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Published on: March 1, 2017
Complexified synchrony
Seungjae Lee1, Lucas Braun1,2,3, Frieder Bönisch1
1Chair for Network Dynamics, Center for Advancing Electronics Dresden (CFAED) and Institut für Theoretische Physik, Technische Universität Dresden, 01062 Dresden, Germany.
Complexifying the Kuramoto model reveals new dynamics in coupled oscillator systems. Finite-size networks exhibit novel asynchronous states and discontinuous phase transitions, even with weak coupling.
Area of Science:
- Physics
- Complex Systems
- Nonlinear Dynamics
Background:
- The Kuramoto model is widely used to study synchrony in coupled oscillators.
- Open questions remain, particularly for finite-size systems.
- Previous work extended the Kuramoto model to the complex domain.
Purpose of the Study:
- Generalize the finite-size Kuramoto model by analytically continuing state variables and complexifying system parameters.
- Investigate the dynamics of coupled oscillators with complex coupling strengths.
- Explore novel collective behaviors and phase transitions in these generalized systems.
Main Methods:
- Analytical continuation of state variables to the complex domain.
- Complexification of system parameters, including coupling strengths.
- Numerical simulations for large networks of coupled oscillators.
Main Results:
- Systems with purely imaginary coupling exhibit persistent asynchronous dynamics, not synchronization, regardless of coupling strength.
- Generic complex coupling leads to 'complex locked states'—fixed points off the real axis—even for weak coupling.
- A new collective mode of rotations with finite, arbitrarily large rotation numbers was identified.
- Numerical simulations revealed a novel discontinuous phase transition in large networks.
Conclusions:
- Complexifying the Kuramoto model introduces fundamentally new dynamical behaviors beyond traditional synchronization.
- The findings challenge existing understanding of collective dynamics in finite-size oscillator networks.
- The study opens new avenues for research into complex systems and emergent phenomena.
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