Oscillators that sync and swarm
By Kevin P. O'Keeffe, Hyunsuk Hong, Steven H. Strogatz. Nature Communications, 2017
343 citations recorded by the source corpus.
Synchronization occurs in many natural and technological systems, from cardiac pacemaker cells to coupled lasers. In the synchronized state, the individual cells or lasers coordinate the timing of their oscillations, but they do not move through space. A complementary form of self-organization occurs among swarming insects, flocking birds, or schooling fish; now the individuals move through space, but without conspicuously altering their internal states. Here we explore systems in which both synchronization and swarming occur together. Specifically, we consider oscillators whose phase dynamics and spatial dynamics are coupled. We call them swarmalators, to highlight their dual character. A case study of a generalized Kuramoto model predicts five collective states as possible long-term modes of organization. These states may be observable in groups of sperm, Japanese tree frogs, colloidal suspensions of magnetic particles, and other biological and physical systems in which self-assembly and synchronization interact. Collective self-organized behavior can be observed in a variety of systems such as colloids and microswimmers. Here O’Keeffe et al. propose a model of oscillators which move in space and tend to synchronize with neighboring oscillators and outline five types of collective self-organized states.
Subfields: Biomedical Engineering, Computer Networks and Communications, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/bc21b518e9874224a680da5c58630c46b49cbeec
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In Biomedical Engineering
In Computer Networks and Communications
- Marco Grassia
- Filippo Radicchi
- Hernán A. Makse
- Giuseppe Mangioni
- J. P. Gleeson
- Oriol Artime
- Matjaz Perc
- Manlio De Domenico
In Global and Planetary Change
Citations in the corpus
- Swarm Robotic Behaviors and Current Applications (2020, background): “(2019) apply the novel concept of swarmalators (O’Keeffe et al., 2017) to robots.”
- Robustness and resilience of complex networks (2024, background): “…of a system (such as whether it is spatially embedded or not, interdependent with other systems or not, or multiplex 34–36 ) and its dynamics (for instance, whether it has regimes in which collective behaviour emerges, such as in synchronization, epidemic spreading or coupled dynamics 37–40 ).”