Topological resilience in non-normal networked systems

Résultats de recherche: Contribution à un journal/une revueArticleRevue par des pairs

47 Téléchargements (Pure)


The network of interactions in complex systems strongly influences their resilience and the system capability to resist external perturbations or structural damages and to promptly recover thereafter. The phenomenon manifests itself in different domains, e.g., parasitic species invasion in ecosystems or cascade failures in human-made networks. Understanding the topological features of the networks that affect the resilience phenomenon remains a challenging goal for the design of robust complex systems. We hereby introduce the concept of non-normal networks, namely networks whose adjacency matrices are non-normal, propose a generating model, and show that such a feature can drastically change the global dynamics through an amplification of the system response to exogenous disturbances and eventually impact the system resilience. This early stage transient period can induce the formation of inhomogeneous patterns, even in systems involving a single diffusing agent, providing thus a new kind of dynamical instability complementary to the Turing one. We provide, first, an illustrative application of this result to ecology by proposing a mechanism to mute the Allee effect and, second, we propose a model of virus spreading in a population of commuters moving using a non-normal transport network, the London Tube.
langue originaleAnglais
Numéro d'article042302
Pages (de - à)1-12
Nombre de pages12
journalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Numéro de publication4
Les DOIs
Etat de la publicationPublié - 4 avr. 2018

Empreinte digitale

Examiner les sujets de recherche de « Topological resilience in non-normal networked systems ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation