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Related Experiment Videos

Behavior of coupled automata.

Reuben Gann1, Jessica Venable, Eric J Friedman

  • 1W. M. Keck Science Center, 925 N. Mills Avenue, Claremont McKenna, Pitzer, and Scripps Colleges, Claremont, CA 91711, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|June 1, 2004
PubMed
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Statistical correlations emerge between interacting self-organized critical automata (sandpiles). Synchronization depends on coupling strength, toppling rules, and the number of sandpiles studied.

Area of Science:

  • Complex systems
  • Statistical physics
  • Computational modeling

Background:

  • Self-organized criticality (SOC) describes systems that naturally evolve to a critical state.
  • Sandpile models are canonical examples of SOC systems, exhibiting power-law distributions in avalanche sizes.
  • Understanding emergent phenomena in coupled SOC systems is crucial for complex systems science.

Purpose of the Study:

  • Investigate statistical correlations between interacting sandpile automata.
  • Characterize the phenomenon of synchronization in coupled sandpile systems.
  • Determine the influence of various parameters on sandpile synchronization.

Main Methods:

  • Numerical simulations of coupled sandpile automata.
  • Analytical derivations of correlation properties.

Related Experiment Videos

  • Systematic variation of coupling strength and toppling rule probabilities.
  • Analysis of symmetric and asymmetric coupling configurations.

    • Main Results:

    • Emergence of statistical synchronization between sandpiles was observed.
    • Synchronization levels were found to be dependent on coupling strength.
    • Toppling rule probabilities significantly impacted synchronization.
    • Asymmetric coupling rules showed distinct synchronization patterns compared to symmetric ones.
    • The number of interacting sandpiles influenced the observed correlations.

    Conclusions:

    • Coupled sandpile systems exhibit emergent synchronization.
    • Synchronization is a tunable property influenced by system parameters.
    • The findings provide insights into the collective behavior of complex critical systems.