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Heterogeneous nucleation in a multiplex adaptive network.

Akash Yadav1, Qazi Saaheelur Rahaman1,2, V K Chandrasekar3

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Summary
This summary is machine-generated.

Frequency disorder in one layer of multiplex networks triggers synchronization transitions in other layers. This heterogeneous nucleation impacts phase transitions and desynchronization, revealing network-specific dynamics.

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Area of Science:

  • Complex systems
  • Network science
  • Nonlinear dynamics

Background:

  • Multiplex networks consist of multiple interacting layers, each with unique properties.
  • Kuramoto oscillators are widely used models for studying synchronization phenomena.
  • Frequency disorder can significantly alter synchronization dynamics in coupled oscillator systems.

Purpose of the Study:

  • To investigate the impact of frequency disorder on phase transitions to synchronization in multiplex networks.
  • To understand how disorder in one layer nucleates synchronization across other layers.
  • To analyze the role of interlayer coupling strength in synchronization and desynchronization transitions.

Main Methods:

  • Simulating adaptively coupled Kuramoto oscillators in a multiplex network structure.
  • Introducing frequency disorder in specific layers to observe its propagation.
  • Analyzing synchronization transitions using synchronization index and coupling weight snapshots.
  • Employing the collective coordinate framework to derive reduced evolution equations.

Main Results:

  • Frequency disorder in one layer acts as a nucleation site, influencing synchronization in uniform layers.
  • Multiplex networks primarily show abrupt single-step transitions, with occasional gradual multistep transitions.
  • Intermediate interlayer coupling strength reduces the required intralayer coupling for synchronization.
  • Desynchronization transitions occur in intermediate coupling ranges, specific to multilayer networks.

Conclusions:

  • Heterogeneous nucleation due to frequency disorder drives distinct synchronization transitions in multiplex networks.
  • Reduced models derived from the collective coordinate framework accurately predict observed transitions.
  • The findings offer insights into the complex synchronization dynamics of real-world multilayer systems.