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Connectivity correlations play an important role in the structure of scale-free networks. While several empirical studies exist, there is no general theoretical analysis that can explain the largely varying behavior of real networks. Here,…

物理与社会 · 物理学 2009-11-13 Lazaros K. Gallos , Chaoming Song , Hernan A. Makse

The structure of complex networks in previous research has been widely described as scale-free networks generated by the preferential attachment model. However, the preferential attachment model does not take into account the detailed…

无序系统与神经网络 · 物理学 2008-02-26 Nobuhiko Oshida , Sigeo Ihara

Scale-free networks are ubiquitous in social, biological and technological networked systems. Dynamic Scale-free networks and their synchronizations are important to understand and predict the behavior of social, biological and…

社会与信息网络 · 计算机科学 2024-09-16 Rakib Hassan Pran

Many weighted scale-free networks are known to have a power-law correlation between strength and degree of nodes, which, however, has not been well explicated. We investigate the dynamic behaviors of resource/traffic flow on scale-free…

物理与社会 · 物理学 2009-11-11 Qing Ou , Ying-Di Jin , Tao Zhou , Bing-Hong Wang , Bao-Qun Yin

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…

物理与社会 · 物理学 2009-11-13 Lazaros K. Gallos , Panos Argyrakis

In search of many social and economical systems, it is found that node strength distribution as well as degree distribution demonstrate the behavior of power-law with droop-head and heavy-tail. We present a new model for the growth of…

无序系统与神经网络 · 物理学 2007-05-23 Chuan-Ji Fu , Qing Ou , Wen Chen , Bing-Hong Wang , Ying-Di Jin , Yong-Wei Niu , Tao Zhou

Many social, technological, biological, and economical systems are best described by weighted networks, whose properties and dynamics depend not only on their structures but also on the connection weights among their nodes. However, most…

无序系统与神经网络 · 物理学 2015-06-24 Chunguang Li , Guanrong Chen

Many real networks are complex and have power-law vertex degree distribution, short diameter, and high clustering. We analyze the network model based on thresholding of the summed vertex weights, which belongs to the class of networks…

其他凝聚态物理 · 物理学 2007-05-23 Naoki Masuda , Hiroyoshi Miwa , Norio Konno

Scale-free networks with small power law exponent are known to be robust, meaning that their qualitative topological structure cannot be altered by random removal of even a large proportion of nodes. By contrast, it has been argued in the…

概率论 · 数学 2013-08-23 Maren Eckhoff , Peter Mörters

The concept of scale-free networks has been widely applied across natural and physical sciences. Many claims are made about the properties of these networks, even though the concept of scale-free is often vaguely defined. We present tools…

适应与自组织系统 · 物理学 2013-10-18 Kevin Judd , Michael Small , Thomas Stemler

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which…

分子网络 · 定量生物学 2014-11-26 Deok-Sun Lee

Using a simple model with link removals as well as link additions, we show that an evolving network is scale free with a degree exponent in the range of (2, 4]. We then establish a relation between the network evolution and a set of…

数学物理 · 物理学 2007-05-23 Dinghua Shi , Liming Liu , Xiang Zhu , Huijie Zhou , Binbin Wang

It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers.…

物理与社会 · 物理学 2012-10-09 Bojin Zheng , Dan Huang , Deyi Li , Guisheng Chen , Wenfei Lan

Several studies on real complex networks from different fields as biology, economy, or sociology have shown that the degree of nodes (number of edges connected to each node) follows a scale-free power-law distribution like $P(k)\approx…

生物物理 · 物理学 2007-05-23 J. C. Nacher , T. Yamada , S. Goto , M. Kanehisa , T. Akutsu

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

Scale-free power law structure describes complex networks derived from a wide range of real world processes. The extensive literature focuses almost exclusively on networks with power law exponent strictly larger than 2, which can be…

社会与信息网络 · 计算机科学 2015-09-29 Harry Crane , Walter Dempsey

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…

统计力学 · 物理学 2009-10-31 D. S. Callaway , M. E. J. Newman , S. H. Strogatz , D. J. Watts

We present a novel type of weighted scale-free network model, in which the weight grows independently of the attachment of new nodes. The evolution of this network is thus determined not only by the preferential attachment of new nodes to…

无序系统与神经网络 · 物理学 2007-07-24 Takuma Tanaka , Toshio Aoyagi

We introduce a new mechanism of connectivity evolution in networks to account for the emergence of scale-free behavior. The mechanism works on a fixed set of nodes and promotes growth from a minimally connected initial topology by the…

统计力学 · 物理学 2007-05-23 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

Real world complex networks are scale free and possess meso-scale properties like core-periphery and community structure. We study evolution of the core over time in real world networks. This paper proposes evolving models for both…

社会与信息网络 · 计算机科学 2015-12-01 Akrati Saxena , S. R. S. Iyengar