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Related Experiment Video

Updated: Apr 8, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
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Intermittent Two-Point Dynamics at the Transition to Chaos for Random Circle Endomorphisms.

V P H Goverse1, A J Homburg2,3, J S W Lamb1,4,5

  • 1Department of Mathematics, Imperial College London, 180 Queen's Gate, London, SW7 2AZ UK.

Communications in Mathematical Physics
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Summary
This summary is machine-generated.

Researchers found intermittent dynamics and infinite stationary measures in random circle maps. This reveals a key transition between synchronized behavior and chaotic dynamics in complex systems.

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Area of Science:

  • Dynamical systems theory
  • Statistical mechanics
  • Nonlinear dynamics

Background:

  • Understanding transitions between order and chaos is crucial in complex systems.
  • Circle endomorphisms are fundamental models for studying chaotic dynamics.
  • Lyapunov exponents characterize the sensitivity to initial conditions, distinguishing regular from chaotic behavior.

Purpose of the Study:

  • To characterize the transition from synchronization to chaos in random circle endomorphisms.
  • To establish the existence of intermittent two-point dynamics.
  • To prove the existence of infinite stationary measures for systems with zero Lyapunov exponent.

Main Methods:

  • Analysis of random circle endomorphisms.
  • Investigation of dynamical properties at zero Lyapunov exponent.
  • Mathematical formulation of intermittent dynamics and stationary measures.

Main Results:

  • Established the existence of intermittent two-point dynamics.
  • Proved the existence of infinite stationary measures.
  • Provided a dynamical characterization of the transition from synchronization (negative Lyapunov exponent) to chaos (positive Lyapunov exponent).

Conclusions:

  • The zero Lyapunov exponent regime exhibits complex dynamics, bridging synchronized and chaotic states.
  • Intermittent dynamics and infinite stationary measures are key features of this transition.
  • These findings offer new insights into the onset of chaos in random dynamical systems.