Astrophysical parameters from Gaia DR2, 2MASS, and AllWISE

Context. Physical and dynamical stellar properties are essential knowledge for understanding the structure, formation, and evolution of our Galaxy. Aims. We produced a uniformly derived all-sky catalog of stellar astrophysical parameters (APs; age, mass, temperature, bolometric luminosity, distance, and dust extinction) to provide insight into the physical properties of Milky Way stars. Methods. Exploiting the power of multiwavelength and multi-survey observations from Gaia DR2 parallaxes and integrated photometry along with 2MASS and AllWISE photometry, we introduce a uniformly derived all-sky catalog of stellar APs, including dust extinction (A(0)) average grain size (R-0) along the line of sight, for 123 076 271 stars. In contrast with previous works, we do not use a Galactic model as a prior in our analysis. Results. We validate our results against other work in the literature (e.g., benchmark stars, interferometry, Bayestar, and StarHorse). The limited optical information in the Gaia photometric bands or the lack of ultraviolet or spectroscopic information renders the chemistry inference prior-dominated. We demonstrate that Gaia parallaxes bring sufficient leverage to explore the detailed structures of the interstellar medium in our Milky Way. Conclusions. In Gaia DR3, we will obtain the dispersed optical light information that will help us break through some limitations of this analysis, allowing us to infer stellar chemistry in particular. Gaia promises us data that we can use to construct the most detailed view of the chemo-dynamics of field star populations in our Galaxy.

Automated summary

This paper introduces a uniformly derived all-sky catalog of stellar astrophysical parameters, providing insights into the physical properties of Milky Way stars. It validates the results by comparing with other work and highlights the usefulness of Gaia parallaxes in exploring the detailed structures of the interstellar medium in our Galaxy. It also discusses the potential of using Gaia DR3 data to break through limitations and infer stellar chemistry.