Limits of Stochastic Semigroups and Block-Triangular Majorisation

Abstract: We investigate limits of semigroups of stochastic matrices defined by their invariant distribution. Given probability vectors $γ(β)$ depending on a parameter $β$, we introduce a notion of convergence as $β\to\infty$ for the corresponding semigroups of $γ(β)$-preserving stochastic matrices and investigate the structure of the resulting limit. In general, the limiting semigroup differs from the semigroup preserving the limiting distribution, showing that these two operations do not commute. We develop a general framework for such limiting semigroups and study in detail the case in which the invariant distributions are Gibbs vectors at the inverse temperature $β$. We show that the limiting semigroup consists of block-upper-triangular stochastic matrices subject to additional substochasticity constraints. We characterise and enumerate their extremal elements and determine the preorder on probability vectors induced by the action of the semigroup. The resulting notion of Block-Triangular majorisation interpolates between ordinary majorisation and upper triangular (aka unordered) majorisation. We show that it is completely characterised by a finite family of monotones and analyse the corresponding behaviour of Rényi $α$-entropies as $β\to\infty$.