摘要：The reloaded Rossiter–McLaughlin method allows us to probe variations in the stellar surface by resolving spectra from the regions that are occulted by a planet as it transits. The goal of this paper is to investigate the optimal parameters space for using this technique to detect differential rotation (DR) and centre-to-limb convective variations. We simulated a star–planet system with and without convective effects to map the optimal regions of the parameter space for retrieving the injected differential rotation. Our simulations explored all possible ranges of projected obliquity (spin-orbit angle), stellar inclination, and impact parameter, as well as differences in instrumental configuration, stellar magnitude, and exposure time. We find that DR is more easily retrieved at low-impact parameters, corresponding to system configurations in which the transiting planet crosses the largest number of stellar latitudes. The main hot-spots for detection (i.e. areas in which DR detectability is high) are 120◦ < |λ| < 180◦ for i∗ < 90◦ and |λ| < 60◦ for i∗ > 90◦ on average, and they tend to shrink as the impact parameter increases. Additionally, in contrast to the crucial impact of brightness, we identify that exposure time has a negligible impact on the difficulty of detecting DR as the increase in signal-to-noise ratio (S/N) at longer exposure times is counteracted by the degraded sampling rate. We determine that an ESPRESSO-like setup of instrumental configuration and sensitivity might retrieve DR up to V = 12, compared to V = 10 for HARPS. We reach no clear conclusion about limb-dependent convective effects and the possible confusion with DR; preliminary results suggest, however, that under certain circumstances, while it seems that one effect could be mistaken for the other, the accuracy of the fit (in particular of α) does not hold up under additional scrutiny.
关键词：convection;methods: data analysis;planets and satellites: dynamical evolution and stability;stars: rotation;techniques: radial velocities;techniques: spectroscopic
