Structure and dynamical behavior of non-normal networks

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 str...

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Bibliographic Details
Published in:Science advances 2018-12, Vol.4 (12), p.eaau9403-eaau9403
Main Authors: Asllani, Malbor, Lambiotte, Renaud, Carletti, Timoteo
Format: Article
Language:eng
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Summary: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.
ISSN:2375-2548
2375-2548