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Complex networks exhibit intermittent synchronization
V P Vera-Ávila1, J R Sevilla-Escoboza1, I Leyva2
1Centro Universitario de los Lagos, Universidad de Guadalajara, Jalisco 47460, Mexico.
Intermittent synchronization, where full synchronization alternates with non-synchronized periods, is influenced by network topology. Network structure can encourage or inhibit this phenomenon, revealing node roles in complex systems.
Area of Science:
- Complex Systems
- Network Science
- Dynamical Systems
Background:
- Synchronization is crucial in many natural and artificial systems.
- Intermittent synchronization is a state observed near complete synchronization, with functional relevance in biological networks.
- Network topology plays a key role in the dynamics of synchronization.
Purpose of the Study:
- To characterize intermittent synchronization as a function of network topology.
- To investigate how different network structures influence the onset and behavior of intermittency.
- To explore the potential of local intermittency analysis for understanding node roles within a network.
Main Methods:
- Analysis of dynamical units and their connection networks.
- Characterization of the intermittent synchronization state.
- Investigation of local intermittency and node incorporation patterns.
- Study of various network topologies and their impact on synchronization transitions.
Main Results:
- Network topology significantly affects the emergence and characteristics of intermittent synchronization.
- Specific network structures can either promote or suppress early signs of intermittency.
- Nodes incorporate into intermittent synchronization in a hierarchical order.
- The hierarchical incorporation provides insights into node topological roles.
Conclusions:
- Network topology is a critical determinant of intermittent synchronization in dynamical systems.
- Understanding local intermittency and node hierarchy can reveal functional roles within networks, even without complete structural knowledge.
- This research highlights the importance of network structure in phenomena near criticality, particularly in biological systems.
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