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Complex networks exhibit intermittent synchronization.

V P Vera-Ávila1, J R Sevilla-Escoboza1, I Leyva2

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Summary
This summary is machine-generated.

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.

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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.