Identification, mass and age of primary red clump stars from spectral features derived with the LAMOST DR7 (2202.09185v2)

Abstract: Although red clump (RC) stars are easy to identify due to their stability of luminosity and color, about 20-50% are actually red giant branch (RGB) stars in the same location on the HR diagram. In this paper, a sample of 210,504 spectra for 184 318 primary RC (PRC) stars from the LAMOST DR7 is identified, which has a purity of higher than 90 percent. The RC and the RGB stars are successfully distinguished through LAMOST spectra(R~1800 and SNR>10) by adopting the XGBoost ensemble learning algorithm, and the secondary RC stars are also removed. The SHapley Additive exPlanations (SHAP) value is used to explain the top features that the XGBoost model selected. The features are around Fe5270, MgH & MgIb, Fe4957, Fe4207, Cr5208, and CN, which can successfully distinguish RGB and RC stars. The XGBoost is also used to estimate the ages and masses of PRC stars by training their spectra with Kepler labeled asteroseismic parameters. The uncertainties of mass and age are 13 and 31 percent, respectively. Verifying the feature attribution model, we find the age-sensitive elements XGBoost gets are consistent with the literature. Distances of the PRC stars are derived by $K_{S}$ absolute magnitude calibrated by Gaia EDR3, which has an uncertainty of about 6 percent and shows the stars mainly locate at the Galactic disk. We also test the XGBoost with R$\sim$250, which is the resolution of the Chinese Space Station Telescope(CSST) under construction, it is still capable of finding sensitive features to distinguish RC and RGB.