期刊
CHAOS
卷 21, 期 2, 页码 -出版社
AIP Publishing
DOI: 10.1063/1.3602223
关键词
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资金
- U.S. National Science Foundation [DMS-0709212, DMS-1057128]
- Academy of Finland [139514]
- Academy of Finland (AKA) [139514, 139514] Funding Source: Academy of Finland (AKA)
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1057128] Funding Source: National Science Foundation
Network modeling based on ensemble averages tacitly assumes that the networks meant to be modeled are typical in the ensemble. Previous research on network eigenvalues, which govern a range of dynamical phenomena, has shown that this is indeed the case for uncorrelated networks with minimum degree >= 3. Here, we focus on real networks, which generally have both structural correlations and low-degree nodes. We show that: (i) the ensemble distribution of the dynamically most important eigenvalues can be not only broad and far apart from the real eigenvalue but also highly structured, often with a multimodal rather than a bell-shaped form; (ii) these interesting properties are found to be due to low-degree nodes, mainly those with degree <= 3, and network communities, which is a common form of structural correlation found in real networks. In addition to having implications for ensemble-based approaches, this shows that low-degree nodes may have a stronger influence on collective dynamics than previously anticipated from the study of computer-generated networks. (C) 2011 American Institute of Physics. [doi:10.1063/1.3602223]
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