ArticleNature communications2021
Designing temporal networks that synchronize under resource constraints.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Stability of synchronization manifolds and its nonlinear behaviour in memristive coupled discrete neuron model.Cognitive neurodynamics · 2024Article
- Higher-order correlations reveal complex memory in temporal hypergraphs.Nature communications · 2024Article
- Compressing the Chronology of a Temporal Network with Graph Commutators.Physical review letters · 2024Article
- Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes.Nature communications · 2023Article
- AI Pontryagin or how artificial neural networks learn to control dynamical systems.Nature communications · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Being fundamentally a non-equilibrium process, synchronization comes with unavoidable energy costs and has to be maintained under the constraint of limited resources. Such resource constraints are often reflected as a finite coupling budget available in a network to facilitate interaction and communication. Here, we show that introducing temporal variation in the network structure can lead to efficient synchronization even when stable synchrony is impossible in any static network under the given budget, thereby demonstrating a fundamental advantage of temporal networks. The temporal networks generated by our open-loop design are versatile in the sense of promoting synchronization for systems with vastly different dynamics, including periodic and chaotic dynamics in both discrete-time and continuous-time models. Furthermore, we link the dynamic stabilization effect of the changing topology to the curvature of the master stability function, which provides analytical insights into synchronization on temporal networks in general. In particular, our results shed light on the effect of network switching rate and explain why certain temporal networks synchronize only for intermediate switching rate.
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Registered trials
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