ArticleScience advances2016
Synchronization in networks with multiple interaction layers.
Article in Science advances, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Biological detail and graph structure in network neuroscience.Frontiers in network physiology · 2025Review
- Research on UAV Swarm Network Modeling and Resilience Assessment Methods.Sensors (Basel, Switzerland) · 2023Article
- Synchronization of gene expression across eukaryotic communities through chemical rhythms.Nature communications · 2021Article
- Stability of synchronization in simplicial complexes.Nature communications · 2021Article
- Symmetries and cluster synchronization in multilayer networks.Nature communications · 2020Article
- Article
- Taming out-of-equilibrium dynamics on interconnected networks.Nature communications · 2019Article
- Assessing diversity in multiplex networks.Scientific reports · 2019Article
- A Complex Network Theory-Based Modeling Framework for Unmanned Aerial Vehicle Swarms.Sensors (Basel, Switzerland) · 2018Article
- Relay synchronization in multiplex networks.Scientific reports · 2018Article
- Spontaneous repulsion in the A+B→0 reaction on coupled networks.Physical review. E · 2018Article
- Null Model and Community Structure in Multiplex Networks.Scientific reports · 2018Article
- Optimal percolation on multiplex networks.Nature communications · 2017Article
- Inter-layer synchronization in non-identical multi-layer networks.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.