"Emergence of cluster synchronization in networks with symmetries"

Francesco Sorrentino, Department of Mechanical Engineering, University of New Mexico

Synchronization is of central importance in power distribution, telecommunication, neuronal and biological networks. Many networks are observed to produce patterns of synchronized clusters, but it has been difficult to predict these clusters or understand the conditions under which they form. We present a new framework and develop techniques for the analysis of network dynamics that shows the connection between network symmetries and cluster formation. The connection between symmetries and cluster synchronization is experimentally confirmed in the context of real networks with heterogeneities and noise using an electrooptic network. We experimentally observe and theoretically predict a surprising phenomenon in which some clusters lose synchrony without disturbing the others. Our analysis shows that such behavior will occur in a wide variety of networks and node dynamics. The results could guide the design of new power grid systems or lead to new understanding of the dynamical behavior of networks ranging from neural to social.

Francesco Sorrentino received a master's degree in Industrial Engineering from the University of Naples Federico II (Italy) in 2003 and a Ph.D. in Control Engineering from the University of Naples Federico II (Italy) in 2007. His expertise is in dynamical systems and controls, with particular emphasis on nonlinear dynamics and adaptive decentralized control. His work includes studies on dynamics and control of complex dynamical networks and hypernetworks, adaptation in complex systems, sensor adaptive networks, coordinated autonomous vehicles operating in a dynamically changing environment, and identification of nonlinear systems. He is interested in applying the theory of dynamical systems to model, analyze, and control the dynamics of complex distributed energy systems, such as power networks and smart grids. Subjects of current investigation are evolutionary game theory on networks (evolutionary graph theory), the dynamics of large networks of coupled neurons, and the use of adaptive techniques for dynamical identification of communication delays between coupled mobile platforms. He has published more than thirty papers in international scientific peer-reviewed journals. Dr. Sorrentino's research is funded by the National Science Foundation.

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