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We study the Markov chain on $\mathbf{F}_p$ obtained by applying a function $f$ and adding $\pm\gamma$ with equal probability. When $f$ is a linear function, this is the well-studied Chung--Diaconis--Graham process. We consider two cases:…

Probability · Mathematics 2022-03-08 Jimmy He

This review paper provides an introduction of Markov chains and their convergence rates which is an important and interesting mathematical topic which also has important applications for very widely used Markov chain Monte Carlo (MCMC)…

Probability · Mathematics 2021-09-03 Yu Hang Jiang , Tong Liu , Zhiya Lou , Jeffrey S. Rosenthal , Shanshan Shangguan , Fei Wang , Zixuan Wu

The cutoff phenomenon is an abrupt transition from out of equilibrium to equilibrium undergone by certain Markov processes in the limit where the size of the state space tends to infinity: instead of decaying gradually over time, their…

Probability · Mathematics 2025-08-29 Justin Salez

We estimate the mixing time of the a nonreversible finite Markov chain called Repeated Balls-into-Bins (RBB) process. This process is a discrete time conservative interacting particle system with parallel updates. Place initially in $L$…

Probability · Mathematics 2020-07-10 Nicoletta Cancrini , Gustavo Posta

Markov chains on the non-negative quadrant of dimension $d$ are often used to model the stochastic dynamics of the number of $d$ entities, such as $d$ chemical species in stochastic reaction networks. The infinite state space poses…

Probability · Mathematics 2024-10-17 Wai-Tong Louis Fan , Jinsu Kim , Chaojie Yuan

Consider a sequence (indexed by n) of Markov chains Z^n in R^d characterized by transition kernels that approximately (in n) depend only on the rescaled state n^{-1} Z^n. Subject to a smoothness condition, such a family can be closely…

Probability · Mathematics 2009-08-17 Kamil Szczegot

We present a novel approach to quantizing Markov chains. The approach is based on the Markov chain coupling method, which is frequently used to prove fast mixing. Given a particular coupling, e.g., a grand coupling, we construct a…

Quantum Physics · Physics 2025-12-24 Kristan Temme , Pawel Wocjan

We consider the almost semi-continuous processes defined on a finite Markov chain. The representation of the moment generating functions for the absolute maximum after achievement positive level and for the recovery time are obtained.…

Probability · Mathematics 2011-07-12 Ievgen Karnaukh

In a series of recent works, Boyd, Diaconis, and their co-authors have introduced a semidefinite programming approach for computing the fastest mixing Markov chain on a graph of allowed transitions, given a target stationary distribution.…

Probability · Mathematics 2011-09-07 S. Roch

This simple note lays out a few observations which are well known in many ways but may not have been said in quite this way before. The basic idea is that when comparing two different Markov chains it is useful to couple them is such a way…

Probability · Mathematics 2017-11-16 James E. Johndrow , Jonathan C. Mattingly

The Burnside process is a classical Markov chain for sampling uniformly from group orbits. We introduce the dual Burnside process, obtained by interchanging the roles of group elements and states. This dual chain has stationary law…

Probability · Mathematics 2026-05-22 Ivan Z. Feng

We present a general method to derive the metastable behavior of weakly mixing Markov chains. This approach is based on properties of the resolvent equations and can be applied to metastable dynamics which do not satisfy the mixing…

Probability · Mathematics 2024-06-21 Claudio Landim , Diego Marcondes , Insuk Seo

When two Markov operators commute, it suggests that we can couple two copies of one of the corresponding processes. We explicitly construct a number of couplings of this type for a commuting family of Markov processes on the set of…

Probability · Mathematics 2008-11-20 Anthony P. Metcalfe , Neil O'Connell , Jon Warren

This study introduces a novel approach for learning mixtures of Markov chains, a critical process applicable to various fields, including healthcare and the analysis of web users. Existing research has identified a clear divide in…

Machine Learning · Computer Science 2024-05-27 Fabian Spaeh , Konstantinos Sotiropoulos , Charalampos E. Tsourakakis

Dealing with finite Markov chains in discrete time, the focus often lies on convergence behavior and one tries to make different copies of the chain meet as fast as possible and then stick together. There is, however, a very peculiar kind…

Probability · Mathematics 2017-02-15 Timo Hirscher , Anders Martinsson

We show a strict hierarchy among various edge and vertex expansion properties of Markov chains. This gives easy proofs of a range of bounds, both classical and new, on chi-square distance, spectral gap and mixing time. The 2-gradient is…

Probability · Mathematics 2009-04-03 Ravi Montenegro

We prove an upper bound on the total variation mixing time of a finite Markov chain in terms of the absolute spectral gap and the number of elements in the state space. Unlike results requiring reversibility or irreducibility, this bound is…

Probability · Mathematics 2013-10-31 Daniel Jerison

A 1-2 model configuration is a subset of edges of a hexagonal lattice satisfying the constraint that each vertex is incident to 1 or 2 edges. We introduce Markov chains to sample the 1-2 model configurations on 2D hexagonal lattice and…

Probability · Mathematics 2019-01-01 Zhongyang Li

For each $n$ let $Y^n_t$ be a continuous time symmetric Markov chain with state space $n^{-1} \Z^d$. A condition in terms of the conductances is given for the convergence of the $Y^n_t$ to a symmetric Markov process $Y_t$ on $\R^d$. We have…

Probability · Mathematics 2008-07-22 R. F. Bass , T. Kumagai , T. Uemura

In this paper, we develop some matrix Poisson's equations satisfied by the mean and variance of the mixing time in an irreducible positive-recurrent discrete-time Markov chain with infinitely-many levels, and provide a computational…

Probability · Mathematics 2013-08-21 Quan-Lin Li , Jing Cao
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