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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

We study fully synchronized states in scale-free networks of chaotic logistic maps as a function of both dynamical and topological parameters. Three different network topologies are considered: (i) random scale-free topology, (ii)…

无序系统与神经网络 · 物理学 2009-11-10 Pedro G. Lind , Jason A. C. Gallas , Hans J. Herrmann

The structure of the network has great impact on its traffic dynamics. Most of the real world networks follow the heterogeneous structure and exhibit scale-free feature. In scale-free network, a new node prefers to connect with hub nodes…

网络与互联网体系结构 · 计算机科学 2019-01-17 Suchi Kumari , Abhishek Saroha , Anurag Singh

Scale-free networks are abundant in nature and society, describing such diverse systems as the world wide web, the web of human sexual contacts, or the chemical network of a cell. All models used to generate a scale-free topology are…

统计力学 · 物理学 2009-11-07 Albert-Laszlo Barabasi , Erzsebet Ravasz , Tamas Vicsek

In this paper, firstly, we study analytically the topological features of a family of hierarchical lattices (HLs) from the view point of complex networks. We derive some basic properties of HLs controlled by a parameter $q$. Our results…

统计力学 · 物理学 2007-05-23 Zhongzhi Zhang , Shuigeng Zhou , Tao Zou

We propose a deterministic weighted scale-free small-world model for considering pseudofractal web with the coevolution of topology and weight. In the model, we have the degree distribution exponent $\gamma$ restricted to a range between 2…

统计力学 · 物理学 2011-02-03 Yichao Zhang , Zhongzhi Zhang , Shuigeng Zhou , Jihong Guan

Synchronization is critical for system level behaviour in physical, chemical, biological and social systems. Empirical evidence has shown that the network topology strongly impacts the synchronizablity of the system, and the analysis of…

社会与信息网络 · 计算机科学 2021-11-24 Mengbang Zou , Weisi Guo

By employing a recently introduced optimization algorithm we explicitely design optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree…

无序系统与神经网络 · 物理学 2009-11-13 Luca Donetti , Pablo I. Hurtado , Miguel A. Munoz

Recently, it has been demonstrated that many large complex networks display a scale-free feature, that is, their connectivity distributions have the power-law form. In this paper, we investigate the synchronization phenomena in a scale-free…

凝聚态物理 · 物理学 2007-05-23 Xiao Fan Wang , Guanrong Chen

With complex networks emerging as an effective tool to tackle multidisciplinary problems, models of network generation have gained an importance of their own. These models allow us to extensively analyze the data obtained from real-world…

物理与社会 · 物理学 2018-09-05 G. Kashyap , G. Ambika

It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and they are also scale-free (the degrees are distributed according to a power…

社会与信息网络 · 计算机科学 2016-05-25 L. Barrière , F. Comellas , C. Dalfó , M. A. Fiol

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the…

无序系统与神经网络 · 物理学 2009-09-29 Xiang Li

Random scale-free overlay topologies provide a number of properties like for example high resilience against failures of random nodes, small (average) diameter as well as good expansion and congestion characteristics that make them…

网络与互联网体系结构 · 计算机科学 2013-07-16 Ingo Scholtes

We give exact relations for certain types of the hierarchic fractal structures. In the blatant distinction from regular networks of the "small world" (SW) topology [1], regular fractal networks manifests the logarithmic dependence of the…

无序系统与神经网络 · 物理学 2007-05-23 Gregory Surdutovich , Vladimir Gol'dshtein , Gennady Koganov

Many complex natural and physical systems exhibit patterns of interconnection that conform, approximately, to a network structure referred to as scale-free. Preferential attachment is one of many algorithms that have been introduced to…

物理与社会 · 物理学 2014-11-18 Linjun Zhang , Michael Small , Kevin Judd

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

统计力学 · 物理学 2007-05-23 M. Baiesi , S. S. Manna

To provide a phenomenological theory for the various interesting transitions in restructuring networks we employ a statistical mechanical approach with detailed balance satisfied for the transitions between topological states. This enables…

统计力学 · 物理学 2007-05-23 Imre Derenyi , Illes Farkas , Gergely Palla , Tamas Vicsek

Systems with lattice geometry can be renormalized exploiting their coordinates in metric space, which naturally define the coarse-grained nodes. By contrast, complex networks defy the usual techniques, due to their small-world character and…

物理与社会 · 物理学 2023-11-07 Elena Garuccio , Margherita Lalli , Diego Garlaschelli

The geometric renormalization technique for complex networks has successfully revealed the multiscale self-similarity of real network topologies and can be applied to generate replicas at different length scales. In this letter, we extend…

物理与社会 · 物理学 2023-07-04 Muhua Zheng , Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical…

物理与社会 · 物理学 2011-11-09 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan , Lujun Fang , Yichao Zhang
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