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Zhou, Haijun; Lipowsky, Reinhard; Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China
Activity patterns on random scale-free networks: global dynamics arising from local majority rules
Source PublicationJOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
KeywordFerromagnetic Ising-model Complex Networks Stability Evolution Internet
AbstractActivity 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).
2007
ISSN1742-5468
Issue1Pages:-
Subject AreaPhysics
Indexed BySCI
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Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/5811
Collection理论物理所科研产出_SCI论文
Corresponding AuthorZhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Haijun,Lipowsky, Reinhard,Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China. Activity patterns on random scale-free networks: global dynamics arising from local majority rules[J]. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT,2007(1):-.
APA Zhou, Haijun,Lipowsky, Reinhard,&Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China.(2007).Activity patterns on random scale-free networks: global dynamics arising from local majority rules.JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT(1),-.
MLA Zhou, Haijun,et al."Activity patterns on random scale-free networks: global dynamics arising from local majority rules".JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT .1(2007):-.
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