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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 establish the conditions under which several algorithmically exploitable structural features hold for random intersection graphs, a natural model for many real-world networks where edges correspond to shared attributes. Specifically, we…

Social and Information Networks · Computer Science 2017-02-10 Matthew Farrell , Timothy Goodrich , Nathan Lemons , Felix Reidl , Fernando Sánchez Villaamil , Blair D. Sullivan

For a unimodular random graph $(G,\rho)$, we consider deformations of its intrinsic path metric by a (random) weighting of its vertices. This leads to the notion of the conformal growth exponent of $(G,\rho)$, which is the best asymptotic…

Probability · Mathematics 2020-06-02 James R. Lee

A growing random graph is constructed by successively sampling without replacement an element from the pool of virtual vertices and edges. At start of the process the pool contains $N$ virtual vertices and no edges. Each time a vertex is…

Probability · Mathematics 2024-02-29 Michael Farber , Alexander Gnedin , Wajid Mannan

We develop a quantitative large deviations theory for random hypergraphs, which rests on tensor decomposition and counting lemmas under a novel family of cut-type norms. As our main application, we obtain sharp asymptotics for joint upper…

Probability · Mathematics 2023-05-10 Nicholas A. Cook , Amir Dembo , Huy Tuan Pham

Baxter permutations, plane bipolar orientations, and a specific family of walks in the non-negative quadrant are well-known to be related to each other through several bijections. We introduce a further new family of discrete objects,…

Probability · Mathematics 2020-06-15 Jacopo Borga , Mickaël Maazoun

We propose an approach to calculate the critical percolation threshold for finite-sized Erdos-Renyi digraphs using minimal Hamiltonian cycles. We obtain an analytically exact result, valid non-asymptotically for all graph sizes, which…

Statistical Mechanics · Physics 2014-05-12 Michelle Rudolph-Lilith , Lyle E. Muller

We establish scaling limits for the random walk whose state space is the range of a simple random walk on the four-dimensional integer lattice. These concern the asymptotic behaviour of the graph distance from the origin and the spatial…

Probability · Mathematics 2021-12-08 David A. Croydon , Daisuke Shiraishi

This paper is inspired by the problem of understanding in a mathematical sense the Liouville quantum gravity on surfaces. Here we show how to define a stationary random metric on self-similar spaces which are the limit of nice finite…

Probability · Mathematics 2015-09-15 Mikhail Khristoforov , Victor Kleptsyn , Michele Triestino

We investigate symmetric edge polytopes generated by Erd\H{o}s--R\'enyi random graphs in a high-dimensional regime. These objects provide a natural and largely unexplored model of random lattice polytopes, in which geometric properties are…

Combinatorics · Mathematics 2026-03-12 Torben Donzelmann , Martina Juhnke , Benedikt Rednoß , Christoph Thäle

Random walkers absorbing on a boundary sample the Harmonic Measure linearly and independently: we discuss how the recurrence times between impacts enable non-linear moments of the measure to be estimated. From this we derive a new technique…

Statistical Mechanics · Physics 2007-05-23 Ellak Somfai , Nicholas R. Goold , Robin C. Ball , Jason P. DeVita , Leonard M. Sander

In recent work on equiangular lines, Jiang, Tidor, Yuan, Zhang, and Zhao showed that a connected bounded degree graph has sublinear second eigenvalue multiplicity. More generally they show that there cannot be too many eigenvalues near the…

Probability · Mathematics 2024-01-17 Mikolaj Fraczyk , Ben Hayes , Madhu Sudan , Yufei Zhao

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

We prove a large deviation principle for a greedy exploration process on an Erd\"os-R\'enyi (ER) graph when the number of nodes goes to infinity. To prove our main result, we use the general strategy to study large deviations of processes…

Probability · Mathematics 2021-10-11 P. Bermolen , V. Goicoechea , M. Jonckheere , E. Mordecki

Counting small subgraphs, referred to as motifs, in large graphs is a fundamental task in graph analysis, extensively studied across various contexts and computational models. In the sublinear-time regime, the relaxed problem of approximate…

Data Structures and Algorithms · Computer Science 2025-03-14 Talya Eden , Reut Levi , Dana Ron , Ronitt Rubinfeld

Recently, variants of many classical extremal theorems have been proved in the random environment. We, complementing existing results, extend the Erd\H{o}s-Gallai Theorem in random graphs. In particular, we determine, up to a constant…

Combinatorics · Mathematics 2020-01-15 József Balogh , Andrzej Dudek , Lina Li

Random walk on changing graphs is considered. For sequences of finite graphs increasing monotonically towards a limiting infinite graph, we establish transition probability upper bounds. It yields sufficient transience criteria for simple…

Probability · Mathematics 2018-10-09 Ruojun Huang

We study the random geometry of first passage percolation on the complete graph equipped with independent and identically distributed edge weights, continuing the program initiated by Bhamidi and van der Hofstad [6]. We describe our results…

Probability · Mathematics 2015-12-23 M. Eckhoff , J. Goodman , R. van der Hofstad , F. R. Nardi

We consider the problem of high-dimensional Gaussian graphical model selection. We identify a set of graphs for which an efficient estimation algorithm exists, and this algorithm is based on thresholding of empirical conditional…

Machine Learning · Computer Science 2012-03-06 Animashree Anandkumar , Vincent Y. F. Tan , Alan. S. Willsky

In this dissertation we demonstrate that the continuous-time quantum walk models remain powerful for nontrivial graph structures. We consider two aspects of this problem. First, it is known that the standard Continuous-Time Quantum Walk…

Quantum Physics · Physics 2021-09-28 Adam Glos