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Related Experiment Videos

Noise-induced intermittent cellular patterns on circular domains.

Peter Blomgren1, Scott Gasner, Antonio Palacios

  • 1Nonlinear Dynamics Group, Department of Mathematics and Statistics, San Diego State University, San Diego, California 92182-7720, USA. blomgren@terminus.sdsu.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 13, 2006
PubMed
Summary

Thermal noise in pattern-forming systems drives dynamic cellular states, mimicking laboratory observations. This study numerically confirms homoclinic intermittent states previously seen only in experiments.

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Area of Science:

  • Physics
  • Nonlinear Dynamics
  • Computational Science

Background:

  • Pattern-forming systems are crucial in various scientific disciplines.
  • Understanding the influence of noise is key to explaining system dynamics.
  • Previous research has observed specific dynamic states in laboratory settings.

Purpose of the Study:

  • To investigate the impact of thermal noise on a pattern-forming system.
  • To explore the emergence of dynamic cellular states under noisy conditions.
  • To numerically validate experimental observations of homoclinic intermittent states.

Main Methods:

  • Stochastic Langevin formulation applied to a two-dimensional circular domain.
  • Numerical simulations to observe system behavior.

Related Experiment Videos

  • Analysis of dynamic states, including homoclinic intermittent states.

    • Main Results:

    • Increased tendency towards dynamic cellular states when subjected to thermal noise.
    • Noise-induced dynamics align with prevailing laboratory experimental behaviors.
    • Successful two-dimensional numerical observation of homoclinic intermittent states.

    Conclusions:

    • Thermal noise plays a significant role in driving dynamic behaviors in pattern-forming systems.
    • The study provides a theoretical and numerical basis for experimental findings.
    • Confirms the existence and behavior of homoclinic intermittent states in a computational model.