Identifiability of Rotating Stellar Surfaces from Astrometric Jitter

Abstract

Astrometry measures shifts in a star's photocentre and can be used to detect reflex motion due to orbiting exoplanets. Brightness asymmetries (e.g. starspots) rotating in and out of view can also cause apparent motion of the photocenter, termed astrometric jitter, that has previously been considered a source of noise. Here, we explore whether it can be used to map stellar surfaces. We derive a Cramer-Rao bound on the minimum variance for which a stellar surface can theoretically be estimated, quantifying the information content in rotational astrometric jitter. To regularize and break singularities in the Fisher information, we impose a spatial-smoothness Gaussian-Markov random field prior. A key challenge in mapping surfaces arises for stars with unknown rotational axis inclinations, requiring joint estimation of the inclination and the stellar surface. We characterize the coupling between them and quantify the precision gain when inclination is known versus unknown.