Gaia Data Release 3: Apsis. II. Stellar parameters

Context. The third Gaia data release (Gaia DR3) contains, beyond the astrometry and photometry, dispersed light for hundreds of millions of sources from the Gaia prism spectra (BP and RP) and the spectrograph (RVS). This data release opens a new window on the chemo-dynamical properties of stars in our Galaxy, essential knowledge for understanding the structure, formation, and evolution of the Milky Way. Aims. To provide insight into the physical properties of Milky Way stars, we used these data to produce a uniformly derived all-sky catalogue of stellar astrophysical parameters: atmospheric properties (Teff, log g, [M/H], [α/Fe], activity index, emission lines, and rotation), 13 chemical abundance estimates, evolution characteristics (radius, age, mass, and bolometric luminosity), distance, and dust extinction. Methods. We developed the astrophysical parameter inference system (Apsis) pipeline to infer astrophysical parameters of Gaia objects by analysing their astrometry, photometry, BP/RP, and RVS spectra. We validate our results against those from other works in the literature, including benchmark stars, interferometry, and asteroseismology. Here we assess the stellar analysis performance from Apsis statistically. Results. We describe the quantities we obtained, including the underlying assumptions and the limitations of our results. We provide guidance and identify regimes in which our parameters should and should not be used. Conclusions. Despite some limitations, this is the most extensive catalogue of uniformly inferred stellar parameters to date. They comprise Teff, log g, and [M/H] (470 million using BP/RP, 6 million using RVS), radius (470 million), mass (140 million), age (120 million), chemical abundances (5 million), diffuse interstellar band analysis (half a million), activity indices (2 million), Hα equivalent widths (200 million), and further classifications of spectral types (220 million) and emission-line stars (50 thousand). More precise and detailed astrophysical parameters based on epoch BP, RP, and RVS spectrophotometry are planned for the next Gaia data release.We would like to thank the anonymous referee for the review of the manuscript and Carme Jordi for the very constructive feedback during the internal review of the manuscript. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular, the institutions participating in the Gaia Multilateral Agreement. This research has used NASA’s Astrophysics Data System, the VizieR catalogue access tool (CDS, Strasbourg, France). This publication made extensive use of the online authoring Overleaf platform (https://www.overleaf.com/). The data processing and analysis made use of matplotlib (Hunter 2007), NumPy (Harris et al. 2020), the IPython package (Pérez & Granger 2007), Vaex (Breddels & Veljanoski 2018), TOPCAT (Taylor 2005), pyphot (http://github.com/mfouesneau/pyphot), QuantStack xtensor (http://xtensor.readthedocs.io/) and R (R Core Team 2013). Part of the calculations have been performed with the high-performance computing facility SIGAMM, hosted by the Observatoire de la Côte d’Azur. C.B.J., R.A., M.F., and J.R. acknowledge the support from the DLR (German space agency) via grants 50QG0602, 50QG1001, 50QG1403, and 50QG2102. A.B., A.R.B., A.C., G.C., G.K., Pd.L., C.O., P.A.P., M.S., and F.T. acknowledge financial supports from the french space agency (CNES), Agence National de la Recherche (ANR 14-CE33-014-01) and Programmes Nationaux de Physique Stellaire & Cosmologie et Galaxies (PNPS & PNCG) of CNRS/INSU. A.G., A.K., B.E., J.S. and U.H. acknowledge financial supports from the Swedish National Space Agency (SNSA). L.S. acknowledges financial support by the Spanish Ministerio de Ciencia e Innovación through grant PID2020-112949GB-I00. Y.F. and A.L. acknowledge the BELgian federal Science Policy Office (BELSPO) through various PROgramme de Développement d’Expériences scientifiques (PRODEX) grants