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SPar: Estimating Stellar Parameters from Multiband Photometries with Empirical Stellar Libraries
Sun, Mingxu et al., 2023, The Astronomical Journal, 166, 126 | View on ADS (2023AJ....166..126S)
Abstract
Modern large-scale photometric surveys have provided us with multiband photometries of billions of stars. Determining the stellar atmospheric parameters, such as the effective temperature (T eff) and metallicities ([Fe/H]), absolute magnitudes (M G ), distances (d), and reddening values (E(G BP - G RP)) is fundamental to study the stellar populations, structure, kinematics, and chemistry of the Galaxy. This work constructed an empirical stellar library that maps the stellar parameters to multiband photometries from a data set with Gaia parallaxes, LAMOST atmospheric parameters, and optical to near-infrared photometry from several photometric surveys. Based on the stellar library, we developed a new algorithm, SPar (Stellar Parameters from multiband photometry), which fits the multiband stellar photometries to derive the stellar parameters (T eff, [Fe/H], M G , d, and E(G BP - G RP)) of the individual stars. The algorithm is applied to the multiband photometric measurements of a sample of stars selected from the SMSS survey, which have stellar parameters derived from the spectroscopic surveys. The stellar parameters derived from multiband photometries by our algorithm are in good agreement with those from the spectroscopic surveys. The typical differences between our results and the literature values are 170 K for T eff, 0.23 dex for [Fe/H], 0.13 mag for M G , and 0.05 mag for E(G BP - G RP). The algorithm proved to be robust and effective and will be applied to the data of future large-scale photometric surveys such as the Mephisto and CSST surveys.
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