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Mixing properties of discrete-time quantum walks on two-dimensional grids with torus-like boundary conditions are analyzed, focusing on their connection to the complexity of the corresponding abstract search algorithm. In particular, an…

Quantum Physics · Physics 2012-05-18 F. L. Marquezino , R. Portugal , G. Abal

We consider an $n$-tuple of independent ergodic Markov processes, each of which converges (in the sense of separation distance) at an exponential rate, and obtain a necessary and sufficient condition for the $n$-tuple to exhibit a…

Probability · Mathematics 2010-03-19 Stephen B. Connor

We give conditions under which near-critical stochastic processes on the half-line have infinitely many or finitely many cutpoints, generalizing existing results on nearest-neighbour random walks to adapted processes with bounded increments…

Probability · Mathematics 2022-03-21 Chak Hei Lo , Mikhail V. Menshikov , Andrew R. Wade

We consider a Markov chain on invertible $n\times n$ matrices with entries in $\mathbb{Z}_2$ which moves by picking an ordered pair of distinct rows and add the first one to the other, modulo $2$. We establish a logarithmic Sobolev…

Probability · Mathematics 2025-09-29 Anna Ben-Hamou

Totally asymmetric simple exclusion processes, consisting of two coupled parallel lattice chains with particles interacting with hard-core exclusion and moving along the channels and between them, are considered. In the limit of strong…

Statistical Mechanics · Physics 2009-11-10 Ekaterina Pronina , Anatoly B. Kolomeisky

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 establish cutoff for a natural random walk (RW) on the set of perfect matchings (PMs). An $n$-PM is a pairing of $2n$ objects. The $k$-PM RW selects $k$ pairs uniformly at random, disassociates the corresponding $2k$ objects, then…

Probability · Mathematics 2024-05-21 Sam Olesker-Taylor

We establish three remarkable consequences of non-negative curvature for sparse Markov chains. First, their conductance decreases logarithmically with the number of states. Second, their displacement is at least diffusive until the mixing…

Probability · Mathematics 2022-06-17 Florentin Münch , Justin Salez

The mixing time of a Markov chain determines how fast the iterates of the Markov chain converge to the stationary distribution; however, it does not control the dependencies between samples along the Markov chain. In this paper, we study…

Statistics Theory · Mathematics 2025-06-30 Jiaming Liang , Siddharth Mitra , Andre Wibisono

We consider the reversible exclusion process with reservoirs on arbitrary networks. We characterize the spectral gap, mixing time, and mixing window of the process, in terms of certain simple statistics of the underlying network. Among…

Probability · Mathematics 2022-01-13 Justin Salez

It is a fact simple to establish that the mixing time of the simple random walk on a d-regular graph $G_n$ with n vertices is asymptotically bounded from below by $d/ ((d-2)\log (d-1))\log n$. Such a bound is obtained by comparing the walk…

Probability · Mathematics 2021-02-17 Charles Bordenave , Hubert Lacoin

We compute the mixing time of the Facilitated Exclusion Process (FEP) and obtain cutoff and pre-cutoff in different regimes. The main tool to obtain this result is a new bijective, deterministic mapping between the joint law of an ergodic…

Probability · Mathematics 2026-01-30 Brune Massoulié

Let $G$ be a finite group. The commuting chain on $G$ moves from an element $x$ to $y$ by selecting $y$ uniformly amongst those which commute with $x$. The $t$ step transition probabilities of this chain converge to a distribution uniform…

Probability · Mathematics 2020-10-19 John Rahmani

In a recent study, (Jain et al 2007 Phys. Rev. Lett. 99 190601), a symmetric exclusion process with time-dependent hopping rates was introduced. Using simulations and a perturbation theory, it was shown that if the hopping rates at two…

Statistical Mechanics · Physics 2008-11-17 Rahul Marathe , Kavita Jain , Abhishek Dhar

We show how to map the states of an ergodic Markov chain to Euclidean space so that the squared distance between states is the expected commuting time. We find a minimax characterization of commuting times, and from this we get monotonicity…

Probability · Mathematics 2017-10-27 Peter G. Doyle , Jean Steiner

We investigate a novel variant of the exclusion process in which particles perform asymmetric nearest-neighbor jumps across a bond \((k, k+1)\) only if the preceding site \((k-1)\) is unoccupied. This next-nearest-neighbor constraint…

Statistical Mechanics · Physics 2025-09-19 Gunter Schutz , Ali Zahra

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

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

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

Markov chains are convenient means of generating realizations of networks with a given (joint or otherwise) degree distribution, since they simply require a procedure for rewiring edges. The major challenge is to find the right number of…

Social and Information Networks · Computer Science 2012-11-01 J. Ray , A. Pinar , C. Seshadhri