TY - JOUR
T1 - Stellar Atmospheric Parameters for Cool Dwarfs in Gaia Data Release 3
AU - Qu, Cai-Xia
AU - Luo, A-Li
AU - Wang, Rui
AU - Jones, Hugh R. A.
AU - Du, Bing
AU - Chen, Xiang-Lei
AU - Wang, You-Fen
N1 - This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/
PY - 2024/2/1
Y1 - 2024/2/1
N2 - 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.
AB - 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.
KW - astro-ph.SR
KW - astro-ph.EP
KW - astro-ph.GA
UR - http://www.scopus.com/inward/record.url?scp=85183995265&partnerID=8YFLogxK
U2 - 10.3847/1538-4365/ad103c
DO - 10.3847/1538-4365/ad103c
M3 - Article
SN - 0067-0049
VL - 270
SP - 1
EP - 11
JO - Astrophysical Journal, Supplement Series
JF - Astrophysical Journal, Supplement Series
IS - 2
M1 - 32
ER -