Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2011-09-30
Nonlinear Sciences
Adaptation and Self-Organizing Systems
9 pages, 8 figures
Scientific paper
Can synchronization properties of a network of identical oscillators in the presence of noise be improved through appropriate rewiring of its connections? What are the optimal network architectures for a given total number of connections? We address these questions by running the optimization process, using the stochastic Markov Chain Monte Carlo method with replica exchange, to design the networks of phase oscillators with the increased tolerance against noise. As we find, the synchronization of a network, characterized by the Kuramoto order parameter, can be increased up to 40 %, as compared to that of the randomly generated networks, when the optimization is applied. Large ensembles of optimized networks are obtained and their statistical properties are investigated.
Mikhailov Alexander S.
Yanagita Tatsuo
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