Inferring the Solar Meridional Circulation Flow Profile by Applying Bayesian Methods to Time–Distance Helioseismology

Abstract Mapping the large-scale subsurface plasma flow profile within Sun has been attempted using various methods for several decades. One such in particular is meridional circulation, which numerous studies have published. However, often show disagreement structure. In an effort to constrain from data, a Bayesian Markov chain Monte Carlo framework developed take advantage of advances computing power that allow efficient exploration high-dimensional parameter spaces. This study utilizes helioseismic travel-time difference data covering span 21 years and parameterized model circulation find most likely profiles. Tests were carried out on artificial determine ability this method recover expected solar-like profiles, as well few extreme cases. We capable recovering input flows both single- double-cell structures. Some inversion results indicate potential differences between two solar cycles terms magnitude morphology, mid-convection zone. Of these, solutions cycle 23 large single-celled profile, while 24 shows weaker general hints toward double-celled