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k-core percolation is an extension of the concept of classical percolation and is particularly relevant to understand the resilience of complex networks under random damage. A new analytical formalism has been recently proposed to deal with…

无序系统与神经网络 · 物理学 2012-09-19 Davide Cellai , Aonghus Lawlor , Kenneth A. Dawson , James P. Gleeson

K-core percolation is a fundamental dynamical process in complex networks with applications that span numerous real-world systems. Earlier studies focus primarily on random networks without spatial constraints and reveal intriguing…

物理与社会 · 物理学 2024-07-12 Leyang Xue , Shengling Gao , Lazaros K. Gallos , Orr Levy , Bnaya Gross , Zengru Di , Shlomo Havlin

$k$-Core percolation has served as a paradigmatic model of discontinuous percolation for a long time. Recently it was revealed that the order parameter of $k$-core percolation of random networks additionally exhibits critical behavior. Thus…

统计力学 · 物理学 2016-12-21 Deokjae Lee , Minjae Jo , B. Kahng

$k$-core percolation is a percolation model which gives a notion of network functionality and has many applications in network science. In analysing the resilience of a network under random damage, an extension of this model is introduced,…

无序系统与神经网络 · 物理学 2013-02-22 Davide Cellai , Aonghus Lawlor , Kenneth A. Dawson , James P. Gleeson

The $k$-core percolation is a fundamental structural transition in complex networks. Through the analysis of the size jump behaviors of $k$-core in the evolution process of networks, we confirm that $k$-core percolation is continuous phase…

统计力学 · 物理学 2017-10-10 Yong Zhu , Xiaosong Chen

Cascading failures in complex systems have been studied extensively using two different models: $k$-core percolation and interdependent networks. We combine the two models into a general model, solve it analytically and validate our…

物理与社会 · 物理学 2017-10-04 Nagendra K. Panduranga , Jianxi Gao , Xin Yuan , H. Eugene Stanley , Shlomo Havlin

We develop the theory of the k-core (bootstrap) percolation on uncorrelated random networks with arbitrary degree distributions. We show that the k-core percolation is an unusual, hybrid phase transition with a jump emergence of the k-core…

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

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…

统计力学 · 物理学 2025-08-29 Xuewei Zhao , Liwenying Yang , Dan Peng , Run-Ran Liu , Ming Li

We propose a statistical model defined on the three-dimensional diamond network where the splitting of randomly selected nodes leads to a spatially disordered network, with decreasing degree of connectivity. The terminal state, that is…

无序系统与神经网络 · 物理学 2013-10-16 Susan Nachtrab , Matthias J. F. Hoffmann , Sebastian C. Kapfer , Gerd E. Schroeder-Turk , Klaus Mecke

Many real-world networks are coupled together to maintain their normal functions. Here we study the robustness of multiplex networks with interdependent and interconnected links under k-core percolation, where a node fails when it connects…

物理与社会 · 物理学 2021-05-26 Kexian Zheng , Ying Liu , Yang Wang , Wei Wang

Dependency links in single-layer networks offer a convenient way of modeling nonlocal percolation effects in networked systems where certain pairs of nodes are only able to function together. We study the percolation properties of the weak…

统计力学 · 物理学 2021-03-16 Gábor Timár , György Kovács , José Fernando F. Mendes

The use of machine learning techniques in classical and quantum systems has led to novel techniques to classify ordered and disordered phases, as well as uncover transition points in critical phenomena. Efforts to extend these methods to…

物理与社会 · 物理学 2023-10-10 Sayat Mimar , Gourab Ghoshal

The notion of k-clique percolation in random graphs is introduced, where k is the size of the complete subgraphs whose large scale organizations are analytically and numerically investigated. For the Erdos-Renyi graph of N vertices we…

无序系统与神经网络 · 物理学 2007-05-23 Imre Derenyi , Gergely Palla , Tamas Vicsek

We perform large-scale numerical simulations to investigate the critical behavior of $k$-core percolation in two dimensions with an extended interaction range $r$. By systematically varying both the core index $k$ and the interaction range…

统计力学 · 物理学 2026-05-26 Qiyuan Shi , Ming Li , Youjin Deng

We generalize the theory of k-core percolation on complex networks to k-core percolation on multiplex networks, where k=(k_a, k_b, ...). Multiplex networks can be defined as networks with a set of vertices but different types of edges, a,…

无序系统与神经网络 · 物理学 2014-10-08 N. Azimi-Tafreshi , J. Gomez-Gardenes , S. N. Dorogovtsev

Weak multiplex percolation generalizes percolation to multi-layer networks, represented as networks with a common set of nodes linked by multiple types (colors) of edges. We report a novel discontinuous phase transition in this problem.…

物理与社会 · 物理学 2022-03-15 R. A. da Costa , G. J. Baxter , S. N. Dorogovtsev , J. F. F. Mendes

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

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 introduce the heterogeneous-$k$-core, which generalizes the $k$-core, and contrast it with bootstrap percolation. Vertices have a threshold $k_i$ which may be different at each vertex. If a vertex has less than $k_i$ neighbors it is…

统计力学 · 物理学 2011-07-04 G. J. Baxter , S. N. Dorogovtsev , A. V. Goltsev , J. F. F. Mendes

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…

概率论 · 数学 2008-04-11 Svante Janson
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