Structure and dynamical behavior of non-normal networks.

Author: 

Asllani, M
Lambiotte, R
Carletti, T

Publication Date: 

12 December 2018

Journal: 

Science advances

Last Updated: 

2019-11-14T22:26:26.49+00:00

Issue: 

12

Volume: 

4

DOI: 

10.1126/sciadv.aau9403

page: 

eaau9403-

abstract: 

We analyze a collection of empirical networks in a wide spectrum of disciplines and show that strong non-normality is ubiquitous in network science. Dynamical processes evolving on non-normal networks exhibit a peculiar behavior, as initial small disturbances may undergo a transient phase and be strongly amplified in linearly stable systems. In addition, eigenvalues may become extremely sensible to noise and have a diminished physical meaning. We identify structural properties of networks that are associated with non-normality and propose simple models to generate networks with a tunable level of non-normality. We also show the potential use of a variety of metrics capturing different aspects of non-normality and propose their potential use in the context of the stability of complex ecosystems.

Symplectic id: 

942612

Submitted to ORA: 

Submitted

Publication Type: 

Journal Article