# Double-blind test program for astrometric planet detection with Gaia - Astrophysics

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Abstract: We use detailed simulations of the Gaia observations of synthetic planetarysystems and develop and utilize independent software codes in double-blind modeto analyze the data, including statistical tools for planet detection anddifferent algorithms for single and multiple Keplerian orbit fitting that useno a priori knowledge of the true orbital parameters of the systems. 1 Planetswith astrometric signatures $\alpha\simeq 3$ times the single-measurement error$\sigma \psi$ and period $P\leq 5$ yr can be detected reliably, with a verysmall number of false positives. 2 At twice the detection limit, uncertaintiesin orbital parameters and masses are typically $15%-20%$. 3 Over 70% oftwo-planet systems with well-separated periods in the range $0.2\leq P\leq 9$yr, $2\leq\alpha-\sigma \psi\leq 50$, and eccentricity $e\leq 0.6$ arecorrectly identified. 4 Favorable orbital configurations have orbital elementsmeasured to better than 10% accuracy $> 90%$ of the time, and the value of themutual inclination angle determined with uncertainties $\leq 10^{\degr}$. 5Finally, uncertainties obtained from the fitting procedures are a good estimateof the actual errors. Extrapolating from the present-day statistical propertiesof the exoplanet sample, the results imply that a Gaia with $\sigma \psi$ = 8$\mu$as, in its unbiased and complete magnitude-limited census of planetarysystems, will measure several thousand giant planets out to 3-4 AUs from starswithin 200 pc, and will characterize hundreds of multiple-planet systems,including meaningful coplanarity tests. Finally, we put Gaia into context,identifying several areas of planetary-system science in which Gaia can beexpected to have a relevant impact, when combined with data coming from otherongoing and future planet search programs.

Autor: S. Casertano 1, M.G. Lattanzi 2, A. Sozzetti 2,3, A. Spagna 2, S. Jancart 4, R. Morbidelli 2, R. Pannunzio 2, D. Pourbaix 4, D. Q

Fuente: https://arxiv.org/