Bayesian analysis of Gaia epoch astrometry and radial velocities with kima

Abstract

The forthcoming data release from the Gaia space telescope expected to yield tens of thousands of newly detected exoplanets, as well as detection and 3D orbital constraints on binary stars and black holes. Many of these systems will warrant in-depth analyses of the astrometric data and radial velocity follow-up. This will require dedicated tools to exploit this wealth of data. We provide open-source software to analyse epoch astrometric data from Gaia, both independently and jointly with radial velocities. We add two models to the open-source orbit-fitting codebase įma and test these on both real and simulated data. This code uses diffusive nested sampling to explore the parameter space, calculate evidence for model comparison, and perform parameter estimation. We show that the results are consistent with published and expected values, validating the use of įma for the analysis of Gaia data. We explore various attributes of įma's Gaia model, including its potential to distinguish genuine orbital signals from scan-angle-dependent signals. s are thousands to