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Controlling a complex system near its critical point via temporal correlations.
Dante R Chialvo1,2, Sergio A Cannas3, Tomás S Grigera4,5
1Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de Gral. San Martín, Campus Miguelete, 25 de Mayo y Francia, 1650, San Martín, Buenos Aires, Argentina. dchialvo@gmail.com.
Scientific Reports
|July 24, 2020
Summary
Complex systems self-tune to critical points by using time correlation feedback. This mechanism, observed in models like the Ising model, helps systems reach phase transitions naturally.
Area of Science:
- Complex Systems Dynamics
- Statistical Physics
- Phase Transitions
Background:
- Complex systems often display significant spatial and temporal fluctuations.
- These fluctuations are frequently associated with critical phenomena, where space and time correlations are interconnected.
Purpose of the Study:
- To investigate if temporal correlation properties enable systems undergoing a phase transition to self-tune to their critical point.
- To test the hypothesis that feedback mechanisms drive systems toward criticality.
Main Methods:
- Simulations of three distinct models: the 2D Ising ferromagnetic model, the 3D Vicsek flocking model, and a small-world neuronal network.
- Analysis of the autocorrelation function of order parameter fluctuations.
Main Results:
- Demonstrated that feedback from the autocorrelation function of order parameter fluctuations drives systems toward their critical point.
- Observed this self-tuning behavior across all three diverse models.
Conclusions:
- Temporal correlation feedback is a viable mechanism for systems to self-organize towards a critical point.
- The findings are based on universal properties of critical systems and have broad applicability.
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