Dimensionality reduction of complex dynamical systems.
Complex Systems
Interdisciplinary Physics
Nonlinear Dynamical Systems
Journal
iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038
Informations de publication
Date de publication:
22 Jan 2021
22 Jan 2021
Historique:
received:
29
07
2020
revised:
06
11
2020
accepted:
03
12
2020
entrez:
28
12
2020
pubmed:
29
12
2020
medline:
29
12
2020
Statut:
epublish
Résumé
One of the outstanding problems in complexity science and engineering is the study of high-dimensional networked systems and of their susceptibility to transitions to undesired states as a result of changes in external drivers or in the structural properties. Because of the incredibly large number of parameters controlling the state of such complex systems and the heterogeneity of its components, the study of their dynamics is extremely difficult. Here we propose an analytical framework for collapsing complex N-dimensional networked systems into an S+1-dimensional manifold as a function of S effective control parameters with S << N. We test our approach on a variety of real-world complex problems showing how this new framework can approximate the system's response to changes and correctly identify the regions in the parameter space corresponding to the system's transitions. Our work offers an analytical method to evaluate optimal strategies in the design or management of networked systems.
Identifiants
pubmed: 33364591
doi: 10.1016/j.isci.2020.101912
pii: S2589-0042(20)31109-3
pmc: PMC7753969
doi:
Types de publication
Journal Article
Langues
eng
Pagination
101912Informations de copyright
© 2020 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no competing interests.
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