Litcius/Paper detail

Controlling Symmetries and Clustered Dynamics of Complex Networks

Lucia Valentina Gambuzza, Mattia Frasca, Francesco Sorrentino, Louis M. Pecora, Stefano Boccaletti

2020IEEE Transactions on Network Science and Engineering28 citationsDOI

Abstract

Symmetries are an essential feature of complex networks as they regulate how the graph collective dynamics organizes into clustered states. We here show how to control network symmetries, and how to enforce patterned states of synchronization with nodes clustered in a desired way. Our approach consists of perturbing the original network connectivity, either by adding new edges or by adding/removing links together with modifying their weights. By solving suitable optimization problems, we guarantee that changes made on the existing topology are minimal. The conditions for the stability of the enforced pattern are derived for the general case, and the performance of the method is illustrated with paradigmatic examples. Our results are relevant to all the practical situations in which coordination of the networked systems into diverse groups may be desirable, such as for teams of robots, unmanned autonomous vehicles, power grids and central pattern generators.

Topics & Concepts

Synchronization (alternating current)Computer scienceTopology (electrical circuits)Homogeneous spaceComplex networkDistributed computingNetwork topologyGraphStability (learning theory)RobotTheoretical computer scienceMathematicsArtificial intelligenceComputer networkGeometryMachine learningCombinatoricsWorld Wide WebNonlinear Dynamics and Pattern FormationNeural Networks Stability and SynchronizationNeural dynamics and brain function