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  Asymptotic scaling describing signal propagation in complex networks

Ji, P., Lin, W., Kurths, J. (2020): Asymptotic scaling describing signal propagation in complex networks. - Nature Physics, 16, 11, 1082-1083.
https://doi.org/10.1038/s41567-020-1025-3

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 Creators:
Ji, Peng1, Author
Lin, Wei1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: The complex dynamics emergent in diverse systems are influenced not only by the network topologies but also by the interplay of these topologies with the dynamical mechanisms of interaction between nodes. Hens et al.1 established a general framework, novelly linking the universal topological features to the spatiotemporal propagation of signals in complex networks and analytically capturing the topological role in predicting local responses through the asymptotic scaling relationship. Although using an appropriate form of the asymptotic scaling can reveal universal characteristics in complex systems, it is likely to lead to biased or even incorrect predictions if the scaling form is not accurately estimated. It is possible, however, to achieve substantial improvements in the predictive power by including a suitable prefactor in the scaling.

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 Dates: 2020-11-022020-11-15
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41567-020-1025-3
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
Organisational keyword: RD4 - Complexity Science
Working Group: Network- and machine-learning-based prediction of extreme events
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Title: Nature Physics
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 16 (11) Sequence Number: - Start / End Page: 1082 - 1083 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1603091
Publisher: Springer Nature