Dynamic interdependence and competition in multilayer networks

Michael M. Danziger, Ivan Bonamassa, Stefano Boccaletti, Shlomo Havlin

Research output: Contribution to journalArticlepeer-review

113 Scopus citations

Abstract

From critical infrastructure to physiology and the human brain, complex systems rarely occur in isolation. Instead, the functioning of nodes in one system often promotes or suppresses the functioning of nodes in another. Structural interdependence—that is, when the functionality of the nodes is determined exclusively by connectivity between layers—can be characterized via percolation processes on interdependent networks. However, modelling more general interactions between dynamical systems has remained an open problem. Here, we present a dynamic dependency framework that can capture interdependent and competitive interactions between dynamic systems, which we use to study synchronization and spreading processes in multilayer networks with interacting layers. By developing a mean-field theory, which we verify by simulations, we find coupled collective phenomena, including multistability, regions of coexistence, and macroscopic chaos. In interdependent dynamics, in particular, we observe hysteretic behaviours with abrupt (hybrid and explosive) transitions, that exhibit universal features that match those emerging from interdependent percolation. This dynamic dependency framework provides a powerful tool with which to improve our understanding of many of the interacting complex systems surrounding us.

Original languageEnglish
Pages (from-to)178-185
Number of pages8
JournalNature Physics
Volume15
Issue number2
DOIs
StatePublished - 1 Feb 2019

Bibliographical note

Publisher Copyright:
© 2018, The Author(s), under exclusive licence to Springer Nature Limited.

Funding

M.D. thanks the Azrieli Foundation for the award of an Azrieli Fellowship Grant. S.H. acknowledges the Israel Science Foundation, ONR Global, the Israel-Italian collaborative project NECST, Japan Science Foundation, BSF-NSF, and DTRA (Grant no. HDTRA-1-10-1-0014) for financial support. S.H. also thanks the Nvidia Corporation for a small hardware grant, which was used for this research. This work was supported by the Israeli Ministry of Science, Technology and Space (MOST grant #3-12072). We also thank B. Barzel, A.K.H. Chan and V. Zlatic for several helpful comments and discussions about the manuscript.

FundersFunder number
BSF-NSFHDTRA-1-10-1-0014
Japan Science Foundation
NECST
Office of Naval Research
NVIDIA
Ministry of Science, Technology and Space
Ministry of Science and Technology3-12072
Israel Science Foundation
Azrieli Foundation

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