How heterogeneity in connections and cycles matter for synchronization of complex networks

We analyze how the structure of complex networks of non-identical oscillators influences synchronization in the context of the Kuramoto model. The complex network metrics assortativity and clustering coefficient are used in order to generate network topologies of Erdos-Renyi, Watts-Strogatz, and Barabasi-Albert types that present high, intermediate, and low values of these metrics. We also employ the total dissonance metric for neighborhood similarity, which generalizes to networks the standard concept of dissonance between two non-identical coupled oscillators. Based on this quantifier and using an optimization algorithm, we generate Similar, Dissimilar, and Neutral natural frequency patterns, which correspond to small, large, and intermediate values of total dissonance, respectively. The emergency of synchronization is numerically studied by considering these three types of dissonance patterns along with the network topologies generated by high, intermediate, and low values of the metrics assortativity and clustering coefficient. We find that, in general, low values of these metrics appear to favor phase locking, especially for the Similar dissonance pattern.

Automated summary

The study examines how the structure of complex networks of non-identical oscillators affects synchronization in the Kuramoto model, using network metrics assortativity and clustering coefficient. Different types of network topologies are generated using Erdos-Renyi, Watts-Strogatz, and Barabasi-Albert models with high, intermediate, and low values of these metrics. The results show that low values of these metrics tend to favor phase locking, especially for Similar dissonance pattern.