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Updated: Jun 7, 2025

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Published on: May 29, 2014
Rhythmic states and first-order phase transitions in adaptive coupled three-dimensional limit-cycle oscillators
Jiangsheng Wang1, Changgui Gu1, Wei Zou2
1Department of Systems Science, Business School, <a href="https://ror.org/00ay9v204">University of Shanghai for Science and Technology</a>, Shanghai 200093, China.
This study reveals phase transitions in adaptive coupled oscillators. Multiple rhythmic states appear with uniform frequency distribution but vanish with Gaussian distribution, showing distinct oscillation behaviors.
Area of Science:
- Complex Systems
- Nonlinear Dynamics
- Statistical Physics
Background:
- Coupled limit-cycle oscillators are fundamental in modeling diverse phenomena.
- Understanding phase transitions in high-dimensional systems is crucial for complex network analysis.
Purpose of the Study:
- To investigate phase transitions in three-dimensional coupled limit-cycle oscillators with adaptive coupling.
- To explore the influence of natural frequency distribution on emergent rhythmic states and phase transitions.
Main Methods:
- Analysis of coupled three-dimensional limit-cycle oscillators with adaptive coupling.
- Investigation of systems with uniform and Gaussian natural frequency distributions.
- Theoretical analysis of incoherent states and fixed points, verified by numerical simulations.
Main Results:
- Multiple-cluster rhythmic states emerge for uniform frequency distribution (Case I) but not for Gaussian distribution (Case II).
- Two sequential first-order phase transitions occur with increasing coupling strength (K).
- A nonhysteretic transition occurs at K→0⁺, while a hysteretic transition emerges for K>0, dependent on frequency distribution width.
Conclusions:
- The natural frequency distribution critically affects the emergence of complex rhythmic states and phase transition behaviors.
- Adaptive coupling in high-dimensional oscillator systems exhibits rich phase transition dynamics.
- The findings offer insights into the collective dynamics of complex oscillatory networks.
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