Evolving enhanced topologies for the synchronization of dynamical complex networks

Phys Rev E Stat Nonlin Soft Matter Phys. 2010 May;81(5 Pt 2):056212. doi: 10.1103/PhysRevE.81.056212. Epub 2010 May 21.

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.