Sergio Gómez

TL;DR: P perturbative analysis is used to reveal analytically the structure of eigenvectors and eigenvalues of the complete network in terms of the spectral properties of the individual layers of the multiplex network, and allows us to understand the physics of diffusionlike processes on top of multiplex networks.

TL;DR: The analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the information awareness to prevent its infection, on top of multiplex networks reveals the phase diagram of the incidence of the epidemics and allows the evolution of the epidemic threshold depending on the topological structure of the multiplex and the inter correlation with the awareness process.

TL;DR: In this paper, a tensorial framework for multilayer complex networks is introduced, and several important network descriptors and dynamical processes such as degree centrality, clustering coefficients, eigenvector centrality and modularity are discussed.

TL;DR: In this article, a tensorial framework for multi-layer networks is introduced, and several important network descriptors and dynamical processes such as degree centrality, clustering coefficients, eigenvector centrality and modularity, Von Neumann entropy, and diffusion are discussed.

TL;DR: In this article, the authors propose a method that allows for multiple resolution screening of the modular structure of real-world complex networks, which is validated using synthetic networks, discovering the predefined structures at all scales.