Physics – Data Analysis – Statistics and Probability
Scientific paper
2011-10-25
Physics
Data Analysis, Statistics and Probability
7 pages, 6 figures
Scientific paper
In the past decade, synchronization on complex networks has attracted increasing attentions from various research disciplines. Most previous works, however, focus only on the dynamic behaviors of synchronization process in the stable region, i.e., global synchronization. In this letter, we demonstrate that synchronization process on complex networks can efficiently reveal the substructures of networks when the coupling strength of chaotic oscillators is under the lower boundary of stable region. Both analytic and numerical results show that the nodes belonging to the same component in the hierarchical network are tightly clustered according to the Euclidean distances between the state vectors of the corresponding oscillators, and different levels of hierarchy can be systematically unfolded by gradually tuning the coupling strength. When the coupling strengths exceed the upper boundary of stable region, the hierarchy of the network cannot be recognized by this approach. Extensive simulations suggest that our method may provide a powerful tool to detect the hierarchical community structure of complex systems and deep insight into the relationship between structure and dynamics of complex systems.
Cai Shimin
Fu Zhongqian
Zhang Jie
Zhuo Zhao
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