Bayesian analysis of Gaia epoch astrometry and radial velocities with kima

Context. The next data release from the Gaia space telescope is expected to result in tens of thousands of newly detected exoplanets, as well as detection and 3D orbital constraints on binary stars and even black holes. Many of these will warrant in-depth analyses of the astrometric data, as well as radial velocity follow-up. This will require dedicated tools to exploit this wealth of data. Aims. We provide open-source software to analyse epoch astrometric data from Gaia, both alone and simultaneously with radial velocities. Methods. We add two models to the open-source orbit-fitting codebase kima, and test these on both real an simulated data. This code uses diffusive nested sampling to explore the parameter space, calculate evidences for model comparison, and perform parameter estimation. Results. We show that the results obtained are consistent with published/expected values, validating the use of kima for analysis of Gaia data. We explore various attributes of kima's Gaia model including using it to potentially distinguish true orbits from scan-angle dependent signals.