Affiliation:
1. School of Computer Science, South China Normal University , No. 55 West of Yat-sen Avenue, Guangzhou 510631, China
Abstract
ABSTRACT
This paper investigates the problem of estimating three stellar atmospheric physical parameters and 13 elemental abundances for medium-resolution spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Typical characteristics of these spectra are their huge scale, wide range of spectral signal-to-noise ratio (S/N), and uneven distribution in parameter space. These characteristics lead to unsatisfactory results on the spectra with low temperature, high temperature, or low metallicity. To this end, this paper proposes a stellar parameter estimation method based on multiple regions (SPEMR) that effectively improves parameter estimation accuracy. On the spectra with S/N ≥ 10, the precisions are 47 K, 0.08 dex, 0.03 dex, respectively, for the estimations of (Teff, $\log \, g$, and $\rm [Fe/H]$), 0.03–0.06 dex for elements C, Mg, Al, Si, Ca, Mn, and Ni, 0.07–0.13 dex for N, O, S, K, and Ti, while that of Cr is 0.16 dex. For the reference of astronomical science researchers and algorithm researchers, we released a catalogue for 4.19 million medium-resolution spectra from the LAMOST DR8, experimental code, trained model, training data, and test data.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
National Development and Reform Commission
Publisher
Oxford University Press (OUP)
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
2 articles.
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