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题名: Activity patterns on random scale-free networks: global dynamics arising from local majority rules
作者: Zhou, Haijun ;  Lipowsky, Reinhard
刊名: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
出版日期: 2007
期号: 1, 页码:-
关键词: FERROMAGNETIC ISING-MODEL ;  COMPLEX NETWORKS ;  STABILITY ;  EVOLUTION ;  INTERNET
学科分类: Physics
通讯作者: Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China
部门归属: Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China; Max Planck Inst Colloids & Interfaces, D-14424 Potsdam, Germany
英文摘要: Activity or spin patterns on a random scale-free network are studied using mean field analysis and computer simulations. These activity patterns evolve in time according to local majority rule dynamics which is implemented using (i) parallel or synchronous updating and (ii) random sequential or asynchronous updating. Our mean field calculations predict that the relaxation processes of disordered activity patterns become much more effcient as the scaling exponent. of the scale-free degree distribution changes from gamma > 5/2 to gamma < 5/2. For. > 5/2, the corresponding decay times increase as ln(N) with increasing network size N whereas they are independent of N for. < 5/2. In order to check these mean field predictions, extensive simulations of the pattern dynamics have been performed using two different ensembles of random scale-free networks: (A) multi-networks as generated by the configuration method, which typically leads to many self-connections and multiple edges, and (B) simple networks without self-connections and multiple edges. We find that the mean field predictions are confirmed (i) for random sequential updating of multi-networks and (ii) for both parallel and random sequential updating of simple networks with gamma = 2.25 and 2.6. For gamma = 2.4, the data for the simple networks seem to be consistent with mean field theory as well, whereas we cannot draw a definite conclusion from the simulation data for the multi-networks. The latter diffculty can be understood in terms of an effective scaling exponent gamma(eff) = gamma(eff) (gamma, N) for multi-networks. This effective exponent is determined by removing all self-connections and multiple edges; it satisfies gamma(eff) = gamma and decreases towards gamma with increasing network size N. For gamma = 2.4, we find gamma(eff) greater than or similar to 5/2 up to N = 2(17).
收录类别: SCI
原文出处: 查看原文
WOS记录号: WOS:000243969300013
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/5811
Appears in Collections:理论物理所1978-2010年知识产出_期刊论文

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Zhou, Haijun,Lipowsky, Reinhard. Activity patterns on random scale-free networks: global dynamics arising from local majority rules[J]. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT,2007(1):-.
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