title: Evolving enhanced topologies for the synchronization of dynamical complex networks.
abstract: Enhancing the synchronization of dynamical networks is of great interest to those designing and analyzing many man-made and natural systems. In this work, we investigate how network topology can be evolved to improve this property through the rewiring of edges. A computational tool called NETEVO performs this task using a simulated annealing metaheuristic. In contrast to other work which considers topological attributes when assessing current performance, we instead take a dynamical approach using simulated output from the system to direct the evolution of the network. Resultant topologies are analyzed using standard network measures, B matrices, and motif distributions. These uncover the convergence of many similar features for all our networks, highlighting also significant differences between those evolved using topological rather than dynamical performance measures.
authors.affiliation: Bristol Centre for Complexity Sciences, Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, United Kingdom.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Gorochowski
authors.forename: Mario
authors.initials: M
authors.lastname: di Bernardo
authors.forename: Claire S
authors.initials: CS
authors.lastname: Grierson