Bayesian Detection and Parameter Recovery of Exoplanets with Gaia: Insights from 5- and 10-Year Mission Simulations

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Ranalli, Hobbs, and Lindegren show that a Bayesian, MCMC-based approach can detect and measure single-planet exoplanets from Gaia data by simulating observations across different signal strengths and orbital shapes, evaluating false positives with information criteria, and finding that a 5- to 10-year mission yields about 50% detection at modest signal-to-noise with good recovery of orbital periods (about 4–5% error for 5 years and ~3% for 10 years), semi-major axes (roughly 6–7%), and eccentricities (around 0.06–0.07), while extending mission length slightly raises some false positives under certain criteria and enabling a larger exoplanet census and better orbital properties.

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Astrometry and exoplanets in the Gaia era: a Bayesian approach to detection and parameter recovery

The Gaia mission is expected to make a significant contribution to the knowledge of exoplanet systems, both in terms of their number and of their physical properties. We develop Bayesian methods and detection criteria for orbital fitting, and revise the detectability of exoplanets in light of the in-flight properties of Gaia. Limiting ourselves to one-planet systems as a first step of the development, we simulate Gaia data for exoplanet systems over a grid of S/N, orbital period, and eccentricity. The simulations are then fit using Markov chain Monte Carlo methods. We investigate the detection rate according to three information criteria and the ∆χSUP2/SUP. For the ∆χSUP2/SUP, the effective number of degrees of freedom depends on the mission length. We find that the choice of the Markov chain starting point can affect the quality of the results; we therefore consider two limit possibilities: an ideal case, and a very simple method that finds the starting point assuming circular orbits. We use 6644 and 4402 simulations to assess the fraction of false positive detections in a 5 yr and in a 10 yr mission, respectively; and 4968 and 4706 simulations to assess the detection rate and how the parameters are recovered. Using Jeffreys scale of evidence, the fraction of false positives passing a strong evidence criterion is ≲0.2% (0.6%) when considering a 5 yr (10 yr) mission and using the Akaike information criterion or the Watanabe-Akaike information criterion, and <0.02% (<0.06%) when using the Bayesian information criterion. We find that there is a 50% chance of detecting a planet with a minimum S/N = 2.3 (1.7). This sets the maximum distance to which a planet is detectable to 70 pc and 3.5 pc for a Jupiter-mass and Neptune-mass planets, respectively, assuming a 10 yr mission, a 4 au semi-major axis, and a 1 MSUB☉/SUB star. We show the distribution of the accuracy and precision with which orbital parameters are recovered. The period is the orbital parameter that can be determined with the best accuracy, with a median relative difference between input and output periods of 4.2% (2.9%) assuming a 5 yr (10 yr) mission. The median accuracy of the semi-major axis of the orbit can be recovered with a median relative error of 7% (6%). The eccentricity can also be recovered with a median absolute accuracy of 0.07 (0.06).