title: Evolutionary reconstruction of networks.
abstract: Can a graph specifying the pattern of connections of a dynamical network be reconstructed from statistical properties of a signal generated by such a system? In this model study, we present a Metropolis algorithm for reconstruction of graphs from their Laplacian spectra. Through a stochastic process of mutations and selection, evolving test networks converge to a reference graph. Applying the method to several examples of random graphs, clustered graphs, and small-world networks, we show that the proposed stochastic evolution allows exact reconstruction of relatively small networks and yields good approximations in the case of large sizes.
authors.affiliation: Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany. mpi@osc.kiku.dk
authors.forename: Mads
authors.initials: M
authors.lastname: Ipsen
authors.forename: Alexander S
authors.initials: AS
authors.lastname: Mikhailov