{
  "id": "2311.08944",
  "version": "v1",
  "published": "2023-11-15T13:29:05.000Z",
  "updated": "2023-11-15T13:29:05.000Z",
  "title": "Stellar Atmospheric Parameters for Cool Dwarfs in Gaia DR3",
  "authors": [
    "Cai-Xia Qu",
    "A-Li Luo",
    "Rui Wang",
    "Hugh R. A. Jones",
    "Bing Du",
    "Xiang-Lei Chen",
    "You-Fen Wang"
  ],
  "comment": "14 pages, 12 figures, accepted by ApJS",
  "categories": [
    "astro-ph.SR",
    "astro-ph.EP",
    "astro-ph.GA"
  ],
  "abstract": "We provide a catalogue of atmospheric parameters for 1,806,921 cool dwarfs from Gaia DR3 which 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 multi-band photometry corrected for dust. The photometric data comprises of optical from SDSS r, i, z bands, near-infrared from 2MASS J, H, K and mid-infrared from ALLWISE W1, W2. We used both random forest and LightGBM 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 most sensitive to [M/H]. We find that our values show a good agreement with APOGEE, but are significantly different to those provided as part of Gaia DR3.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2023-11-15T13:29:05.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "stellar atmospheric parameters",
      "gaia dr3",
      "machine learning models",
      "lamost cool dwarf spectroscopic parameters",
      "photometric data comprises"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 14,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}