Gaia Data Release 3: Stellar multiplicity, a teaser for the hidden treasure
Gaia Collaboration: F. Arenou, C. Babusiaux, M.A. Barstow, S. Faigler,, A. Jorissen, P. Kervella, T. Mazeh, N. Mowlavi, P. Panuzzo, J. Sahlmann, S., Shahaf, A. Sozzetti, N. Bauchet, Y. Damerdji, P. Gavras, P. Giacobbe, E., Gosset, J.-L. Halbwachs, B. Holl, M.G. Lattanzi

TL;DR
Gaia DR3 provides extensive data on stellar multiplicity, enabling detailed analysis of binary systems, discovery of new binaries, substellar companions, and exoplanets, significantly advancing our understanding of stellar and substellar populations.
Contribution
This paper showcases the first large-scale Gaia DR3 binary catalog, offering new insights into stellar multiplicity, substellar companions, and exoplanet detection with detailed orbital solutions and statistical analyses.
Findings
Catalog of 800,000 binary solutions and properties
Discovery of new EL CVn systems and candidate binaries
Constraints on substellar companion occurrence rates
Abstract
The Gaia DR3 Catalogue contains for the first time about eight hundred thousand solutions with either orbital elements or trend parameters for astrometric, spectroscopic and eclipsing binaries, and combinations of them. This paper aims to illustrate the huge potential of this large non-single star catalogue. Using the orbital solutions together with models of the binaries, a catalogue of tens of thousands of stellar masses, or lower limits, partly together with consistent flux ratios, has been built. Properties concerning the completeness of the binary catalogues are discussed, statistical features of the orbital elements are explained and a comparison with other catalogues is performed. Illustrative applications are proposed for binaries across the H-R diagram. The binarity is studied in the RGB/AGB and a search for genuine SB1 among long-period variables is performed. The discovery of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
