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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 study the effects of nonreciprocity and network structure on percolation. To this end, we investigate nonreciprocal random networks - directed networks for which the probability of a link occurring from node i to node j differs from the…

Statistical Mechanics · Physics 2025-10-07 Chanania Steinbock

Network dismantling is a relevant research area in network science, gathering attention both from a theoretical and an operational point of view. Here, we propose a general framework for dismantling that prioritizes the removal of nodes…

Physics and Society · Physics 2022-09-29 Federico Musciotto , Salvatore Micciché

After a failure or attack the structure of a complex network changes due to node removal. Here, we show that the degree distribution of the distorted network, under any node disturbances, can be easily computed through a simple formula.…

Data Analysis, Statistics and Probability · Physics 2009-11-13 Bivas Mitra , Niloy Ganguly , Sujoy Ghose , Fernando Peruani

We study the large-deviation properties of minimum spanning trees for two ensembles of random graphs with $N$ nodes. First, we consider complete graphs. Second, we study Erd\H{o}s-R\'{e}nyi (ER) random graphs with edge probability $p=c/N$…

Disordered Systems and Neural Networks · Physics 2025-12-16 Mahdi Sarikhani , Alexander K. Hartmann

Biased (degree-dependent) percolation was recently shown to provide new strategies for turning robust networks fragile and vice versa. Here we present more detailed results for biased edge percolation on scale-free networks. We assume a…

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

We consider propagation models that describe the spreading of an attribute, called "damage", through the nodes of a random network. In some systems, the average fraction of nodes that remain undamaged vanishes in the large system limit, a…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Björn Samuelsson , Joshua E. S. Socolar

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…

Statistical Mechanics · Physics 2009-10-31 D. S. Callaway , M. E. J. Newman , S. H. Strogatz , D. J. Watts

We present analytic and numeric results for percolation in a network formed of interdependent spatially embedded networks. We show results for a treelike and a random regular network of networks each with $(i)$ unconstrained interdependent…

Physics and Society · Physics 2015-06-18 Louis M. Shekhtman , Yehiel Berezin , Michael M. Danziger , Shlomo Havlin

Recently increasing attention has been addressed to the fluctuations observed in percolation defined in single and multiplex networks. These fluctuations are extremely important to characterize the robustness of real finite networks but…

Disordered Systems and Neural Networks · Physics 2019-08-21 Ginestra Bianconi

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

We apply percolation theory to a recently proposed measure of fragmentation $F$ for social networks. The measure $F$ is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after…

Disordered Systems and Neural Networks · Physics 2007-05-23 Yiping Chen , Gerald Paul , Reuven Cohen , Shlomo Havlin , Stephen P. Borgatti , Fredrik Liljeros , H. Eugene Stanley

A central concern of network operators is to estimate the probability of an incident that affects a significant part and thus may yield to a breakdown. We answer this question by modeling how a failure of either a node or an edge will…

Applications · Statistics 2018-02-22 Sandra König

We consider different methods, that do not rely on numerical simulations of the percolation process, to approximate percolation thresholds in networks. We perform a systematic analysis on synthetic graphs and a collection of 109 real…

Physics and Society · Physics 2015-01-16 Filippo Radicchi

Measuring and optimizing the influence of nodes in big-data online social networks are important for many practical applications, such as the viral marketing and the adoption of new products. As the viral spreading on social network is a…

Physics and Society · Physics 2018-07-31 Yanqing Hu , Shenggong Ji , Yuliang Jin , Ling Feng , H. Eugene Stanley , Shlomo Havlin

Can we employ one neural model to efficiently dismantle many complex yet unique networks? This article provides an affirmative answer. Diverse real-world systems can be abstracted as complex networks each consisting of many functional nodes…

Social and Information Networks · Computer Science 2022-08-17 Jiazheng Zhang , Bang Wang

We investigate the statistics of articulation points and bredges (bridge-edges) in complex networks in which bonds are randomly removed in a percolation process. Articulation points are nodes in a network which, if removed, would split the…

Disordered Systems and Neural Networks · Physics 2021-04-07 Haggai Bonneau , Ido Tishby , Ofer Biham , Eytan Katzav , Reimer Kuehn

Almost all network research has been focused on the properties of a single network that does not interact and depends on other networks. In reality, many real-world networks interact with other networks. Here we develop an analytical…

Data Analysis, Statistics and Probability · Physics 2011-11-09 Jianxi Gao , Sergey V. Buldyrev , Shlomo Havlin , H. Eugene Stanley

We consider percolation on interdependent locally treelike networks, recently introduced by Buldyrev et al., Nature 464, 1025 (2010), and demonstrate that the problem can be simplified conceptually by deleting all references to cascades of…

Data Analysis, Statistics and Probability · Physics 2012-01-09 Seung-Woo Son , Golnoosh Bizhani , Claire Christensen , Peter Grassberger , Maya Paczuski
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