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This paper presents a rigorous mathematical framework for the limits of stochastic semigroups defined by Gibbs distributions, establishing a new form of "Block-Triangular majorisation" that interpolates between standard and unordered majorisation. While the work is deeply theoretical within probability and mathematical physics, it offers foundational insights relevant to quantum information theory, particularly regarding the behavior of Rényi entropies in high-temperature limits and the structural properties of invariant distributions.
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Limits of Stochastic Semigroups and Block-Triangular Majorisation

arXiv2 min read

arXiv:2609.04057v1 Announce Type: cross Abstract: We investigate limits of semigroups of stochastic matrices defined by their invariant distribution. Given probability vectors $\gamma(\beta)$ depending on a parameter $\beta$, we introduce a notion of convergence as $\beta\to\infty$ for the corresponding semigroups of $\gamma(\beta)$-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 $\beta$. 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 R\'enyi $\alpha$-entropies as $\beta\to\infty$.

Abstract:We investigate limits of semigroups of stochastic matrices defined by their invariant distribution. Given probability vectors $\gamma(\beta)$ depending on a parameter $\beta$, we introduce a notion of convergence as $\beta\to\infty$ for the corresponding semigroups of $\gamma(\beta)$-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 $\beta$. 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 $\alpha$-entropies as $\beta\to\infty$.

21 pages, 3 figure; Comments welcome!

Mathematical Physics (math-ph); Combinatorics (math.CO); Probability (math.PR); Quantum Physics (quant-ph)

arXiv:2609.04057 [math-ph]

(or arXiv:2609.04057v1 [math-ph] for this version)

https://doi.org/10.48550/arXiv.2609.04057 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 278 words

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