Design of Oscillator Networks with Enhanced Synchronization Tolerance against Noise
arXiv:1109.6731 · doi:10.1103/PhysRevE.85.056206
Abstract
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.
9 pages, 8 figures
References in corpus (9)
- Synchronization in complex networks
- Network Synchronization, Diffusion, and the Paradox of Heterogeneity
- Noise-Induced Synchronization and Clustering in Ensembles of Uncoupled Limit-Cycle Oscillators
- Synchronization in scale-free network with asymmetric coupling
- Synchronization transition in scale-free networks: Clusters of synchrony
- Probing rare physical trajectories with Lyapunov weighted dynamics
- Structure of Cell Networks Critically Determines Oscillation Regularity
- Computation of the Kolmogorov-Sinai entropy using statistitical mechanics: Application of an exchange Monte Carlo method
- Exploration of Order in Chaos with Replica Exchange Monte Carlo
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