Activity patterns on random scale-free networks: global dynamics arising from local majority rules
文献类型：期刊论文
| 作者 | Lipowsky, Reinhard; Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China; Zhou, Haijun
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| 刊名 | JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
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| 出版日期 | 2007 |
| 期号 | 1页码:- |
| 关键词 | Ferromagnetic Ising-model Complex Networks Stability Evolution Internet |
| ISSN号 | 1742-5468 |
| 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). |
| 学科主题 | Physics |
| URL标识 | 查看原文 |
| WOS记录号 | WOS:000243969300013 |
| 公开日期 | 2012-08-02 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/5811]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 通讯作者 | Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lipowsky, Reinhard,Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China,Zhou, Haijun. 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 | Lipowsky, Reinhard,Zhou, HJ , Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China,&Zhou, Haijun.(2007).Activity patterns on random scale-free networks: global dynamics arising from local majority rules.JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT(1),-. |
| MLA | Lipowsky, Reinhard,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):-. |
入库方式： OAI收割
来源：理论物理研究所
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