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We discuss problems posed by the quantitative study of time inhomogeneous Markov chains. The two main notions for our purpose are merging and stability. Merging (also called weak ergodicity) occurs when the chain asymptotically forgets…

Probability · Mathematics 2010-04-15 Laurent Saloff-Coste , Jessica Zuniga

The main subject of the study in this paper is the simultaneous renewal time for two time-inhomogeneous Markov chains which start with arbitrary initial distributions. By a simultaneous renewal we mean the first time of joint hitting the…

Probability · Mathematics 2020-01-09 Vitaliy Golomoziy

We study an irreducible Markov chain on the category of finite abelian $p$-groups, whose stationary measure is the Cohen-Lenstra distribution. This Markov chain arises when one studies the cokernel of a random matrix $M$, after conditioning…

Probability · Mathematics 2024-08-14 Nikita Lvov

We study the limit behaviour of a generally non-linear ordinary differential equation whose solution is a superadditive generalisation of a stochastic matrix, and provide necessary and sufficient conditions for this solution to be ergodic,…

Probability · Mathematics 2016-09-21 Jasper De Bock

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 a new Bernstein-type deviation inequality for general (non-reversible) discrete-time Markov chains via an elementary approach. More robust than existing works in the literature, our result only requires the Markov chain to…

Probability · Mathematics 2025-10-07 De Huang , Xiangyuan Li

A finite ergodic Markov chain is said to exhibit cutoff if its distance to stationarity remains close to 1 over a certain number of iterations and then abruptly drops to near 0 on a much shorter time scale. Discovered in the context of card…

Probability · Mathematics 2015-04-10 Anna Ben-Hamou , Justin Salez

This paper studies a finite reversible lumpable Markov chain for which relaxed spectral compression yields a larger determinant than partition-constrained compression. For a symmetric six-state lumpable chain and the positive operator…

Probability · Mathematics 2026-04-14 Oleg Kiriukhin

Improved rates of convergence for ergodic homogeneous Markov chains are studied. In comparison to the earlier papers the setting is also generalised to the case without a unique dominated measure. Examples are provided where the new bound…

Probability · Mathematics 2021-11-02 Alexander Veretennikov , Maria Veretennikova

The standard coalescent is widely used in evolutionary biology and population genetics to model the ancestral history of a sample of molecular sequences as a rooted and ranked binary tree. In this paper, we present a representation of the…

Probability · Mathematics 2020-12-16 Mackenzie Simper , Julia A. Palacios

We present a spectral-theoretic approach to time-average statistical mechanics for general, non-equilibrium initial conditions. We consider the statistics of bounded, local additive functionals of reversible as well as irreversible ergodic…

Statistical Mechanics · Physics 2020-10-21 Alessio Lapolla , David Hartich , Aljaž Godec

A spectral method for identifying lumping in large Markov chains is presented. Identification of meta stable states is treated as a special case. The method is based on spectral analysis of a self-adjoint matrix that is a function of the…

Numerical Analysis · Mathematics 2010-02-19 Martin Nilsson Jacobi

There is a relation between the irreversibility of thermodynamic processes as expressed by the breaking of time-reversal symmetry, and the entropy production in such processes. We explain on an elementary mathematical level the relations…

Statistical Mechanics · Physics 2007-05-23 C. Maes , K. Netocny

Time-homogeneous Markov chains are often used as disease progression models in studies of cost-effectiveness and optimal decision-making. Maximum likelihood estimation of these models can be challenging when data are collected at a time…

Methodology · Statistics 2022-09-26 Duncan Ermini Leaf

We compute the stationary distribution of a continuous-time Markov chain which is constructed by gluing together two finite, irreducible Markov chains by identifying a pair of states of one chain with a pair of states of the other and…

Probability · Mathematics 2015-10-22 Bence Mélykúti , Peter Pfaffelhuber

We further clarify the relation between detailed-balanced and complex-balanced equilibria of reversible chemical reaction networks. Our results hold for arbitrary kinetics and also for boundary equilibria. Detailed balance, complex balance,…

Dynamical Systems · Mathematics 2020-09-29 Stefan Müller , Badal Joshi

The problem of sampling from the stationary distribution of a Markov chain finds widespread applications in a variety of fields. The time required for a Markov chain to converge to its stationary distribution is known as the classical…

Quantum Physics · Physics 2022-09-14 Shantanav Chakraborty , Kyle Luh , Jérémie Roland

The paper presents efficient approaches for evaluating convergence rate in total variation for finite and general linear Markov chains. The motivation for studying convergence rate in this metric is its usefulness in various limit theorems.…

Probability · Mathematics 2026-01-21 Alexander Veretennikov

We consider nonparametric estimation of the transition operator $P$ of a Markov chain and its transition density $p$ where the singular values of $P$ are assumed to decay exponentially fast. This is for instance the case for periodised,…

Statistics Theory · Mathematics 2021-10-26 Matthias Löffler , Antoine Picard

This pedagogical document explains three variational representations that are useful when comparing the efficiencies of reversible Markov chains: (i) the Dirichlet form and the associated variational representations of the spectral gaps;…

Statistics Theory · Mathematics 2025-06-23 Chris Sherlock