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What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is…

Statistical Mechanics · Physics 2007-05-23 Gang Yan , Tao Zhou , Ying-Di Jin , Zhong-Qian Fu

The Barab\'{a}si-Albert (BA) model is extended to include the concept of local world and the microscopic event of adding edges. With probability $p$, we add a new node with $m$ edges which preferentially link to the nodes presented in the…

Disordered Systems and Neural Networks · Physics 2009-11-11 Bing Wang , Huanwen Tang , Zhongzhi Zhang , Zhilong Xiu

A network is formed using the $N$ sites of an one-dimensional lattice in the shape of a ring as nodes and each node with the initial degree $k_{in}=2$. $N$ links are then introduced to this network, each link starts from a distinct node,…

Statistical Mechanics · Physics 2009-11-07 G. Mukherjee , S. S. Manna

Ever since the Barab\'{a}si-Albert (BA) scale-free network has been proposed, network modeling has been studied intensively in light of the network growth and the preferential attachment (PA). However, numerous real systems are featured…

Social and Information Networks · Computer Science 2025-11-25 Yuhan Li , Minyu Feng , Jürgen Kurths

We study the detailed mechanism of the failure of scale-free networks under intentional attacks. Although it is generally accepted that such networks are very sensitive to targeted attacks, we show that for a particular type of structure…

Physics and Society · Physics 2009-11-13 Lazaros K. Gallos , Panos Argyrakis

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the…

Social and Information Networks · Computer Science 2026-04-02 Yichao Yao , Minyu Feng , Matjaž Perc , Jürgen Kurths

We develop and test a rewiring method (originally proposed by Newman) which allows to build random networks having pre-assigned degree distribution and two-point correlations. For the case of scale-free degree distributions, we discretize…

Physics and Society · Physics 2019-09-26 M. L. Bertotti , G. Modanese

It is commonly believed that real networks are scale-free and fraction of nodes $P(k)$ with degree $k$ satisfies the power law $P(k) \propto k^{-\gamma} \text{ for } k > k_{min} > 0$. Preferential attachment is the mechanism that has been…

Data Structures and Algorithms · Computer Science 2023-06-22 Raheel Anwar , Muhammad Irfan Yousuf , Muhammad Abid

Recently there have been a tremendous interest in models of networks with a power-law distribution of degree -- so called "scale-free networks." It has been observed that such networks, normally, have extremely short path-lengths, scaling…

Disordered Systems and Neural Networks · Physics 2007-05-23 Petter Holme

In this letter, we proposed an ungrowing scale-free network model, wherein the total number of nodes is fixed and the evolution of network structure is driven by a rewiring process only. In spite of the idiographic form of $G$, by using a…

Statistical Mechanics · Physics 2015-06-25 Yan-Bo Xie , Tao Zhou , Bing-Hong Wang

The sampling of scale-free networks in Molecular Biology is usually achieved by growing networks from a seed using recursive algorithms with elementary moves which include the addition and deletion of nodes and bonds. These algorithms…

Physics and Society · Physics 2018-02-07 S Konini , EJ Janse van Rensburg

In this paper we describe the emergence of scale-free degree distributions from statistical mechanics principles. We define an energy associated to a degree sequence as the logarithm of the number of indistinguishable simple networks it is…

Statistical Mechanics · Physics 2007-05-23 Ginestra Bianconi

A majority of studied models for scale-free networks have degree distributions with exponents greater than $2$. Real networks, however, can demonstrate essentially more heavy-tailed degree distributions. We explore two models of scale-free…

Physics and Society · Physics 2016-12-14 Gábor Timár , Sergey N. Dorogovtsev , José Fernando F. Mendes

We show how scale-free degree distributions can emerge naturally from growing networks by using random walks for selecting vertices for attachment. This result holds for several variants of the walk algorithm and for a wide range of…

Statistical Mechanics · Physics 2007-05-23 T. S. Evans , J. P. Saramaki

The average node-to-node distance of scale-free graphs depends logarithmically on N, the number of nodes, while the probability distribution function (pdf) of the distances may take various forms. Here we analyze these by considering…

Statistical Mechanics · Physics 2009-11-07 Gabor Szabo , Mikko Alava , Janos Kertesz

Through the distinction between ``real'' and ``virtual'' links between the nodes of a graph, we develop a set of simple rules leading to scale-free networks with a tunable degree distribution exponent. Albeit sharing some similarities with…

Statistical Mechanics · Physics 2007-05-23 F. Stauffer

We introduce the link-space formalism for analyzing network models with degree-degree correlations. The formalism is based on a statistical description of the fraction of links l_{i,j} connecting nodes of degrees i and j. To demonstrate its…

Physics and Society · Physics 2009-10-08 David M. D. Smith , Chiu Fan Lee , Jukka-Pekka Onnela , Neil F. Johnson

In their recent work "Scale-free networks are rare", Broido and Clauset address the problem of the analysis of degree distributions in networks to classify them as scale-free at different strengths of "scale-freeness." Over the last two…

Physics and Society · Physics 2020-04-01 Pim van der Hoorn , Ivan Voitalov , Remco van der Hofstad , Dmitri Krioukov

In random graph models, the degree distribution of an individual node should be distinguished from the (empirical) degree distribution of the graph that records the fractions of nodes with given degree. We introduce a general framework to…

Social and Information Networks · Computer Science 2018-11-14 Siddharth Pal , Armand M. Makowski

We study Erd\"{o}s-R\'enyi random graphs with random weights associated with each link. We generate a new ``Supernode network'' by merging all nodes connected by links having weights below the percolation threshold (percolation clusters)…

Disordered Systems and Neural Networks · Physics 2015-06-25 Tomer Kalisky , Sameet Sreenivasan , Lidia A. Braunstein , Sergey V. Buldyrev , Shlomo Havlin , H. Eugene Stanley