Vorträge, Seminare, Ereignisse

Abstract
The CARMENES radial-velocity (RV) survey of 365 M dwarfs to search for exoplanet has been in operation for more than five years at the 3.5 m telescope on Calar Alto, Spain. In the first part of the talk, I will give a short overview of results in which I was involved during my Ph.D. studies and that were possible thanks to CARMENES. The RV measurements of M-dwarf stars, which rank among the most active stars in the Universe, typically contain signals related to the star's rotational activity. Stellar astrophysical noise and aliasing caused by data sampling are significant obstacles that needed to be overcome for many investigated systems in the CARMENES survey. Therefore, in the second part of the talk, I will focus on a handful of such systems. I will demonstrate that it is possible to detect and model planetary RV signals at the limit of the stellar astrophysical noise by applying rigorous statistical models, along with prior information from auxiliary data and further simulations. I will also give more details regarding the disentanglement of stellar activity and planetary signals and our approach to model them by applying a Bayesian framework and Gaussian process (GP) regression models. Despite their advantages, GP models are still very controversial in the RV community due to their intrinsic flexibility and intransparency which brings the risk to come to wrong conclusions when incorporating a GP into the modeling. As part of my Ph.D. thesis, I have investigated the properties and the performance of GP models based on numerical simulations of simulated RV data of active M dwarfs. I will present some key outcomes from these simulations as well as some guidelines, tips and tricks on how to robustly use GP models for RV and photometric time series data. My goal is to convince you that while GP models can be risky if not applied correctly (as with many other types of models), they can be extremely helpful, even necessary, in many situations leading to the fact that not accounting for the correlated noise caused by the stellar activity of the star, for example by applying a GP model, might lead to wrong conclusions about the planets in the system.

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