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The mixer chain on a graph G is the following Markov chain. Place tiles on the vertices of G, each tile labeled by its corresponding vertex. A "mixer" moves randomly on the graph, at each step either moving to a randomly chosen neighbor, or…

Probability · Mathematics 2009-01-13 Ariel Yadin

Let $T$ be the regular tree in which every vertex has exactly $d\ge 3$ neighbours. Run a branching random walk on $T$, in which at each time step every particle gives birth to a random number of children with mean $d$ and finite variance,…

Probability · Mathematics 2019-11-19 Matthew I. Roberts

We compute the mixing rate of a non-backtracking random walk on a regular expander. Using some properties of Chebyshev polynomials of the second kind, we show that this rate may be up to twice as fast as the mixing rate of the simple random…

Probability · Mathematics 2011-06-27 Noga Alon , Itai Benjamini , Eyal Lubetzky , Sasha Sodin

Whereas classical invariance principles for ergodic Markov chains address the situation in which the time horizon of observations is much larger than the mixing time, the quality of approximation is questionable when this is not the case…

Probability · Mathematics 2026-05-12 Gabriele Bellerino , Angelika Rohde

Consider a Markov chain with finite state space and suppose you wish to change time replacing the integer step index $n$ with a random counting process $N(t)$. What happens to the mixing time of the Markov chain? We present a partial reply…

Probability · Mathematics 2021-11-17 Nicos Georgiou , Enrico Scalas

In this paper we consider coalescing random walks on a general connected graph $G=(V,E)$. We set up a unified framework to study the leading order of the decay rate of $P_t$, the expectation of the fraction of occupied sites at time $t$,…

Probability · Mathematics 2022-09-13 Jonathan Hermon , Shuangping Li , Dong Yao , Lingfu Zhang

We define a general model of stochastically-evolving graphs, namely the \emph{Edge-Uniform Stochastically-Evolving Graphs}. In this model, each possible edge of an underlying general static graph evolves independently being either alive or…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-19 Ioannis Lamprou , Russell Martin , Paul Spirakis

This paper studies Markov chains on the symmetric group $S_n$ where the transition probabilities are given by the Ewens distribution with parameter $\theta>1$. The eigenvalues are identified to be proportional to the content polynomials of…

Probability · Mathematics 2022-09-21 Alperen Y. Özdemir

Most approximation algorithms for #P-complete problems (e.g., evaluating the permanent of a matrix or the volume of a polytope) work by reduction to the problem of approximate sampling from a distribution $\pi$ over a large set $\S$. This…

Quantum Physics · Physics 2011-11-09 Peter C. Richter

We consider one-dimensional discrete-time random walks (RWs) with arbitrary symmetric and continuous jump distributions $f(\eta)$, including the case of L\'evy flights. We study the expected maximum ${\mathbb E}[M_n]$ of bridge RWs, i.e.,…

Statistical Mechanics · Physics 2021-08-30 Benjamin De Bruyne , Satya N. Majumdar , Gregory Schehr

We analyze hitting times of simple random walk on realizations of the stochastic block model. We show that under some natural assumptions the hitting time averaged over the target vertex asymptotically almost surely given by $N(1+o(1))$. On…

Probability · Mathematics 2025-04-24 Matthias Löwe , Sara Terveer

We consider a Markov jump process on a general state space to which we apply a time-dependent weak perturbation over a finite time interval. By martingale-based stochastic calculus, under a suitable exponential moment bound for the…

Probability · Mathematics 2024-05-14 Alessandra Faggionato , Vittoria Silvestri

We analyse a random walk on the ring of integers mod $n$, which at each time point can make an additive `step' or a multiplicative `jump'. When the probability of making a jump tends to zero as an appropriate power of $n$ we prove the…

Probability · Mathematics 2016-02-26 Michael E. Bate , Stephen B. Connor

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

Random walks are a fundamental tool for analyzing realistic complex networked systems and implementing randomized algorithms to solve diverse problems such as searching and sampling. For many real applications, their actual effect and…

Social and Information Networks · Computer Science 2018-03-09 Yuan Lin , Zhongzhi Zhang

Under the assumption that sequences of graphs equipped with resistances, associated measures, walks and local times converge in a suitable Gromov-Hausdorff topology, we establish asymptotic bounds on the distribution of the…

Probability · Mathematics 2025-09-30 George Andriopoulos

In this article, we present new random walk methods to solve flow and transport problems in unsaturated/saturated porous media, including coupled flow and transport processes in soils, heterogeneous systems modeled through random hydraulic…

Numerical Analysis · Mathematics 2021-05-14 Nicolae Suciu , Davide Illiano , Alexander Prechtel , Florin A. Radu

We investigate the statistics of the gap, G_n, between the two rightmost positions of a Markovian one-dimensional random walker (RW) after n time steps and of the duration, L_n, which separates the occurrence of these two extremal…

Statistical Mechanics · Physics 2013-08-26 Satya N. Majumdar , Philippe Mounaix , Gregory Schehr

We introduce a new partial order on the class of stochastically monotone Markov kernels having a given stationary distribution $\pi$ on a given finite partially ordered state space $\mathcal{X}$. When $K\preceq L$ in this partial order we…

Probability · Mathematics 2013-09-09 James Allen Fill , Jonas Kahn

We study the mixing time of a random walk on the torus, alternated with a Lebesgue measure preserving Bernoulli map. Without the Bernoulli map, the mixing time of the random walk alone is $O(1/\epsilon^2)$, where $\epsilon$ is the step…

Probability · Mathematics 2023-03-28 Gautam Iyer , Ethan Lu , James Nolen