Metastable chimera states in community-structured oscillator networks

Area of Science:

• Complex systems
• Nonlinear dynamics
• Computational neuroscience

Background:

• Coupled oscillator systems exhibit complex emergent behaviors.
• Chimera states represent a unique phenomenon where synchronization and desynchronization coexist within a network.
• Understanding the conditions for generating diverse chimera states is crucial for various scientific fields.

Purpose of the Study:

• To introduce and analyze a novel system of symmetrically coupled identical oscillators with phase lag.
• To investigate the generation of a wide range of transient (metastable) chimera states.
• To quantify metastability and the prevalence and variety of chimera states.

Main Methods:

• Development of a mathematical model for symmetrically coupled identical oscillators with phase lag.
• Organization of oscillators into communities with specific coupling rules.
• Introduction of quantitative measures for metastability, chimera state prevalence, and variety.
• Numerical simulations to explore system dynamics and parameter space.

Main Results:

• The proposed system successfully generates a large repertoire of transient chimera states.
• Metastability, chimera state prevalence, and variety are maximized when the phase lag is close to pi/2.
• The findings reveal a critical parameter regime for complex emergent dynamics.

Conclusions:

• The model provides a framework for understanding and generating complex chimera states in coupled oscillator networks.
• The optimal phase lag condition highlights a key factor in maximizing system metastability and diversity.
• The research has potential applications in understanding brain dynamics and other complex systems.