Gaia DR3 astrometric orbit determination with Markov Chain Monte Carlo and Genetic Algorithms. Systems with stellar, substellar, and planetary mass companions

Astrometric discovery of sub-stellar mass companions orbiting stars is exceedingly hard due to the required sub-milliarcsecond precision, limiting the application of this technique to only a few instruments on a target-per-target basis as well as the global astrometry space missions Hipparcos and Gaia. The third Gaia data release includes the first Gaia astrometric orbital solutions, whose sensitivity in terms of estimated companion mass extends down into the planetary-mass regime. We present the contribution of the `exoplanet pipeline' to the Gaia DR3 sample of astrometric orbital solutions by describing the methods used for fitting the orbits, the identification of significant solutions, and their validation. We then present an overview of the statistical properties of the solution parameters. Using both a Markov Chain Monte Carlo and Genetic Algorithm we fit the 34 months of Gaia DR3 astrometric time series with a single Keplerian astrometric-orbit model. Verification and validation steps are taken using significance tests, internal consistency checks using the Gaia radial velocity measurements (when available), as well as literature radial velocity and astrometric data, leading to a subset of candidates that are labelled as 'validated'. We determined astrometric-orbit solutions for 1162 sources and 198 solutions have been assigned the 'validated' label. Precise companion mass estimates are presented elsewhere. From internal and external verification and validation we estimate the level of spurious/incorrect solutions in our sample to be of the order of ~5-10% in our non-'validated' candidate samples. We demonstrate that Gaia is able to confirm and sometimes refine known orbital companion orbits as well as identify new candidates, providing us with a positive outlook of the expected harvest from the full mission data in future data releases.