Quasi-periodic Gaussian processes for stellar activity: From physical to kernel parameters

ABSTRACT In recent years, Gaussian Process (GP) regression has become widely used to analyse stellar and exoplanet time-series data sets. For spotted stars, the most popular GP covariance function is quasi-periodic (QP) kernel, whose hyperparameters of have a plausible interpretation in terms physical properties star spots. this paper, we test reliability by modelling simulated using spot model QP GP, recently proposed plus cosine (QPC) comparing posterior distributions input parameters model. We find excellent agreement between rotation period QPC period, very good decay time-scale length scale squared exponential term. also compare derived from light radial velocity (RV) curves for given star, finding that evolution time-scales are agreement. However, harmonic complexity while displaying no clear correlation with our simulations, systematically higher RV than light-curve data. Finally, investigate impact noise time-sampling on case RVs. Our results indicate coverage more important total number points, characteristics govern complexity.