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Critical phenomena on scale-free networks with a degree distribution $p_k \sim k^{-\lambda}$ exhibit rich finite-size effects due to its structural heterogeneity. We systematically study the finite-size scaling of percolation and identify…

Statistical Mechanics · Physics 2025-08-29 Xuewei Zhao , Liwenying Yang , Dan Peng , Run-Ran Liu , Ming Li

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

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

We provide a simple proof that graphs in a general class of self-similar networks have zero percolation threshold. The considered self-similar networks include random scale-free graphs with given expected node degrees and zero clustering,…

Disordered Systems and Neural Networks · Physics 2011-01-28 M. Angeles Serrano , Dmitri Krioukov , Marian Boguna

Let $G=G(d)$ be a random graph with a given degree sequence $d$, such as a random $r$-regular graph where $r\ge 3$ is fixed and $n=|G|\to\infty$. We study the percolation phase transition on such graphs $G$, i.e., the emergence as $p$…

Probability · Mathematics 2012-03-26 Oliver Riordan

Networks are ubiquitous in diverse real-world systems. Many empirical networks grow as the number of nodes increases with time. Percolation transitions in growing random networks can be of infinite order. However, when the growth of large…

Physics and Society · Physics 2021-04-28 Soo Min Oh , Seung-Woo Son , Byungnam Kahng

A random graph process, $\Gorg[1](n)$, is a sequence of graphs on $n$ vertices which begins with the edgeless graph, and where at each step a single edge is added according to a uniform distribution on the missing edges. It is well known…

Probability · Mathematics 2008-11-26 Gideon Amir , Ori Gurel-Gurevich , Eyal Lubetzky , Amit Singer

Percolation theory is extensively studied in statistical physics and mathematics with applications in diverse fields. However, the research is focused on systems with only one type of links, connectivity links. We review a recently…

Statistical Mechanics · Physics 2015-05-28 Amir Bashan , Shlomo Havlin

We consider the zero-average Gaussian free field on a certain class of finite $d$-regular graphs for fixed $d\geq 3$. This class includes $d$-regular expanders of large girth and typical realisations of random $d$-regular graphs. We show…

Probability · Mathematics 2019-09-05 Angelo Abächerli , Jiří Černý

We consider the zero-average Gaussian free field on a certain class of finite $d$-regular graphs for fixed $d\ge 3$. This class includes $d$-regular expanders of large girth and typical realisations of random $d$-regular graphs. We show…

Probability · Mathematics 2021-10-01 Jiří Černý

We present an analytic formalism describing structural properties of random uncorrelated networks with arbitrary degree distributions. The formalism allows to calculate the main network characteristics like: the position of the phase…

Disordered Systems and Neural Networks · Physics 2016-08-31 Agata Fronczak , Piotr Fronczak , Janusz A. Holyst

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network…

A significant generalization of the Erd\"os-R\'enyi random graph model is an `inhomogeneous' random graph where the edge probabilities vary according to vertex types. We identify the threshold value for this random graph with a finite…

Probability · Mathematics 2024-11-06 Hamin Jung

We introduce a new family of models for growing networks. In these networks new edges are attached preferentially to vertices with higher number of connections, and new vertices are created by already existing ones, inheriting part of their…

Statistical Mechanics · Physics 2009-11-07 S. N. Dorogovtsev , A. N. Samukhin , J. F. F. Mendes

No-exclaves percolation (NExP) is a nonlocal percolation process in which the components are formed not only by the connected occupied nodes but also by the agglomeration of empty nodes completely surrounded by the occupied nodes. It has…

Statistical Mechanics · Physics 2024-05-27 Byungjoon Min , Eun-Kyu Park , Sang-Hwan Gwak , K. -I. Goh

Partially motivated by the desire to better understand the connectivity phase transition in fractal percolation, we introduce and study a class of continuum fractal percolation models in dimension d greater than or equal to 2. These include…

Probability · Mathematics 2010-12-30 Erik I. Broman , Federico Camia

We study the percolation phase transition on preferential attachment models, in which vertices enter with $m$ edges and attach proportionally to their degree plus $\delta$. We identify the critical percolation threshold as…

Probability · Mathematics 2023-12-22 Rajat Subhra Hazra , Remco van der Hofstad , Rounak Ray

The location and nature of the percolation transition in random networks is a subject of intense interest. Recently, a series of graph evolution processes have been introduced that lead to discontinuous percolation transitions where the…

Statistical Mechanics · Physics 2015-06-17 Wei Chen , Xueqi Cheng , Zhiming Zheng , Ning Ning Chung , Raissa M. D'Souza , Jan Nagler

Many networks exhibit scale free behavior where their degree distribution obeys a power law for large vertex degrees. Models constructed to explain this phenomena have relied on preferential attachment where the networks grow by the…

Physics and Society · Physics 2012-02-08 Vijay K Samalam

We introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the…

Disordered Systems and Neural Networks · Physics 2015-05-13 Roni Parshani , Mark Dickison , Reuven Cohen , H. Eugene Stanley , Shlomo Havlin