Examining the orbital decay targets KELT-9 b, KELT-16 b, and WASP-4b, and the transit-timing variations of HD 97658 b

Abstract

Context Tidal orbital decay is suspected to occur for hot Jupiters in particular, with the only observationally confirmed case of this being WASP-12b. By examining this effect, information on the properties of the host star can be obtained using the so-called stellar modified tidal quality factor Q*′, which describes the efficiency with which the kinetic energy of the planet is dissipated within the star. This can provide information about the interior of the star. Aims In this study, we aim to improve constraints on the tidal decay of the KELT-9, KELT-16, and WASP-4 systems in order to find evidence for or against the presence of tidal orbital decay. With this, we want to constrain the Q*′ value for each star. In addition, we aim to test the existence of the transit timing variations (TTVs) in the HD 97658 system, which previously favoured a quadratic trend with increasing orbital period. Methods Making use of newly acquired photometric observations from CHEOPS (CHaracterising ExOplanet Satellite) and TESS (Transiting Exoplanet Survey Satellite), combined with archival transit and occultation data, we use Markov chain Monte Carlo (MCMC) algorithms to fit three models to the data, namely a constant-period model, an orbital-decay model, and an apsidal-precession model. Results We find that the KELT-9 system is best described by an apsidal-precession model for now, with an orbital decay trend at over 2 σ being a possible solution as well. A Keplerian orbit model with a constant orbital period provides the best fit to the transit timings of KELT-16 b because of the scatter and scale of their error bars. The WASP-4 system is best represented by an orbital decay model at a 5 σ significance, although apsidal precession cannot be ruled out with the present data. For HD 97658 b, using recently acquired transit observations, we find no conclusive evidence for a previously suspected strong quadratic trend in the data.