  Convergence of the Bayes posterior measure is considered in canonical
statistical settings where observations sit on a geometrical object such as a
compact manifold, or more generally on a compact metric space verifying some
conditions. A natural geometric prior based on randomly rescaled solutions of
the heat equation is considered. Upper and lower bound posterior contraction
rates are derived.
