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The functionality of nodes in a network is often described by the structural feature of belonging to the giant component. However, when dealing with problems like transport, a more appropriate functionality criterion is for a node to belong…

物理与社会 · 物理学 2021-02-03 Bnaya Gross , Ivan Bonamassa , Shlomo Havlin

Percolation is a fundamental concept that brought new understanding on the robustness properties of complex systems. Here we consider percolation on weakly interacting networks, that is, network layers coupled together by much less…

物理与社会 · 物理学 2019-04-10 Giacomo Rapisardi , Alex Arenas , Guido Caldarelli , Giulio Cimini

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…

We investigate topologically biased failure in scale-free networks with degree distribution $P(k) \propto k^{-\gamma}$. The probability $p$ that an edge remains intact is assumed to depend on the degree $k$ of adjacent nodes $i$ and $j$…

无序系统与神经网络 · 物理学 2009-11-13 Andre A. Moreira , Jose S. Andrade , Hans J. Herrmann , Joseph O. Indekeu

Communication networks, power grids, and transportation networks are all examples of networks whose performance depends on reliable connectivity of their underlying network components even in the presence of usual network dynamics due to…

物理与社会 · 物理学 2020-06-26 Arman Mohseni-Kabir , Mihir Pant , Don Towsley , Saikat Guha , Ananthram Swami

A model of interdependent networks of networks (NoN) has been introduced recently in the context of brain activation to identify the neural collective influencers in the brain NoN. Here we develop a new approach to derive an exact…

神经元与认知 · 定量生物学 2017-07-05 Kevin Roth , Flaviano Morone , Byungjoon Min , Hernán A. Makse

It is often claimed that the entropy of a network's degree distribution is a proxy for its robustness. Here, we clarify the link between degree distribution entropy and giant component robustness to node removal by showing that the former…

物理与社会 · 物理学 2022-09-12 Chris Jones , Karoline Wiesner

The study of network robustness focuses on the way the overall functionality of a network is affected as some of its constituent parts fail. Failures can occur at random or be part of an intentional attack and, in general, networks behave…

物理与社会 · 物理学 2020-01-29 Nahuel Almeira , Orlando Vito Billoni , Juan Ignacio Perotti

The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease…

定量方法 · 定量生物学 2009-05-14 Joel C Miller

We study the distribution $P(\sigma)$ of the equivalent conductance $\sigma$ for Erd\H{o}s-R\'enyi (ER) and scale-free (SF) weighted resistor networks with $N$ nodes. Each link has conductance $g\equiv e^{-ax}$, where $x$ is a random number…

We investigate the growth of connectivity in a network. In our model, starting with a set of disjoint nodes, links are added sequentially. Each link connects two nodes, and the connection rate governing this random process is proportional…

统计力学 · 物理学 2012-02-16 E. Ben-Naim , P. L. Krapivsky

The stability of networks is greatly influenced by their degree distributions and in particular by their broadness. Networks with broader degree distributions are usually more robust to random failures but less robust to localized attacks.…

物理与社会 · 物理学 2015-09-23 Xin Yuan , Shuai Shao , H. Eugene Stanley , Shlomo Havlin

Many real-world networks are embedded in space, and their resilience in the presence of reinforced nodes has not been studied. Here we model such networks using a spatial network model that have an exponential distribution of link length…

物理与社会 · 物理学 2023-06-21 Nir Vaturi , Bnaya Gross , Shlomo Havlin

The random graph of Erdos and Renyi is one of the oldest and best studied models of a network, and possesses the considerable advantage of being exactly solvable for many of its average properties. However, as a model of real-world networks…

统计力学 · 物理学 2007-05-23 M. E. J. Newman

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

The robustness of complex networks against node failure and malicious attack has been of interest for decades, while most of the research has focused on random attack or hub-targeted attack. In many real-world scenarios, however, attacks…

物理与社会 · 物理学 2015-06-23 Shuai Shao , Xuqing Huang , H Eugene Stanley , Shlomo Havlin

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…

统计力学 · 物理学 2025-10-07 Chanania Steinbock

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase…

无序系统与神经网络 · 物理学 2013-01-22 Bernard Sonnenschein , Francesc Sagués , Lutz Schimansky-Geier

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.…

数据分析、统计与概率 · 物理学 2009-11-13 Bivas Mitra , Niloy Ganguly , Sujoy Ghose , Fernando Peruani

We present analytical results for the structural evolution of random networks undergoing contraction processes via generic node deletion scenarios, namely, random deletion, preferential deletion and propagating deletion. Focusing on…

物理与社会 · 物理学 2020-09-10 I. Tishby , O. Biham , E. Katzav