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| Paper: |
Analysis of Stellar Spectra from LAMOST DR5 with Generative Spectrum Networks |
| Volume: |
523, Astronomical Data Analysis Software and Systems XXVIII |
| Page: |
119 |
| Authors: |
Wang, R.; Luo, A. |
| Abstract: |
We derive the fundamental stellar atmospheric parameters (Teff, log g, [Fe/H] and [α/Fe]) of low-resolution spectroscopy from LAMOST DR5 with Generative Spectrum Networks (GSN), which follows the same scheme as a normal ANN with stellar parameters as the inputs and spectrum as outputs. After training on PHOENIX theoretical spectra, the GSN model performed effectively on producing synthetic spectra. Combining with a Bayes framework, application in analysis of LAMOST observed spectra becomes efficient on the Spark platform. Also, we examined and validated the results by comparing with reference parameters of high-resolution surveys and asteroseismic results. Our method is credible with a precision of 130K for Teff, 0.15 dex for log g, 0.13 dex for [Fe/H] and 0.10 dex for [α/Fe]. |
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