Application of probabilistic methods to Mount Wilson Ca H&K data confirms robustness of the inactive branch

The existence of "activity branches", that is stellar cycles clustering in groups that show linear dependencies as function of rotation, has been debated for years. Such dependencies have crucial implications on how to explain stellar magnetism in terms of dynamo theory. In this study we applied novel time series analysis techniques to one of the longest stellar activity database.

The existence of "activity branches", that is stellar cycles clustering in groups that show linear dependencies as function of rotation, has been debated for years. Such dependencies have crucial implications on how to explain stellar magnetism in terms of dynamo theory. In this study we applied novel time series analysis techniques (Olspert et al., 2018, A&A, 615, A111 for a Bayesian generalised Lomb-Scargle periodogram with trend) to one of the longest stellar activity database. We confirmed the clustering into inactive (solar-like) and active stars using a Gaussian mixture model. The inactive population exhibits a robust, positive slope in the activity diagram, while the previously claimed positive trend in the active population does not exist according to our analysis. Comparing to cycle data inferred for even more active stars (see the study of Lehtinen et al., 2016, A&A, 588, A38), the data is consistent with a negative trend that smoothly continues from active to super active stars. Hence, the positive slope for the inactive cluster, hosting the Sun itself, remains enigmatic for the prevailing solar dynamo paradigms, inexplicable by both the flux-transport concept and the classical turbulent dynamo mechanism.