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Critical exponents in coupled phase-oscillator models on small-world networks
Ryosuke Yoneda1, Kenji Harada1, Yoshiyuki Y Yamaguchi1
1Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan.
Synchronization transitions in coupled phase-oscillator models reveal a single universality class on small-world networks. This finding simplifies understanding complex synchronization dynamics, regardless of network structure or coupling functions.
Area of Science:
- Complex Systems
- Statistical Physics
- Network Science
Background:
- Coupled phase-oscillator models exhibit synchronization transitions between nonsynchronized and partially synchronized states.
- These transitions are crucial for understanding emergent collective behavior in various systems.
- Universality classes, defined by critical exponents, characterize the synchronization transition's behavior.
Purpose of the Study:
- To investigate the number of universality classes in synchronization transitions on small-world networks.
- To determine if the infinite universality classes observed in perfect graphs persist in small-world networks.
- To analyze the critical exponent's dependence on network topology and coupling functions.
Main Methods:
- Simulated coupled phase-oscillator models on small-world networks.
- Analyzed the order parameter's dependence on coupling strength to determine critical exponents.
- Varied natural frequency distributions and coupling functions (up to second harmonics).
Main Results:
- Numerical simulations indicate a reduction to a single universality class on small-world networks.
- The critical exponent is shared across different coupling functions and unimodal, symmetric frequency distributions.
- This contrasts with the infinite universality classes found in perfect graph models.
Conclusions:
- Small-world network topology significantly simplifies the universality classes of synchronization transitions.
- A single universality class and shared critical exponent are observed under specific conditions.
- These findings offer a more unified understanding of synchronization phenomena in complex networks.
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