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Related papers: Gaussian Level-Set Percolation on Complex Networks

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In the random $r$-neighbour bootstrap percolation process on a graph $G$, a set of initially infected vertices is chosen at random by retaining each vertex of $G$ independently with probability $p\in (0,1)$, and "healthy" vertices get…

Combinatorics · Mathematics 2024-06-21 Mihyun Kang , Michael Missethan , Dominik Schmid

We study the locality of critical percolation on finite graphs: let $G_n$ be a sequence of finite graphs, converging locally weakly to a (random, rooted) infinite graph $G$. Consider Bernoulli edge percolation: does the critical probability…

Probability · Mathematics 2022-12-13 Michael Ren , Nike Sun

Using a maximum entropy principle to assign a statistical weight to any graph, we introduce a model of random graphs with arbitrary degree distribution in the framework of standard statistical mechanics. We compute the free energy and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Bauer , D. Bernard

We consider first passage percolation on sparse random graphs with prescribed degree distributions and general independent and identically distributed edge weights assumed to have a density. Assuming that the degree distribution satisfies a…

Probability · Mathematics 2012-10-26 Shankar Bhamidi , Remco van der Hofstad , Gerard Hooghiemstra

A necessary and sufficient condition is established for the strict inequality $p_c(G_*)<p_c(G)$ between the critical probabilities of site percolation on a quasi-transitive, plane graph $G$ and on its matching graph $G_*$. It is assumed…

Probability · Mathematics 2024-02-21 Geoffrey R. Grimmett , Zhongyang Li

Complex networks display various types of percolation transitions. We show that the degree distribution and the degree-degree correlation alone are not sufficient to describe diverse percolation critical phenomena. This suggests that a…

Statistical Mechanics · Physics 2008-11-27 Jae Dong Noh

For massless vertex-transitive transient graphs, the percolation phase transition for the level sets of the Gaussian free field on the associated continuous cable system is particularly well understood, and in particular the associated…

Probability · Mathematics 2023-07-24 Alexis Prévost

We study asymptotic percolation as $N\to \infty$ in an infinite random graph ${\cal G}_N$ embedded in the hierarchical group of order $N$, with connection probabilities depending on an ultrametric distance between vertices. ${\cal G}_N$ is…

Probability · Mathematics 2007-05-23 D. A. Dawson , L. G. Gorostiza

In this article, we first extend the construction of random interlacements, introduced by A.S. Sznitman in [arXiv:0704.2560], to the more general setting of transient weighted graphs. We prove the Harris-FKG inequality for this model and…

Probability · Mathematics 2009-07-03 Augusto Teixeira

We develop techniques to study the phase transition for planar Gaussian percolation models that are not (necessarily) positively correlated. These models lack the property of positive associations (also known as the `FKG inequality'), and…

Probability · Mathematics 2023-07-18 Stephen Muirhead , Alejandro Rivera , Hugo Vanneuville , Laurin Köhler-Schindler

Spatial random graphs capture several important properties of real-world networks. We prove quenched results for the continuum space version of scale-free percolation introduced in [DW18]. This is an undirected inhomogeneous random graph…

Probability · Mathematics 2019-02-18 Joseba Dalmau , Michele Salvi

Communication networks, power grids, and transportation networks are all examples of networks whose performance depends on reliable connectivity of their underlying network components even in the presence of usual network dynamics due to…

Physics and Society · Physics 2020-06-26 Arman Mohseni-Kabir , Mihir Pant , Don Towsley , Saikat Guha , Ananthram Swami

In $H$-percolation, we start with an Erd\H{o}s--R\'enyi graph ${\mathcal G}_{n,p}$ and then iteratively add edges that complete copies of $H$. The process percolates if all edges missing from ${\mathcal G}_{n,p}$ are eventually added. We…

Combinatorics · Mathematics 2025-11-18 Zsolt Bartha , Brett Kolesnik , Gal Kronenberg

Percolation is a model for random damage to a network. It is one of the simplest models that displays a phase transition: when the network is severely damaged, it falls apart in many small connected components, while if the damage is light,…

Probability · Mathematics 2025-12-18 Remco van der Hofstad

We consider the bond percolation problem on a transient weighted graph induced by the excursion sets of the Gaussian free field on the corresponding cable system. Owing to the continuity of this setup and the strong Markov property of the…

Probability · Mathematics 2023-03-21 Alexander Drewitz , Alexis Prévost , Pierre-François Rodriguez

Methods for determining the percolation threshold usually study the behavior of network ensembles and are often restricted to a particular type of probabilistic node/link removal strategy. We propose a network-specific method to determine…

Disordered Systems and Neural Networks · Physics 2015-05-30 Dane Taylor , Juan G. Restrepo

We consider upper level-sets of the Gaussian free field on $\mathbb Z^d$, for $d\geq 3$, above a given real-valued height parameter $h$. As $h$ varies, this defines a canonical percolation model with strong, algebraically decaying…

Probability · Mathematics 2024-06-26 Hugo Duminil-Copin , Subhajit Goswami , Pierre-François Rodriguez , Franco Severo

We define an inhomogeneous percolation model on "ladder graphs" obtained as direct products of an arbitrary graph $G = (V,E)$ and the set of integers $\mathbb{Z}$ (vertices are thought of as having a "vertical" component indexed by an…

Probability · Mathematics 2019-03-19 Réka Szabó , Daniel Valesin

We study first passage percolation on the configuration model. Assuming that each edge has an independent exponentially distributed edge weight, we derive explicit distributional asymptotics for the minimum weight between two randomly…

Probability · Mathematics 2010-11-10 Shankar Bhamidi , Remco van der Hofstad , Gerard Hooghiemstra

We present a novel probabilistic approach for generating multi-fidelity data while accounting for errors inherent in both low- and high-fidelity data. In this approach a graph Laplacian constructed from the low-fidelity data is used to…

Machine Learning · Computer Science 2025-12-01 Orazio Pinti , Jeremy M. Budd , Franca Hoffmann , Assad A. Oberai