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Accurate determination of stellar atmospheric parameters and elementalabundances is crucial for Galactic archeology via large-scale spectroscopicsurveys. In this paper, we estimate stellar atmospheric parameters -- effectivetemperature T_{\rm eff}, surface gravity log g and metallicity [Fe/H], absolutemagnitudes M_V and M_{Ks}, {\alpha}-element to metal (and iron) abundance ratio[{\alpha}/M] (and [{\alpha}/Fe]), as well as carbon and nitrogen abundances[C/H] and [N/H] from the LAMOST spectra with amultivariate regressionmethodbased on kernel-based principal component analysis, using stars in common withother surveys (Hipparcos, Kepler, APOGEE) as training data sets. Both internaland external examinations indicate that given a spectral signal-to-noise ratio(SNR) better than 50, our method is capable of delivering stellar parameterswith a precision of ~100K for Teff, ~0.1 dex for log g, 0.3 -- 0.4mag for M_Vand M_{Ks}, 0.1 dex for [Fe/H], [C/H] and [N/H], and better than 0.05 dex for[{\alpha}/M] ([{\alpha}/Fe]). The results are satisfactory even for a spectralSNR of 20. The work presents first determinations of [C/H] and [N/H] abundancesfrom a vast data set of LAMOST, and, to our knowledge, the first reportedimplementation of absolute magnitude estimation directly based on the observedspectra. The derived stellar parameters for millions of stars from the LAMOSTsurveys will be publicly available in the form of value-added catalogues.

monthly notices of the royal astronomical society

Estimating stellar atmospheric parameters, absolute magnitudes and  elemental abundances from the LAMOST spectra with Kernel-based Principal  Component Analysis