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We investigate the mixing rate of a Markov chain where a combination of long distance edges and non-reversibility is introduced: as a first step, we focus here on the following graphs: starting from the cycle graph, we select random nodes…

Probability · Mathematics 2018-02-13 Balázs Gerencsér , Julien Hendrickx

We study a simple Markov chain, the switch chain, on the set of all perfect matchings in a bipartite graph. This Markov chain was proposed by Diaconis, Graham and Holmes as a possible approach to a sampling problem arising in Statistics. We…

Data Structures and Algorithms · Computer Science 2017-01-27 Martin Dyer , Mark Jerrum , Haiko Müller

We introduce a Markov chain for sampling from the uniform distribution on a Riemannian manifold $\mathcal{M}$, which we call the $\textit{geodesic walk}$. We prove that the mixing time of this walk on any manifold with positive sectional…

Probability · Mathematics 2017-11-28 Oren Mangoubi , Aaron Smith

We develop Markov chain mixing time estimates for a class of Markov chains with restricted transitions. We assume transitions may occur along a cycle of $n$ nodes and on $n^\gamma$ additional edges, where $\gamma < 1$. We find that the…

Probability · Mathematics 2015-06-26 Balázs Gerencsér

We prove the convergence of the law of grid-valued random walks, which can be seen as time-space Markov chains, to the law of a general diffusion process. This includes processes with sticky features, reflecting or absorbing boundaries and…

Probability · Mathematics 2024-11-15 Alexis Anagnostakis , Antoine Lejay , Denis Villemonais

The first paper in this series introduced a \emph{short-to-long mixing} condition that captures mean-field GOE/GUE edge universality in the supercritical sparsity regime, for symmetric/Hermitian random matrices with independent entries and…

Probability · Mathematics 2026-04-23 Dang-Zheng Liu , Guangyi Zou

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

We investigate the mixing properties of a model of reversible Markov chains in random environment, which notably contains the simple random walk on the superposition of a deterministic graph and a second graph whose vertex set has been…

Probability · Mathematics 2026-05-13 Bastien Dubail

Quantum walks on graphs have been shown in certain cases to mix quadratically faster than their classical counterparts. Lifted Markov chains, consisting of a Markov chain on an extended state space which is projected back down to the…

Quantum Physics · Physics 2018-03-22 Danial Dervovic

We survey recent results concerning the total-variation mixing time of the simple exclusion process on the segment (symmetric and asymmetric) and a continuum analog, the simple random walk on the simplex with an emphasis on cutoff results.…

Probability · Mathematics 2021-11-15 Hubert Lacoin

We consider Markov chains on general state spaces in stationary random environment which are defined by a random mapping that is contractive up to a bounded perturbation. We prove their convergence to a limiting law, providing convergence…

Probability · Mathematics 2025-12-18 Attila Lovas , Miklós Rásonyi , Lionel Truquet

We survey existing techniques to bound the mixing time of Markov chains. The mixing time is related to a geometric parameter called conductance which is a measure of edge-expansion. Bounds on conductance are typically obtained by a…

Data Structures and Algorithms · Computer Science 2016-03-07 Venkatesan Guruswami

Exponential random graph models have become increasingly important in the study of modern networks ranging from social networks, economic networks, to biological networks. They seek to capture a wide variety of common network tendencies…

Probability · Mathematics 2019-06-07 Ryan DeMuse , Terry Easlick , Mei Yin

We prove that a uniformized variant of both the Rosenthal walk \cite{Rosenthal} and the Kac random walk \cite{Kac} on SO(n) mixes in $\cO(n^3)$ steps in total variation distance. The proof also extends easily to Rosenthal walk with fixed…

Probability · Mathematics 2011-10-26 Yunjiang Jiang

We establish and generalise several bounds for various random walk quantities including the mixing time and the maximum hitting time. Unlike previous analyses, our derivations are based on rather intuitive notions of local expansion…

Probability · Mathematics 2019-03-05 Thomas Sauerwald , Luca Zanetti

We consider tilings of $\mathbb{Z}^2$ by two types of squares. We are interested in the rate of convergence to the stationarity of a natural Markov chain defined for square tilings. The rate of convergence can be represented by the mixing…

Discrete Mathematics · Computer Science 2018-01-16 Alexandra Ugolnikova

We derive the first explicit bounds for the spectral gap of a random walk Metropolis algorithm on $R^d$ for any value of the proposal variance, which when scaled appropriately recovers the correct $d^{-1}$ dependence on dimension for…

Probability · Mathematics 2024-09-25 Christophe Andrieu , Anthony Lee , Sam Power , Andi Q. Wang

We analyze the absolute spectral gap of Markov chains on graphs obtained from a cycle of $n$ vertices and perturbed only at approximately $n^{1/\rho}$ random locations with an appropriate, possibly sparse, interconnection structure.…

Probability · Mathematics 2023-07-20 Balázs Gerencsér , Julien M. Hendrickx

This paper introduces the Attracting Random Walks model, which describes the dynamics of a system of particles on a graph with $n$ vertices. At each step, a single particle moves to an adjacent vertex (or stays at the current one) with…

Probability · Mathematics 2020-06-01 Julia Gaudio , Yury Polyanskiy

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