Network evolution towards optimal dynamical performance

Abstract

Understanding the mutual interdependence between the behavior of dynamical processes on networks and the underlying topologies promises new insight for a large class of empirical networks. We present a generic approach to investigate this relationship which is applicable to a wide class of dynamics, namely to evolve networks using a performance measure based on the whole spectrum of the dynamics' time evolution operator. As an example, we consider the graph Laplacian describing diffusion processes, and we evolve the network structure such that a given sub-diffusive behavior emerges.

5 pages, 4 figures

References in corpus (10)

• Synchronization in complex networks
• Adaptive Coevolutionary Networks: A Review
• Scaling theory of transport in complex networks
• Laplacian spectra of complex networks and random walks on them: Are scale-free architectures really important?
• Network synchronization: Spectral versus statistical properties
• Efficient Rewirings for Enhancing Synchronizability of Dynamical Networks
• Bounding network spectra for network design
• Network synchronization: Optimal and Pessimal Scale-Free Topologies
• Reliability of genetic networks is evolvable
• Dynamics-Driven Evolution to Structural Heterogeneity in Complex Networks