期刊
PHYSICAL REVIEW E
卷 83, 期 3, 页码 -出版社
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.83.036112
关键词
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资金
- Science Foundation Ireland [06/IN.1/I366, MACSI06/MI/005]
- James S. McDonnell Foundation [220020177]
- National Science Foundation (NSF) [DMS-0645369]
- Science Foundation Ireland (SFI) [06/IN.1/I366] Funding Source: Science Foundation Ireland (SFI)
We demonstrate that a tree-based theory for various dynamical processes operating on static, undirected networks yields extremely accurate results for several networks with high levels of clustering. We find that such a theory works well as long as the mean intervertex distance l is sufficiently small-that is, as long as it is close to the value of l in a random network with negligible clustering and the same degree-degree correlations. We support this hypothesis numerically using both real-world networks from various domains and several classes of synthetic clustered networks. We present analytical calculations that further support our claim that tree-based theories can be accurate for clustered networks, provided that the networks are sufficiently small worlds.
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