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Bootstrap percolation is a process that is used to model the spread of an infection on a given graph. In the model considered here each vertex is equipped with an individual threshold. As soon as the number of infected neighbors exceeds…

Probability · Mathematics 2022-10-25 Nils Detering , Thilo Meyer-Brandis , Konstantinos Panagiotou

In complex networks the degrees of adjacent nodes may often appear dependent -- which presents a modelling challenge. We present a working framework for studying networks with an arbitrary joint distribution for the degrees of adjacent…

Combinatorics · Mathematics 2020-08-25 Samuel , G. Balogh , Gergely Palla , Ivan Kryven

In this paper, we study a model of long-range site percolation on graphs of bounded degree, namely the Boolean percolation model. In this model, each vertex of an infinite connected graph is the center of a ball of random radius, and…

Probability · Mathematics 2025-11-25 Corentin Faipeur

We extend previous work of max-linear models on finite directed acyclic graphs to infinite graphs as well as random graphs, and investigate their relations to classical percolation theory, more particularly the impact of Bernoulli bond…

Probability · Mathematics 2022-06-27 Claudia Klüppelberg , Ercan Sönmez

We examine the heterogeneous responses of individual nodes in sparse networks to the random removal of a fraction of edges. Using the message-passing formulation of percolation, we discover considerable variation across the network in the…

Statistical Mechanics · Physics 2017-09-13 Reimer Kuehn , Tim Rogers

We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model and, by performing percolation processes, we get information about topology and resilience properties of the networks…

Statistical Mechanics · Physics 2015-05-30 Elena Agliari , Claudia Cioli , Enore Guadagnini

Many complex networks in nature have directed links, a property that affects the network's navigability and large-scale topology. Here we study the percolation properties of such directed scale-free networks with correlated in- and…

Disordered Systems and Neural Networks · Physics 2009-11-07 N. Schwartz , R. Cohen , D. ben-Avraham , A. -L. Barabasi , S. Havlin

We consider a class of scale-free inhomogeneous random graphs, which includes some long-range percolation models. We study the maximum degree in such graphs in a growing observation window and show that its limiting distribution is Frechet.…

Probability · Mathematics 2021-06-18 Chinmoy Bhattacharjee , Matthias Schulte

There is proposed a model of scale-free random graphs which are locally close to the uncorrelated complex random networks with divergent $\langle k^2 \rangle$ studied in e.g. S. N. Dorogovtsev {\it et al}, Rev. Mod. Phys. {\bf 80}, 1275…

Mathematical Physics · Physics 2011-09-22 Yuri Kozitsky

Geometric inhomogeneous random graphs (GIRGs) are a model for scale-free networks with underlying geometry. We study bootstrap percolation on these graphs, which is a process modelling the spread of an infection of vertices starting within…

Probability · Mathematics 2020-09-02 Christoph Koch , Johannes Lengler

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

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

The margins within the geographic range of species are often specific in terms of ecological and evolutionary processes, and can strongly influence the species' reaction to climate change. One of the frequently observed features at range…

Populations and Evolution · Quantitative Biology 2020-02-28 R. Juhász , B. Oborny

Real-life networks often encounter vertex dysfunctions, which are usually followed by recoveries after appropriate maintenances. In this paper we present our research on a model of scale-free networks whose vertices are regularly removed…

Physics and Society · Physics 2013-10-08 Linjun Li , Xiangwen Wang

We present an exact mathematical framework able to describe site-percolation transitions in real multiplex networks. Specifically, we consider the average percolation diagram valid over an infinite number of random configurations where…

Physics and Society · Physics 2016-12-21 Ginestra Bianconi , Filippo Radicchi

We study the random graph obtained by random deletion of vertices or edges from a random graph with given vertex degrees. A simple trick of exploding vertices instead of deleting them, enables us to derive results from known results for…

Probability · Mathematics 2008-04-11 Svante Janson

Many real-world networks exhibit the so-called small-world phenomenon: their typical distances are much smaller than their sizes. One mathematical model for this phenomenon is a long-range percolation graph on a $d$-dimensional box $\{0, 1,…

Probability · Mathematics 2022-11-30 Tianqi Wu

Percolation is perhaps the simplest example of a process exhibiting a phase transition and one of the most studied phenomena in statistical physics. The percolation transition is continuous if sites/bonds are occupied independently with the…

Statistical Mechanics · Physics 2015-05-27 Santo Fortunato , Filippo Radicchi

Dynamical processes taking place on networks have received much attention in recent years, especially on various models of random graphs (including small world and scale free networks). They model a variety of phenomena, including the…

Probability · Mathematics 2007-05-23 Jonathan Rowe , Boris Mitavskiy

Percolation is an important topic in climate, physics, materials science, epidemiology, finance, and so on. Prediction of percolation thresholds with machine learning methods remains challenging. In this paper, we build a powerful graph…

Statistical Mechanics · Physics 2023-04-10 Hua Tian , Lirong Zhang , Youjin Deng , Wanzhou Zhang