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Related papers: Bootstrap percolation on geometric inhomogeneous r…

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Graph bootstrap percolation is a simple cellular automaton introduced by Bollob\'as in 1968. Given a graph $H$ and a set $G \subseteq E(K_n)$ we initially "infect" all edges in $G$ and then, in consecutive steps, we infect every $e \in K_n$…

Combinatorics · Mathematics 2017-06-28 Béla Bollobás , Michał Przykucki , Oliver Riordan , Julian Sahasrabudhe

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

In this paper, we study the trajectory of a classic SIR epidemic on a family of dynamic random graphs of fixed size, whose set of edges continuously evolves over time. We set general infection and recovery times, and start the epidemic from…

Probability · Mathematics 2025-01-17 Marta Milewska , Remco van der Hofstad , Bert Zwart

In \emph{$k$-bootstrap percolation}, we fix $p\in (0,1)$, an integer $k$, and a plane graph $G$. Initially, we infect each face of $G$ independently with probability $p$. Infected faces remain infected forever, and if a healthy (uninfected)…

Combinatorics · Mathematics 2019-11-18 Neal Bushaw , Daniel W. Cranston

Consider a discrete locally finite subset $\Gamma$ of $R^d$ and the complete graph $(\Gamma,E)$, with vertices $\Gamma$ and edges $E$. We consider Gibbs measures on the set of sub-graphs with vertices $\Gamma$ and edges $E'\subset E$. The…

Probability · Mathematics 2010-09-17 Pablo A. Ferrari , Eugene A. Pechersky , Valentin V. Sisko , Anatoly A. Yambartsev

In this paper we study the threshold model of \emph{geometric inhomogeneous random graphs} (GIRGs); a generative random graph model that is closely related to \emph{hyperbolic random graphs} (HRGs). These models have been observed to…

Discrete Mathematics · Computer Science 2023-06-19 Thomas Bläsius , Tobias Friedrich , Maximilian Katzmann , Janosch Ruff , Ziena Zeif

We consider bootstrap percolation on uncorrelated complex networks. We obtain the phase diagram for this process with respect to two parameters: $f$, the fraction of vertices initially activated, and $p$, the fraction of undamaged vertices…

Statistical Mechanics · Physics 2015-03-13 G J Baxter , S N Dorogovtsev , A V Goltsev , J F F Mendes

We consider the fractal Sierpi\'{n}ski gasket or carpet graph in dimension $d\geq 2,$ denoted by $G$. At time $0$, we place a Poisson point process of particles onto the graph and let them perform independent simple random walks, which in…

Probability · Mathematics 2024-07-23 Alexander Drewitz , Gioele Gallo , Peter Gracar

Detecting the dimensionality of graphs is a central topic in machine learning. While the problem has been tackled empirically as well as theoretically, existing methods have several drawbacks. On the one hand, empirical tools are…

Social and Information Networks · Computer Science 2024-08-16 Tobias Friedrich , Andreas Göbel , Maximilian Katzmann , Leon Schiller

We study two competing growth models. Each of these models describes the spread of a finite number of infections on a graph. Each infection evolves like an (oriented or unoriented) first passage percolation process except that once a vertex…

Probability · Mathematics 2007-10-25 Jean-Baptiste Gouéré

The problem of continuum percolation in dispersions of rods is reformulated in terms of weighted random geometric graphs. Nodes (or sites or vertices) in the graph represent spatial locations occupied by the centers of the rods. The…

Statistical Mechanics · Physics 2015-09-30 Avik P. Chatterjee , Claudio Grimaldi

\emph{Full-bond percolation} with parameter $p$ is the process in which, given a graph, for every edge independently, we delete the edge with probability $1-p$. Bond percolation is motivated by problems in mathematical physics and it is…

Probability · Mathematics 2022-05-23 Luca Becchetti , Andrea Clementi , Francesco Pasquale , Luca Trevisan , Isabella Ziccardi

We introduce a very general model of an inhomogenous random graph with independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p=c/n scaling for G(n,p)…

Probability · Mathematics 2011-11-10 Bela Bollobas , Svante Janson , Oliver Riordan

In this work, a novel model of the random geometric graph (RGG), namely the isotropic random geometric graph (IRGG) has been developed and its topological properties in two dimensions have been studied in details. The defining…

Physics and Society · Physics 2021-08-12 Dipa Saha , Sayantan Mitra , Bishnu Bhowmik , Ankur Sensharma

We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes, depending on the graph size N. Large metric graphs are…

Statistical Mechanics · Physics 2010-07-26 T. Tlusty , J. -P. Eckmann

We study a simple model of epidemics where an infected node transmits the infection to its neighbors independently with probability $p$. This is also known as the independent cascade or Susceptible-Infected-Recovered (SIR) model with fixed…

Data Structures and Algorithms · Computer Science 2021-10-19 Yeganeh Alimohammadi , Christian Borgs , Amin Saberi

We propose an interdependent random geometric graph (RGG) model for interdependent networks. Based on this model, we study the robustness of two interdependent spatially embedded networks where interdependence exists between geographically…

Social and Information Networks · Computer Science 2018-06-08 Jianan Zhang , Edmund Yeh , Eytan Modiano

We address the question of understanding the effect of the underlying network topology on the spread of a virus and the dissemination of information when users are mobile performing independent random walks on a graph. To this end we…

Probability · Mathematics 2008-10-20 M. Draief , A. Ganesh

A simple random walk on a graph is a sequence of movements from one vertex to another where at each step an edge is chosen uniformly at random from the set of edges incident on the current vertex, and then transitioned to next vertex.…

Probability · Mathematics 2012-02-28 Mohammed Abdullah

We study the mixing time of random graphs in the $d$-dimensional toric unit cube $[0,1]^d$ generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a…

Probability · Mathematics 2011-09-21 Andrew Beveridge , Milan Bradonjić
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