Résumé
| langue originale | Anglais |
|---|---|
| Numéro d'article | 042302 |
| Pages (de - à) | 1-12 |
| Nombre de pages | 12 |
| journal | Phys. Rev. E |
| Volume | 97 |
| Numéro de publication | 4 |
| Les DOIs | |
| état | Publié - 4 avr. 2018 |
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Topological resilience in non-normal networked systems. / Asllani, Malbor; Carletti, Timoteo.
Dans: Phys. Rev. E , Vol 97, Numéro 4, 042302, 04.04.2018, p. 1-12.Résultats de recherche: Contribution à un journal/une revue › Article
TY - JOUR
T1 - Topological resilience in non-normal networked systems
AU - Asllani, Malbor
AU - Carletti, Timoteo
PY - 2018/4/4
Y1 - 2018/4/4
N2 - 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.
AB - 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.
KW - Dynamical systems
KW - complex network
KW - resilience
KW - non-normal networks
KW - Reaction-diffusion model
KW - Allee effect
KW - Turing patterns
UR - http://www.scopus.com/inward/record.url?scp=85044997501&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.97.042302
DO - 10.1103/PhysRevE.97.042302
M3 - Article
VL - 97
SP - 1
EP - 12
JO - Phys. Rev. E
JF - Phys. Rev. E
IS - 4
M1 - 042302
ER -