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For random walks on graph $\mathcal{G}$ with $n$ vertices and $m$ edges, the mean hitting time $H_j$ from a vertex chosen from the stationary distribution to vertex $j$ measures the importance for $j$, while the Kemeny constant…

Social and Information Networks · Computer Science 2024-12-17 Haisong Xia , Wanyue Xu , Zuobai Zhang , Zhongzhi Zhang

Theoretical computer science plays an important role in the understanding of social networks and their properties. We can model information rippling throughout social networks, or the opinions of social media users for example, using graph…

Discrete Mathematics · Computer Science 2024-06-11 Timothy Horscroft

The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random walk model is defined in terms of three parameters which control the probability of,…

Probability · Mathematics 2026-04-16 Luca Avena , Gianmarco Bet , Lars Schroeder , Clara Stegehuis

Let $G = (V,E)$ be a connected directed graph on $n$ vertices. Assign values from the set $\{1,2,\dots,n\}$ to the vertices of $G$ and update the values according to the following rule: uniformly at random choose a vertex and update its…

Data Structures and Algorithms · Computer Science 2024-06-05 John Larkin

This paper shows that graph spectral embedding using the random walk Laplacian produces vector representations which are completely corrected for node degree. Under a generalised random dot product graph, the embedding provides uniformly…

Methodology · Statistics 2021-05-05 Alexander Modell , Patrick Rubin-Delanchy

We prove for an arbitrary one-dimensional random walk with independent increments that the probability of crossing a level at a given time n has the order of square root of n. Moment or symmetry assumptions are not necessary. In removing…

Probability · Mathematics 2007-05-23 Rainer Siegmund-Schultze , Heinrich von Weizsaecker

We give a deterministic algorithm to construct a graph with no loops (a tree or a forest) whose vertices are the points of a d-dimensional stationary Poisson process S, subset of R^d. The algorithm is independent of the origin of…

Probability · Mathematics 2011-11-10 P. A. Ferrari , C. Landim , H. Thorisson

In this paper we define direct product of graphs and give a recipe for obtained probability of observing particle on vertices in the continuous-time classical and quantum random walk. In the recipe, the probability of observing particle on…

Quantum Physics · Physics 2015-05-13 S. Salimi , M. A. Jafarizadeh

A convergence theorem is obtained for quantum random walks with particles in an arbitrary normal state. This result unifies and extends previous work on repeated-interactions models, including that of the author (2010, J. London Math. Soc.…

Operator Algebras · Mathematics 2012-11-22 Alexander C. R. Belton

The evolution of many stochastic systems is accurately described by random walks on graphs. We here explore the close connection between local steady-state fluctuations of random walks and the global structure of the underlying graph.…

Statistical Mechanics · Physics 2022-10-25 M. Bruderer

We consider the continuous-time quantum walk defined on the adjacency matrix of a graph. At each instant, the walk defines a mixing matrix which is doubly-stochastic. The average of the mixing matrices contains relevant information about…

Combinatorics · Mathematics 2017-09-13 Gabriel Coutinho , Chris Godsil , Krystal Guo , Hanmeng Zhan

This paper considers non-backtracking random walks on random graphs generated according to the configuration model. The quantity of interest is the scaling of the mixing time of the random walk as the number of vertices of the random graph…

Probability · Mathematics 2022-09-15 Luca Avena , Hakan Güldaş , Remco van der Hofstad , Frank den Hollander , Oliver Nagy

We consider a modified random walk which uses unvisited edges whenever possible, and makes a simple random walk otherwise. We call such a walk an edge-process. We assume there is a rule A, which tells the walk which unvisited edge to use…

Data Structures and Algorithms · Computer Science 2015-03-20 Petra Berenbrink , Colin Cooper , Tom Friedetzky

We revisit an old minor topic in algorithms, the deterministic walk on a finite graph which always moves toward the nearest unvisited vertex until every vertex is visited. There is an elementary connection between this cover time and…

Probability · Mathematics 2021-03-19 David Aldous

The continuous-time quantum walk is a particle evolving by Schr\"odinger's equation in discrete space. Encoding the space as a graph of vertices and edges, the Hamiltonian is proportional to the discrete Laplacian. In some physical systems,…

Quantum Physics · Physics 2021-10-26 Thomas G. Wong , Joshua Lockhart

Following the recent work of Sznitman (arXiv:0805.4516), we investigate the microscopic picture induced by a random walk trajectory on a cylinder of the form G_N x Z, where G_N is a large finite connected weighted graph, and relate it to…

Probability · Mathematics 2010-07-13 David Windisch

Reflecting boundary conditions cause two one-dimensional random walks to synchronize if a common direction is chosen in each step. The mean synchronization time and its standard deviation are calculated analytically. Both quantities are…

Disordered Systems and Neural Networks · Physics 2007-05-23 Andreas Ruttor , Georg Reents , Wolfgang Kinzel

In [3] the radius of convergence of the generating function of the collision local time of two independent copies of an irreducible, symmetric and transient random walk on Zd, d \geq 1, was studied. Two versions were considered: z1, the…

Probability · Mathematics 2012-06-11 Frank den Hollander , Alex A. Opoku

Consider the random set composed of particles initially distributed on Zd, d >= 2, according to a Poisson point process of intensity u > 0 and moving as independent simple symmetric random walks, the trap particles. We are interested in the…

Probability · Mathematics 2025-07-22 Gonzalo Panizo , Carlos Martínez

The following random graph model was introduced for the evolution of protein-protein interaction networks: Let $\mathcal G = (G_n)_{n=n_0, n_0+1,...}$ be a sequence of random graphs, where $G_n = (V_n, E_n)$ is a graph with $|V_n|=n$…

Probability · Mathematics 2024-07-02 Felix Hermann , Peter Pfaffelhuber
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