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We provide an explicit formula for the global mean first-passage time (GMFPT) for random walks in a general graph with a perfect trap fixed at an arbitrary node, where GMFPT is the average of mean first-passage time to the trap over all…

Statistical Mechanics · Physics 2012-09-28 Yuan Lin , Alafate Julaiti , Zhongzhi Zhang

For a finite graph $G=(V,E)$ let $G^*$ be obtained by considering a random perfect matching of $V$ and adding the corresponding edges to $G$ with weight $\varepsilon$, while assigning weight 1 to the original edges of $G$. We consider…

Probability · Mathematics 2023-10-17 Zsuzsanna Baran , Jonathan Hermon , Anđela Šarković , Perla Sousi

We consider a random walk on a $d$-regular graph $G$ where $d\to\infty$ and $G$ satisfies certain conditions. Our prime example is the $d$-dimensional hypercube, which has $n=2^d$ vertices. We explore the likely component structure of the…

Combinatorics · Mathematics 2014-10-09 Colin Cooper , Alan Frieze

We show that the expected time for a random walk on a (multi-)graph $G$ to traverse all $m$ edges of $G$, and return to its starting point, is at most $2m^2$; if each edge must be traversed in both directions, the bound is $3m^2$. Both…

Combinatorics · Mathematics 2019-02-20 Agelos Georgakopoulos , Peter Winkler

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 arbitrary graphs $G$ with $n$ vertices and minimum degree at least $\delta n$ where $\delta>0$ is constant. If the conductance of $G$ is sufficiently large then we obtain an asymptotic expression for the cover time $C_G$ of $G$…

Combinatorics · Mathematics 2019-05-29 Colin Cooper , Alan Frieze , Wesley Pegden

In this paper we find an upper bound for the probability that a $3$ dimensional simple random walk covers each point in a nearest neighbor path connecting 0 and the boundary of an $L_1$ ball of radius $N$. For $d\ge 4$, it has been shown in…

Probability · Mathematics 2017-05-12 Eviatar B. Procaccia , Yuan Zhang

Random walks on expander graphs were thoroughly studied, with the important motivation that, under some natural conditions, these walks mix quickly and provide an efficient method of sampling the vertices of a graph. Alon, Benjamini,…

Probability · Mathematics 2007-05-23 Noga Alon , Eyal Lubetzky

The quantum walk dynamics obey the laws of quantum mechanics with an extra locality constraint, which demands that the evolution operator is local in the sense that the walker must visit the neighboring locations before endeavoring to…

Quantum Physics · Physics 2023-05-23 Caue F. T. Silva , Daniel Posner , Renato Portugal

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 prove new results on lazy random walks on finite graphs. To start, we obtain new estimates on return probabilities $P^t(x,x)$ and the maximum expected hitting time $t_{\rm hit}$, both in terms of the relaxation time. We also prove a…

Probability · Mathematics 2018-07-19 Roberto I. Oliveira , Yuval Peres

Random walks on expanders play a crucial role in Markov Chain Monte Carlo algorithms, derandomization, graph theory, and distributed computing. A desirable property is that they are rapidly mixing, which is equivalent to having a spectral…

Probability · Mathematics 2024-12-18 Sam Olesker-Taylor , Thomas Sauerwald , John Sylvester

The graph obtained from the integer grid Z x Z by the removal of all horizontal edges that do not belong to the x-axis is called a comb. In a random walk on a graph, whenever a walker is at a vertex v, in the next step it will visit one of…

Probability · Mathematics 2013-09-26 János Pach , Gábor Tardos

The cycle space of a graph $G$, denoted $C(G)$, is a vector space over ${\mathbb F}_2$, spanned by all incidence vectors of edge-sets of cycles of $G$. If $G$ has $n$ vertices, then $C_n(G)$ is the subspace of $C(G)$, spanned by the…

Combinatorics · Mathematics 2025-07-08 Dan Hefetz , Michael Krivelevich

For a simple (unbiased) random walk on a connected graph with $n$ vertices, the cover time (the expected number of steps it takes to visit all vertices) is at most $O(n^3)$. We consider locally biased random walks, in which the probability…

Probability · Mathematics 2016-07-19 Roee David , Uriel Feige

We study properties of a simple random walk on the random digraph D_{n,p} when np={d\log n},\; d>1. We prove that whp the stationary probability pi_v of a vertex v is asymptotic to deg^-(v)/m where deg^-(v) is the in-degree of v and…

Combinatorics · Mathematics 2011-03-23 Colin Cooper , Alan Frieze

In a coalescing random walk, a set of particles make independent random walks on a graph. Whenever one or more particles meet at a vertex, they unite to form a single particle, which then continues the random walk through the graph.…

Data Structures and Algorithms · Computer Science 2016-12-28 Colin Cooper , Robert Elsasser , Hirotaka Ono , Tomasz Radzik

We prove that on any transitive graph $G$ with infinitely many ends, a self-avoiding walk of length $n$ is ballistic with extremely high probability, in the sense that there exist constants $c,t>0$ such that $\mathbb{P}_n(d_G(w_0,w_n)\geq…

Combinatorics · Mathematics 2026-01-14 Florian Lehner , Christian Lindorfer , Christoforos Panagiotis

Consider the random subgraph process on a base graph $G$ on $n$ vertices: a sequence $\lbrace G_t \rbrace _{t=0} ^{|E(G)|}$ of random subgraphs of $G$ obtained by choosing an ordering of the edges of $G$ uniformly at random, and by…

Combinatorics · Mathematics 2021-07-06 Yahav Alon , Michael Krivelevich

Search patterns of randomly oriented steps of different lengths have been observed on all scales of the biological world, ranging from the microscopic to the ecological, including in protein motors, bacteria, T-cells, honeybees, marine…

Quantitative Methods · Quantitative Biology 2020-02-14 Brieuc Guinard , Amos Korman