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A divide-and-conquer approach to analyzing Markov chains (MCs) is not utilized as widely as it could be, despite its potential benefits. One primary reason for this is the fact that most MC decomposition approaches involve a complex and…

Probability · Mathematics 2021-02-25 Katsunobu Sasanuma , Robert Hampshire , Alan Scheller-Wolf

This paper presents an elementary proof of stochastic stability of a discrete-time reversible Markov chain starting from a Foster-Lyapunov drift condition. Besides its relative simplicity, there are two salient features of the proof: (i) it…

Probability · Mathematics 2020-05-19 Amirhossein Taghvaei , Prashant G. Mehta

We study fixed-policy evaluation for finite Markov chains that may be reducible and periodic. Classical evaluation methods with gain and bias decomposition are not always diagnostic: the gain records only invariant Ces\`aro averages, while…

Machine Learning · Statistics 2026-05-11 Yang Xu , Vaneet Aggarwal

The main purpose of this article is to establish moderate deviation principles for additive functionals of bifurcating Markov chains. Bifurcating Markov chains are a class of processes which are indexed by a regular binary tree. They can be…

Probability · Mathematics 2021-05-21 S. Valère Bitseki Penda , Gorgui Gackou

Perturbation analysis of Markov chains provides bounds on the effect that a change in a Markov transition matrix has on the corresponding stationary distribution. This paper compares and analyzes bounds found in the literature for finite…

Probability · Mathematics 2024-04-03 Karim Abbas , Joost Berkhout , Bernd Heidergott

We study the limit behaviour of upper and lower bounds on expected time averages in imprecise Markov chains; a generalised type of Markov chain where the local dynamics, traditionally characterised by transition probabilities, are now…

Probability · Mathematics 2020-03-27 Natan T'Joens , Jasper De Bock

We establish universal modified log-Sobolev inequalities for reversible Markov chains on the boolean lattice $\{0,1\}^n$, under the only assumption that the invariant law $\pi$ satisfies a form of negative dependence known as the stochastic…

Probability · Mathematics 2020-02-28 Jonathan Hermon , Justin Salez

We study the large deviations of Markov chains under the sole assumption that the state space is discrete. In particular, we do not require any of the usual irreducibility and exponential tightness assumptions. Using subadditive arguments,…

Probability · Mathematics 2026-05-15 Léo Daures

The core of generalization theory was developed for independent observations. Some PAC and PAC-Bayes bounds are available for data that exhibit a temporal dependence. However, there are constants in these bounds that depend on properties of…

Machine Learning · Statistics 2026-03-12 Vahe Karagulyan , Pierre Alquier

We study the convergence of states under continuous-time depolarizing channels with full rank fixed points in terms of the relative entropy. The optimal exponent of an upper bound on the relative entropy in this case is given by the…

Quantum Physics · Physics 2017-12-06 Alexander Müller-Hermes , Daniel Stilck Franca , Michael M. Wolf

Rowmotion is a certain well-studied bijective operator on the distributive lattice $J(P)$ of order ideals of a finite poset $P$. We introduce the rowmotion Markov chain ${\bf M}_{J(P)}$ by assigning a probability $p_x$ to each $x\in P$ and…

Combinatorics · Mathematics 2025-07-29 Colin Defant , Rupert Li , Evita Nestoridi

For general spin systems, we prove that a contractive coupling for any local Markov chain implies optimal bounds on the mixing time and the modified log-Sobolev constant for a large class of Markov chains including the Glauber dynamics,…

The goal of this paper is to push forward the study of those properties of log-concave measures that help to estimate their Poincar{\'e} constant. First we revisit E. Milman's result [40] on the link between weak (Poincar{\'e} or…

Probability · Mathematics 2018-10-22 Patrick Cattiaux , Arnaud Guillin

We prove existence of minimizers for the sharp Poincar\'e-Sobolev constant in general Steiner symmetric sets, in the subcritical and superhomogeneous regime. The sets considered are not necessarily bounded, thus the relevant embeddings may…

Analysis of PDEs · Mathematics 2025-05-19 Lorenzo Brasco , Luca Briani , Francesca Prinari

About two dozens of exactly solvable Markov chains on one-dimensional finite and semi-infinite integer lattices are constructed in terms of convolutions of orthogonality measures of the Krawtchouk, Hahn, Meixner, Charlier, $q$-Hahn,…

Probability · Mathematics 2022-06-17 Satoru Odake , Ryu Sasaki

We prove a lower bound on the sharp Poincar\'e-Sobolev embedding constants for general open sets, in terms of their inradius. We consider the following two situations: planar sets with given topology; open sets in any dimension, under the…

Analysis of PDEs · Mathematics 2024-01-17 Francesco Bozzola , Lorenzo Brasco

Functional inequalities such as the Poincar\'e and log-Sobolev inequalities quantify convergence to equilibrium in continuous-time Markov chains by linking generator properties to variance and entropy decay. However, many applications,…

Probability · Mathematics 2026-02-20 Bastian Hilder , Patrick van Meurs , Upanshu Sharma

A discrete-time Markov chain can be transformed into a new Markov chain by looking at its states along iterations of an almost surely finite stopping time. By the optional stopping theorem, any bounded harmonic function with respect to the…

Probability · Mathematics 2022-05-04 Iddo Ben-Ari , Behrang Forghani

Logarithmic Sobolev inequalities are a powerful way to estimate the rate of convergence of Markov chains and to derive concentration inequalities on distributions. We prove that the log-Sobolev constant of any isotropic logconcave density…

Probability · Mathematics 2017-12-06 Yin Tat Lee , Santosh S. Vempala

We prove logarithmic Sobolev inequality for measures $$ q^n(x^n)=\text{dist}(X^n)=\exp\bigl(-V(x^n)\bigr), \quad x^n\in \Bbb R^n, $$ under the assumptions that: (i) the conditional distributions $$ Q_i(\cdot| x_j, j\neq i)=\text{dist}(X_i|…

Probability · Mathematics 2015-06-23 Katalin Marton