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The degree distributions of many real world networks follow power-laws whose exponents tend to fall between two and three. Within the framework of the Barabasi-Albert model (BA model), we explain this empirical observation by a simple fact.…

Physics and Society · Physics 2009-05-19 Shinji Tanimoto

The connectivity of individual neurons of large neural networks determine both the steady state activity of the network and its answer to external stimulus. Highly diluted random networks have zero activity. We show that increasing the…

Condensed Matter · Physics 2008-02-03 Albert-László Barabási

The parallel computational complexity or depth of growing network models is investigated. The networks considered are generated by preferential attachment rules where the probability of attaching a new node to an existing node is given by a…

Statistical Mechanics · Physics 2009-11-10 Benjamin Machta , Jonthan Machta

In network evolution, the effect of aging is universal: in scientific collaboration network, scientists have a finite time span of being active; in movie actors network, once popular stars are retiring from stage; devices on the Internet…

Statistical Mechanics · Physics 2009-11-10 Han Zhu , Xin-Ran Wang , Jian-Yang Zhu

The evolution of complex networks is governed by both growing rules and internal properties. Most evolving network models (e.g. preferential attachment) emphasize on the growing strategy, while neglecting the characteristics of individual…

Social and Information Networks · Computer Science 2020-05-07 Dong Chen , Hong Yu

This article addresses the degree distribution of subnetworks, namely the number of links between the nodes in each subnetwork and the remainder of the structure (cond-mat/0408076). The transformation from a subnetwork-partitioned model to…

Disordered Systems and Neural Networks · Physics 2007-05-23 Luciano da Fontoura Costa

A model of distribution of the wealth in a society based on the properties of complex networks has been proposed. The wealth is interpreted as a consequence of communication possibilities and proportional to the number of connections…

Physics and Society · Physics 2010-10-12 D. Lande , A. Snarskii , M. Zhenirovskyy

We derive a analytic evolution equation for overlap parameters including the effect of degree distribution on the transient dynamics of sequence processing neural networks. In the special case of globally coupled networks, the precisely…

Disordered Systems and Neural Networks · Physics 2008-01-31 Yong Chen , Pan Zhang , Lianchun Yu , Shengli Zhang

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [Tadi\'c, Physica A {\bf 293},…

Statistical Mechanics · Physics 2009-11-07 Bosiljka Tadic

Epidemics on complex networks is a widely investigated topic in the last few years, mainly due to the last pandemic events. Usually, real contact networks are dynamic, hence much effort has been invested in studying epidemics on evolving…

Physics and Society · Physics 2022-05-18 Hillel Sanhedrai , Shlomo Havlin

We propose a novel network measure of topological invariants, called small-worldness, for identifying topological phase transitions of quantum and classical spin models. Small-worldness is usually defined in the study of social networks…

Statistical Mechanics · Physics 2014-05-09 Chung-Pin Chou , Ming-Chiang Chung

Using probabilistic approach, the transient dynamics of sparsely connected Hopfield neural networks is studied for arbitrary degree distributions. A recursive scheme is developed to determine the time evolution of overlap parameters. As…

Disordered Systems and Neural Networks · Physics 2011-11-09 Pan Zhang , Yong Chen

We study the combined effects of aging and links removal on epidemic dynamics in the Barab\'{a}si-Albert scale-free networks. The epidemic is described by a susceptible-infected-refractory (SIR) model. The aging effect of a node introduced…

Disordered Systems and Neural Networks · Physics 2009-11-10 K. P. Chan , Dafang Zheng , P. M. Hui

Critical phenomena can show unusual phase diagrams when defined in complex network topologies. The case of classical phase transitions such as the classical Ising model and the percolation transition has been studied extensively in the last…

Disordered Systems and Neural Networks · Physics 2015-06-04 Arda Halu , Luca Ferretti , Alessandro Vezzani , Ginestra Bianconi

We study the evolution of a social network with friendly/enmity connections into a balanced state by introducing a dynamical model with an intrinsic randomness, similar to Glauber dynamics in statistical mechanics. We include the…

Physics and Society · Physics 2019-08-14 Rana Shojaei , Pouya Manshour , Afshin Montakhab

As in an earlier paper we start from the hypothesis that physics on the Planck scale should be described by means of concepts taken from ``discrete mathematics''. This goal is realized by developing a scheme being based on the dynamical…

High Energy Physics - Theory · Physics 2016-09-06 Manfred Requardt

This paper presents an approach to the modeling of degree-degree correlation in complex networks. Thus, a simple function, \Delta(k', k), describing specific degree-to- degree correlations is considered. The function is well suited to…

Physics and Society · Physics 2015-06-17 Alfonso Niño , Camelia Muñoz-Caro

The "power of choice" has been shown to radically alter the behavior of a number of randomized algorithms. Here we explore the effects of choice on models of tree and network growth. In our models each new node has k randomly chosen…

Statistical Mechanics · Physics 2009-11-13 Raissa M. D'Souza , Paul L. Krapivsky , Cristopher Moore

We propose a growing model which interpolates between one-dimensional regular lattice and small-world networks. The model undergoes an interesting phase transition from large to small world. We investigate the structural properties by both…

Statistical Mechanics · Physics 2007-09-24 Zhongzhi Zhang , Shuigeng Zhou , Zhen Shen

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