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Consider a simple random walk on a realization of an Erd\H{o}s-R\'enyi graph. Assume that it is asymptotically almost surely (a.a.s.) connected. Conditional on an eigenvector delocalization conjecture, we prove a Central Limit Theorem (CLT)…

Probability · Mathematics 2023-11-28 Matthias Löwe , Sara Terveer

Analyzing the mixing time of random walks is a well-studied problem with applications in random sampling and more recently in graph partitioning. In this work, we present new analysis of random walks and evolving sets using more…

Data Structures and Algorithms · Computer Science 2015-07-09 Siu On Chan , Tsz Chiu Kwok , Lap Chi Lau

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

We study a class of nearest-neighbor discrete time integer random walks introduced by Zerner, the so called multi-excited random walks. The jump probabilities for such random walker have a drift to the right whose intensity depends on a…

Probability · Mathematics 2011-08-15 Thomas Mountford , Leandro P. R. Pimentel , Glauco Valle

We introduce the notion of a "random basic walk" on an infinite graph, give numerous examples, list potential applications, and provide detailed comparisons between the random basic walk and existing generalizations of simple random walks.…

Discrete Mathematics · Computer Science 2013-08-06 David White

We consider the following problem arising from the study of human problem solving: Let $G$ be a vertex-weighted graph with marked "in" and "out" vertices. Suppose a random walker begins at the in-vertex, steps to neighbors of vertices with…

Combinatorics · Mathematics 2009-05-28 Joshua N. Cooper

We propose a model of random walks on weighted graphs where the weights are interval valued, and connect it to reversible imprecise Markov chains. While the theory of imprecise Markov chains is now well established, this is a first attempt…

Optimization and Control · Mathematics 2016-09-20 Damjan Škulj

We construct a bounded degree graph $G$, such that a simple random walk on it is transient but the random walk path (i.e., the subgraph of all the edges the random walk has crossed) has only finitely many cutpoints, almost surely. We also…

Probability · Mathematics 2011-04-11 Itai Benjamini , Ori Gurel-Gurevich , Oded Schramm

We consider self-avoiding walk on finite graphs with large girth. We study a few aspects of the model originally considered by Lawler, Schramm and Werner on finite balls in Z^d. The expected length of a random self avoiding path is…

Probability · Mathematics 2016-06-22 Ariel Yadin

We consider random walks that start and are absorbed on the leaves of random networks and study the length of such walks. For the networks we investigate, Erdos-Renyi random graphs and Barabasi-Albert scale free networks, these walks are…

Disordered Systems and Neural Networks · Physics 2016-07-11 David Lancaster

Graph-limit theory focuses on the convergence of sequences of graphs when the number of nodes becomes arbitrarily large. This framework defines a continuous version of graphs allowing for the study of dynamical systems on very large graphs,…

Probability · Mathematics 2020-05-20 Julien Petit , Renaud Lambiotte , Timoteo Carletti

Consider an expander graph in which a $\mu$ fraction of the vertices are marked. A random walk starts at a uniform vertex and at each step continues to a random neighbor. Gillman showed in 1993 that the number of marked vertices seen in a…

Probability · Mathematics 2017-08-25 Shravas Rao , Oded Regev

On a connected finite graph, we propose an evolution of weights including Ollivier's Ricci flow as a special case. During the evolution process, on each edge, the speed of change of weight is exactly the difference between the Wasserstein…

Classical Analysis and ODEs · Mathematics 2025-04-30 Jicheng Ma , Yunyan Yang

We study random walks on Erd\"os-R\'enyi random graphs in which, every time the random walk returns to the starting point, first an edge probability is independently sampled according to a priori measure $\mu$, and then an Erd\"os-R\'enyi…

Probability · Mathematics 2025-02-06 Giulio Iacobelli , Guilherme Ost , Daniel Y. Takahashi

Suppose we are given the free product $V$ of a finite family of finite or countable sets $(V_i)_{i\in\mathcal{I}}$ and probability measures on each $V_i$, which govern random walks on it. We consider a transient random walk on the free…

Probability · Mathematics 2007-08-29 Lorenz Gilch

We derive an exact closed-form analytical expression for the distribution of the cover time for a random walk over an arbitrary graph. In special case, we derive simplified exact expressions for the distributions of cover time for a…

Mathematical Physics · Physics 2009-10-20 Nikola Zlatanov , Ljupco Kocarev

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

Suppose we are given a homogeneous tree $\mathcal{T}_q$ of degree $q\geq 3$, where at each vertex sits a lamp, which can be switched on or off. This structure can be described by the wreath product $(\mathbb{Z}/2)\wr \Gamma$, where…

Probability · Mathematics 2007-08-29 Lorenz Gilch

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

Graph vertex embeddings based on random walks have become increasingly influential in recent years, showing good performance in several tasks as they efficiently transform a graph into a more computationally digestible format while…

Machine Learning · Statistics 2021-07-22 Dominik Kloepfer , Angelica I. Aviles-Rivero , Daniel Heydecker