationship varies with the indices. The lower the SNR, the less precise the measurements of indices. The effect of SNR on the measurements of indices can be ignored if SNR is larger than 25.

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