The decrease of the spectral radius, an important characterizer of network dynamics, by
removing links is investigated. The minimization of the spectral radius by removing m links is …

Determining the effect of structural perturbations on the eigenvalue spectra of networks is an
important problem because the spectra characterize not only their topological structures, but …

Dynamics on networks are often characterized by the second smallest eigenvalue of the
Laplacian matrix of the network, which is called the spectral gap. Examples include the …

The largest eigenvalue of the adjacency matrix of networks is a key quantity determining
several important dynamical processes on complex networks. Based on this fact, we present …

The largest eigenvalue of the adjacency matrix of a network plays an important role in
several network processes (eg, synchronization of oscillators, percolation on directed …

Newman's measure for (dis) assortativity, the linear degree correlation coefficient ρ_D, is
reformulated in terms of the total number N k of walks in the graph with k hops. This …

Many natural and social systems develop complex networks that are usually modeled as
random graphs. The eigenvalue spectrum of these graphs provides information about their …

We propose a general approach to the description of spectra of complex networks. For the
spectra of networks with uncorrelated vertices (and a local treelike structure), exact …

We study the spectra and eigenvectors of the adjacency matrices of scale-free networks
when bidirectional interaction is allowed, so that the adjacency matrix is real and symmetric …

The largest eigenvalue of a network's adjacency matrix and its associated principal
eigenvector are key elements for determining the topological structure and the properties of …