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We prove limit theorems for random walks with $n$ steps in the $d$-dimensional Euclidean space as both $n$ and $d$ tend to infinity. One of our results states that the path of such a random walk, viewed as a compact subset of the…

Probability · Mathematics 2023-05-23 Zakhar Kabluchko , Alexander Marynych

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

Nested graphs have been used in different applications, for example to represent knowledge in semantic networks. On the other hand, graphs with cycles are really important in surface reconstruction, periodic schedule and network analysis.…

Combinatorics · Mathematics 2018-11-08 María Carrasco , Zenaida Castillo , Nerio Borges , Ramón Pino Pérez

The motion of pedestrians is subject to a wide range of influences and exhibits a rich phenomenology. To enable precise measurement of the density and velocity we use an alternative definition using Voronoi diagrams which exhibits smaller…

Small-world graphs, which combine randomized and structured elements, are seen as prevalent in nature. Jon Kleinberg showed that in some graphs of this type it is possible to route, or navigate, between vertices in few steps even with very…

Probability · Mathematics 2008-11-18 Oskar Sandberg

Landscapes that are rhythmically dissected by natural drainage channels exist in various geologic and climatic settings. Such landscapes are characterized by a length-scale for the lateral spacing between channels. We observe a small-scale…

Pattern Formation and Solitons · Physics 2009-11-10 Norbert Schorghofer , Bill Jensen , Arshad Kudrolli , Daniel H. Rothman

This work analyses the practice of sister city pairing. We investigate structural properties of the resulting city and country networks and present rankings of the most central nodes in these networks. We identify different country clusters…

Social and Information Networks · Computer Science 2013-02-27 Andreas Kaltenbrunner , Pablo Aragón , David Laniado , Yana Volkovich

We survey recent results on some one- and two-dimensional patterns generated by random permutations of natural numbers. In the first part, we discuss properties of random walks, evolving on a one-dimensional regular lattice in discrete time…

Statistical Mechanics · Physics 2009-11-11 G. Oshanin , R. Voituriez , S. Nechaev , O. Vasilyev , F. Hivert

Any symmetric affinity function $w: V\times V \to \mathbb{R}_+$ defined on a discrete set $V$ induces Euclidean space structure on $V$. In particular, an undirected graph specified by an affinity (or adjacency) matrix can be considered as a…

Mathematical Physics · Physics 2008-04-29 Ph. Blanchard , D. Volchenkov

The Wigner spacing distribution has a long and illustrious history in nuclear physics and in the quantum mechanics of classically chaotic systems. In this paper, a novel connection between the Wigner distribution and 2D classical mechanics…

Chaotic Dynamics · Physics 2017-08-03 Jamal Sakhr

In the randomly-oriented Manhattan lattice, every line in $\mathbb{Z}^d$ is assigned a uniform random direction. We consider the directed graph whose vertex set is $\mathbb{Z}^d$ and whose edges connect nearest neighbours, but only in the…

Probability · Mathematics 2018-02-13 Sean Ledger , Bálint Tóth , Benedek Valkó

One usually thinks of a cat moving from one room to another in an apartment as random walk model. Imagine now that it also has the possibility to go from one apartment to another by crossing some corridors. That yields a new probabilistic…

Combinatorics · Mathematics 2020-08-06 Hery Randriamaro

In the context of a random walk on an undirected graph, Kemeny's constant can measure the average travel time for a random walk between two randomly chosen vertices. We are interested in graphs that behave counter-intuitively in regard to…

Combinatorics · Mathematics 2022-05-18 Sooyeong Kim

We identify a relationship between a certain family of random walks on Euclidean lattices and difference matrices over cyclic groups. We then use the techniques of Fourier analysis to estimate the return probabilities of these random walks,…

Combinatorics · Mathematics 2017-06-06 Aaron M Montgomery

Community structures have been identified in various complex real-world networks, for example, communication, information, internet and shareholder networks. The scaling of community size distribution indicates the heterogeneity in the…

Physics and Society · Physics 2022-07-11 Qing Yao , Bingsheng Chen , Tim S. Evans , Kim Christensen

The random walk process underlies the description of a large number of real world phenomena. Here we provide the study of random walk processes in time varying networks in the regime of time-scale mixing; i.e. when the network connectivity…

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

Random networks are increasingly used to analyse complex transportation networks, such as airline routes, roads and rail networks. So far, this research has been focused on describing the properties of the networks with the help of random…

Physics and Society · Physics 2017-09-19 Jürgen Hackl , Bryan T. Adey

The stationary isotropic Poisson line process was used to derive upper bounds on mean excess network geodesic length in Aldous and Kendall [Adv. in Appl. Probab. 40 (2008) 1-21]. The current paper presents a study of the geometry and…

Probability · Mathematics 2012-11-08 Wilfrid S. Kendall

Several state-of-the-art neural graph embedding methods are based on short random walks (stochastic processes) because of their ease of computation, simplicity in capturing complex local graph properties, scalability, and interpretibility.…

Machine Learning · Computer Science 2020-07-30 Charu Sharma , Jatin Chauhan , Manohar Kaul