Predictions of planet detections with near infrared radial velocities in the up-coming SPIRou Legacy Survey-Planet Search

Abstract

The SPIRou near infrared spectro-polarimeter is destined to begin science operations at the Canada-France-Hawaii Telescope in mid-2018. One of the instrument's primary science goals is to discover the closest exoplanets to the Solar System by conducting a 3-5 year long radial velocity survey of nearby M dwarfs at an expected precision of $\sim 1$ m s${}^{-1}$; the SPIRou Legacy Survey-Planet Search (SLS-PS). In this study we conduct a detailed Monte-Carlo simulation of the SLS-PS using our current understanding of the occurrence rate of M dwarf planetary systems and physical models of stellar activity. From simultaneous modelling of planetary signals and activity, we predict the population of planets detected in the SLS-PS. With our fiducial survey strategy and expected instrument performance over a nominal survey length of $\sim 3$ years, we expect SPIRou to detect $85.3_{-12.4}^{+29.3}$ planets including $20.0_{-7.2}^{+16.8}$ habitable zone planets and $8.1_{-3.2}^{+7.6}$ Earth-like planets from a sample of 100 M1-M8.5 dwarfs out to 11 pc. By studying mid-to-late M dwarfs previously inaccessible to existing optical velocimeters, SPIRou will put meaningful constraints on the occurrence rate of planets around those stars including the value of ${\eta }_{\oplus }$ at an expected level of precision of $\lesssim 45$%. We also predict a subset of $46.7_{-6.0}^{+16.0}$ planets may be accessible with dedicated high-contrast imagers on the next generation of ELTs including $4.9_{-2.0}^{+4.7}$ potentially imagable Earth-like planets. Lastly, we compare the results of our fiducial survey strategy to other foreseeable survey versions to quantify which strategy is optimized to reach the SLS-PS science goals. The results of our simulations are made available to the community on github.

Accepted for publication in AJ. 19 figures including 15 interactive figures when viewed in Adobe Acrobat. Simulation results provided at https://github.com/r-cloutier/SLSPS_Simulations

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