"Synchronization in complex network topologies"
The study of complex systems pervades all of science, from cell biology to ecology, from computer science to meteorology. A paradigm of a complex system is a network where complexity may come from different sources: topological structure, network evolution, connection and node diversity, and/or dynamical evolution. Examples of networks include food webs, electrical power grids, cellular and metabolic networks, the World-Wide Web, the Internet backbone, neural networks, and co-authorship and citation networks of scientists. These networks consist of nodes which are interconnected by a mesh of links. The macroscopic behavior of a network is determined by both the dynamical rules governing the nodes and the flow occurring along the links. In this paper, we study synchronization properties of networks with regular, random and power-low topologies. We show that random networks are synchronizable.