Bounding robustness in complex networks under topological changes through majorization techniques

Gian Paolo Clemente, Alessandra Cornaro

Risultato della ricerca: Contributo in rivistaArticolo in rivista

Abstract

Measuring robustness is a fundamental task for analysing the structure of complex networks. Indeed, several approaches to capture the robustness properties of a network have been proposed. In this paper we focus on spectral graph theory where robustness is measured by means of a graph invariant called Kirchhoff index, expressed in terms of eigenvalues of the Laplacian matrix associated to a graph. This graph metric is highly informative as a robustness indicator for several real-world networks that can be modeled as graphs. We discuss a methodology aimed at obtaining some new and tighter bounds of this graph invariant when links are added or removed. We take advantage of real analysis techniques, based on majorization theory and optimization of functions which preserve the majorization order. Applications to simulated graphs and to empirical networks generated by collecting assets of the S&P 100 show the effectiveness of our bounds, also in providing meaningful insights with respect to the results obtained in the literature.
Lingua originaleEnglish
pagine (da-a)1-13
Numero di pagine13
RivistaEUROPEAN PHYSICAL JOURNAL. B, CONDENSED MATTER AND COMPLEX SYSTEMS
DOI
Stato di pubblicazionePubblicato - 2020

Keywords

  • Statistical and Nonliear Physics

Fingerprint Entra nei temi di ricerca di 'Bounding robustness in complex networks under topological changes through majorization techniques'. Insieme formano una fingerprint unica.

Cita questo