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Gaia Data Release 3 : A golden sample of astrophysical parameters
- Publication Year :
- 2023
-
Abstract
- Context: Gaia Data Release 3 (DR3) provides a wealth of new data products for the astronomical community to exploit, including astrophysical parameters for half a billion stars. In this work, we demonstrate the high quality of these data products and illustrate their use in di fferent astrophysical contexts. Aims: We produce homogeneous samples of stars with high-quality astrophysical parameters by exploiting Gaia DR3, while focusing on many regimes across the Hertzsprung-Russell (HR) diagram; spectral types OBA, FGKM, and ultracool dwarfs (UCDs). We also focus on specific subsamples of particular interest to the community: solar analogues, carbon stars, and the Gaia spectrophotometric standard stars (SPSS). Methods: We query the astrophysical parameter tables along with other tables in Gaia DR3 to derive the samples of the stars of interest. We validate our results using the Gaia catalogue itself and by comparison with external data. Results: We produced six homogeneous samples of stars with high-quality astrophysical parameters across the HR diagram for the community to exploit. We first focus on three samples that span a large parameter space: young massive disc stars (OBA; about 3 Million), FGKM spectral type stars (about 3 Million), and UCDs (about 20 000). We provide these sources along with additional information (either a flag or complementary parameters) as tables that are made available in the Gaia archive. We also identify 15 740 bone fide carbon stars and 5863 solar analogues, and provide the first homogeneous set of stellar parameters of the SPSS sample. We demonstrate some applications of these samples in di fferent astrophysical contexts. We use a subset of the OBA sample to illustrate its usefulness in analysing the Milky Way rotation curve. We then use the properties of the FGKM stars to analyse known exoplanet systems. We also analyse the ages of some unseen UCD-companions to the FGKM stars. We additionally predict the colours of the Sun in various<br />For complete list of authors see http://dx.doi.org/10.1051/0004-6361/202243800
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1399994531
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1051.0004-6361.202243800