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A class of examples is constructed to show that for strictly stationary Markov chains that are reversible, the simultaneous mixing rates for the $\rho$-mixing and strong mixing ($\alpha$-mixing) conditions can be fairly arbitrary, within…

Probability · Mathematics 2022-10-04 Richard C. Bradley

In the analysis of Markov chains and processes, it is sometimes convenient to replace an unbounded state space with a "truncated" bounded state space. When such a replacement is made, one often wants to know whether the equilibrium behavior…

Probability · Mathematics 2022-03-30 Alex Infanger , Peter W. Glynn , Yuanyuan Liu

Discovered in the context of card shuffling by Aldous, Diaconis and Shahshahani, the cutoff phenomenon has since then been established in a variety of Markov chains. However, proving cutoff remains a delicate affair, which requires a…

Probability · Mathematics 2021-03-02 Justin Salez

We consider continuous-space, discrete-time Markov chains on $\mathbb{R}^d$, that admit a finite number $N$ of metastable states. Our main motivation for investigating these processes is to analyse random Poincar\'e maps, which describe…

Probability · Mathematics 2025-08-19 Nils Berglund

We introduce a unified operator-theoretic framework for analyzing mixing times of finite-state ergodic Markov chains that applies to both reversible and non-reversible dynamics. The central object in our analysis is the projected transition…

Probability · Mathematics 2025-11-05 Muhammad Abdullah Naeem

We provide new upper bounds for mixing times of general finite Markov chains. We use these bounds to show that the total variation mixing time is robust under rough isometry for bounded degree graphs that are roughly isometric to trees.

Probability · Mathematics 2017-12-06 Louigi Addario-Berry , Matthew I. Roberts

Sampling uniform simple graphs with power-law degree distributions with degree exponent $\tau\in(2,3)$ is a non-trivial problem. We propose a method to sample uniform simple graphs that uses a constrained version of the configuration model…

Probability · Mathematics 2017-11-17 Tom Bannink , Remco van der Hofstad , Clara Stegehuis

In this paper we consider the field of local times of a discrete-time Markov chain on a general state space, and obtain uniform (in time) upper bounds on the total variation distance between this field and the one of a sequence of $n$…

Probability · Mathematics 2019-03-25 Diego F. de Bernardini , Christophe Gallesco , Serguei Popov

The cutoff phenomenon describes a sharp transition in the convergence of a Markov chain to equilibrium. In recent work, the authors established cutoff and its location for the stochastic Ising model on the $d$-dimensional torus $(Z/nZ)^d$…

Probability · Mathematics 2012-11-06 Eyal Lubetzky , Allan Sly

The switch Markov chain has been extensively studied as the most natural Markov Chain Monte Carlo approach for sampling graphs with prescribed degree sequences. We use comparison arguments with other, less natural but simpler to analyze,…

Discrete Mathematics · Computer Science 2018-10-29 Georgios Amanatidis , Pieter Kleer

In this paper, we are interested in investigating the perturbation bounds for the stationary distributions for discrete-time or continuous-time Markov chains on a countable state space. For discrete-time Markov chains, two new norm-wise…

Probability · Mathematics 2012-08-27 Yuanyuan Liu

In this paper, we propose a new Markov chain which generalizes random-to-random shuffling on permutations to random-to-random shuffling on linear extensions of a finite poset of size $n$. We conjecture that the second largest eigenvalue of…

Probability · Mathematics 2017-03-01 Arvind Ayyer , Anne Schilling , Nicolas M. Thiéry

We find the total variation mixing time of the interchange process on the dumbbell graph (two complete graphs, $K_n$ and $K_m$, connected by a single edge), and show that this sequence of chains exhibits the cutoff phenomenon precisely when…

Probability · Mathematics 2019-08-27 Richárd Patkó , Gábor Pete

We consider the East model in $\mathbb Z^d$, an example of a kinetically constrained interacting particle system with oriented constraints, together with one of its natural variant. Under any ergodic boundary condition it is known that the…

Probability · Mathematics 2025-09-15 Concetta Campailla , Fabio Martinelli

This paper gives a necessary and sufficient condition for a sequence of birth and death chains to converge abruptly to stationarity, that is, to present a cut-off. The condition involves the notions of spectral gap and mixing time. Y. Peres…

Probability · Mathematics 2007-05-23 Persi Diaconis , Laurent Saloff-Coste

This paper explores the mixing time of the random transposition walk on permutations with one-sided interval restrictions. In particular, we're interested in the notion of cutoff, a phenomenon which occurs when mixing occurs in a window of…

Probability · Mathematics 2012-02-23 Olena Blumberg

We give a new proof of a result of Rudolph stating that a countable-state mixing Markov chain with exponential return times is finitarily isomorphic to an IID process. Besides being short and direct, our proof has the added benefit of…

Probability · Mathematics 2025-06-05 Yinon Spinka

In this paper, we consider a general class of two-time-scale Markov chains whose transition rate matrix depends on a parameter $\lambda>0$. We assume that some transition rates of the Markov chain will tend to infinity as…

Probability · Mathematics 2015-07-10 Chen Jia

The spectral gap $\gamma$ of a finite, ergodic, and reversible Markov chain is an important parameter measuring the asymptotic rate of convergence. In applications, the transition matrix $P$ may be unknown, yet one sample of the chain up to…

Statistics Theory · Mathematics 2017-08-25 Daniel Hsu , Aryeh Kontorovich , David A. Levin , Yuval Peres , Csaba Szepesvári

The cutoff phenomenon was recently shown to systematically follow from non-negative curvature and the product condition, for all Markov diffusions. The proof crucially relied on a classical \emph{chain rule} satisfied by the carr\'e du…

Probability · Mathematics 2025-01-23 Francesco Pedrotti , Justin Salez