Stellar Atmospheric Parameters for Cool Dwarfs in Gaia Data Release 3

• Published in: The Astrophysical journal. Supplement series 2024-02, Vol.270 (2), p.32
• Main Authors: Qu, Cai-Xia, Luo, A-Li, Wang, Rui, Jones, Hugh R. A., Du, Bing, Chen, Xiang-Lei, Wang, You-Fen
• Format: Article
• Language: English
• Subjects: Atmospheric models; Galactic evolution; Late-type dwarf stars; M dwarf stars; Machine learning; Mathematical models; Parameters; Photometry; Sky surveys (astronomy); Stellar atmospheres
• ISSN: 0067-0049; 1538-4365
• DOI: 10.3847/1538-4365/ad103c

We provide a catalog of atmospheric parameters for 1,806,921 cool dwarfs from Gaia Data Release 3 (DR3) that lie within the range covered by LAMOST cool dwarf spectroscopic parameters: 3200 K < T eff < 4300 K, −0.8 < [M/H] < 0.2 dex, and 4.5 < log g < 5.5 dex. Our values are derived based on machine-learning models trained with multiband photometry corrected for dust. The photometric data comprise optical data from the Sloan Digital Sky Survey r , i , and z bands, near-infrared data from the Two Micron All Sky Survey J , H , and K bands, and mid-infrared data from the ALLWISE W1 and W2 bands. We used both random forest and light gradient boosting machine machine-learning models and found similar results from both, with an error dispersion of 68 K, 0.22 dex, and 0.05 dex for T eff , [M/H], and log g , respectively. Assessment of the relative feature importance of different photometric colors indicated W1 − W2 as most sensitive to both T eff and log g , with J − H being most sensitive to [M/H]. We find that our values show a good agreement with the Apache Point Observatory Galactic Evolution Experiment, but are significantly different to those provided as part of Gaia DR3.