Asteroseismic potential of CHEOPS

A. Moya, S. Barceló Forteza, A. Bonfanti, S. J. A. J. Salmon, V. Van Grootel and D. Barrado. 2018. Asteroseismic potential of CHEOPS. Astronomy and Astrophysics 620

Asteroseismology has been impressively boosted during the last decade mainly thanks to space missions such as Kepler/K2 and CoRoT. This has a large impact, in particular, in exoplanetary sciences since the accurate characterization of the exoplanets is convoluted in most cases with the characterization of their hosting star. In the decade before the expected launch of the ESA mission PLATO 2.0, only two important missions will provide short-cadence high-precision photometric time-series: NASA-TESS and ESA-CHEOPS missions, both having high capabilities for exoplanetary sciences.

Aims. In this work we want to explore the asteroseismic potential of CHEOPS time-series.

Methods. Following the works estimating the asteroseismic potential of Kepler and TESS, we have analysed the probability of detecting solar-like pulsations using CHEOPS light-curves. Since CHEOPS will collect runs with observational times from hours up to a few days, we have analysed the accuracy and precision we can obtain for the estimation of nu(max). This is the only asteroseismic observable we can recover using CHEOPS observations. Finally, we have analysed the impact of knowing nu(max) in the characterization of exoplanet host stars.

Results. Using CHEOPS light-curves with the expected observational times we can determine nu(max) for massive G and F-type stars from late main sequence (MS) on, and for F, G, and K-type stars from post-main sequence on with an uncertainty lower than a 5%. For magnitudes V < 12 and observational times from eight hours up to two days, the HR zone of potential detectability changes. The determination of nu(max) leads to an internal age uncertainty reduction in the characterization of exoplanet host stars from 52% to 38%; mass uncertainty reduction from 2.1% to 1.8%; radius uncertainty reduction from 1.8% to 1.6%; density uncertainty reduction from 5.6% to 4.7%, in our best scenarios.

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