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The structure of many real networks is not locally tree-like and hence, network analysis fails to characterise their bond percolation properties. In a recent paper [P. Mann, V. A. Smith, J. B. O. Mitchell, and S. Dobson, Percolation in…

物理与社会 · 物理学 2021-01-27 Peter Mann , V. Anne Smith , John B. O. Mitchell , Simon Dobson

We consider bond percolation on random graphs with given degrees and bounded average degree. In particular, we consider the order of the largest component after the random deletion of the edges of such a random graph. We give a rough…

组合数学 · 数学 2022-01-12 Nikolaos Fountoulakis , Felix Joos , Guillem Perarnau

Recent work on the internet, social networks, and the power grid has addressed the resilience of these networks to either random or targeted deletion of network nodes. Such deletions include, for example, the failure of internet routers or…

统计力学 · 物理学 2009-10-31 D. S. Callaway , M. E. J. Newman , S. H. Strogatz , D. J. Watts

Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, social and biological networks are often characterized by degree-degree {dependencies} between neighbouring nodes. One of the problems with the…

概率论 · 数学 2014-02-03 Nelly Litvak , Remco van der Hofstad

We study connected graphs with a fixed degree sequence, in the sparse setting where the number of edges grows linearly in the number of vertices. Using the relation to the configuration model, we identify the number of such connected graphs…

组合数学 · 数学 2026-05-11 Sasha Bell , Serte Donderwinkel , Remco van der Hofstad

Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree. Conversely, in biological and technological networks, high-degree nodes tend to be…

离散数学 · 计算机科学 2015-09-30 Kevin E. Bassler , Charo I. Del Genio , Péter L. Erdős , István Miklós , Zoltán Toroczkai

We reconsider the problem of percolation on an equilibrium random network with degree-degree correlations between nearest-neighboring vertices focusing on critical singularities at a percolation threshold. We obtain criteria for…

统计力学 · 物理学 2009-11-13 A. V. Goltsev , S. N. Dorogovtsev , J. F. F. Mendes

Correlations may affect propagation processes on complex networks. To analyze their effect, it is useful to build ensembles of networks constrained to have a given value of a structural measure, such as the degree-degree correlation $r$,…

统计力学 · 物理学 2013-04-09 Marlon Ramos , Celia Anteneodo

As a fundamental structural transition in complex networks, core percolation is related to a wide range of important problems. Yet, previous theoretical studies of core percolation have been focusing on the classical Erd\H{o}s-R\'enyi…

统计力学 · 物理学 2013-01-01 Yang-Yu Liu , Endre Csóka , Haijun Zhou , Márton Pósfai

We study the properties of the giant connected component in random graphs with arbitrary degree distribution. We concentrate on the degree-degree correlations. We show that the adjoining nodes in the giant connected component are correlated…

统计力学 · 物理学 2010-05-11 Piotr Bialas , Andrzej K. Oleś

We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module and the inter-module connections are defined by the joint degree-degree distribution of nodes for each pair of modules.…

物理与社会 · 物理学 2014-04-18 Sergey Melnik , Mason A. Porter , Peter J. Mucha , James P. Gleeson

Random graphs have played an instrumental role in modelling real-world networks arising from the internet topology, social networks, or even protein-interaction networks within cells. Percolation, on the other hand, has been the fundamental…

概率论 · 数学 2018-09-12 Souvik Dhara

In this paper, we study the order of the largest connected component of a random graph having two sources of randomness: first, the graph is chosen randomly from all graphs with a given degree sequence, and then bond percolation is applied.…

概率论 · 数学 2024-02-20 Lyuben Lichev , Dieter Mitsche , Guillem Perarnau

We study site and bond percolation on directed simple random graphs with a given degree distribution and derive the expressions for the critical value of the percolation probability above which the giant strongly connected component emerges…

组合数学 · 数学 2021-03-08 Femke van Ieperen , Ivan Kryven

Random networks are widely used to model complex networks and research their properties. In order to get a good approximation of complex networks encountered in various disciplines of science, the ability to tune various statistical…

无序系统与神经网络 · 物理学 2009-11-13 Andreas Pusch , Sebastian Weber , Markus Porto

Spreading of either information or matter can often be treated as a network problem. It can be of great importance to be able to estimate the likelihood that spreading through a network reaches essentially the entire network while still not…

无序系统与神经网络 · 物理学 2009-03-09 Tomas Alarcon , Henrik Jeldtoft Jensen

In this study, we investigate bond percolation in networks that have the Poisson degree distribution and a nearest-neighbor degree-degree correlation. Previous numerical studies on percolation critical behaviors of degree-correlated…

物理与社会 · 物理学 2022-03-14 Shogo Mizutaka , Takehisa Hasegawa

Although most of the real networks contain a mixture of directed and bidirectional (reciprocal) connections, the reciprocity $r$ has received little attention as a subject of theoretical understanding. We study the expected reciprocity of…

The existence or not of a percolation threshold on power law correlated graphs is a fundamental question for which a general criterion is lacking. In this work we investigate the problems of site and bond percolation on graphs with degree…

无序系统与神经网络 · 物理学 2009-11-07 Alexei Vazquez , Yamir Moreno

Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof…

物理与社会 · 物理学 2015-09-03 Ju Xiang , Ke Hu , Tao Hu , Yan Zhang , Jian-Ming Li
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