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Related Experiment Video

Updated: Jun 25, 2026

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

Control of multistate hopping intermittency.

¹Laser and Plasma Technology Division, Bhabha Atomic Research Centre, Mumbai 400085, India. binoy@barc.gov.in

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|March 5, 2009

Summary

This summary is machine-generated.

Noise-induced multistate hopping intermittency in complex systems can be controlled. A small periodic perturbation can shift the system

Related Experiment Videos

Last Updated: Jun 25, 2026

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

Area of Science:

Nonlinear Dynamics
Complex Systems
Chaos Theory

Background:

Multistable systems exhibit noise-induced multistate hopping intermittency, characterized by intermittent transitions between coexisting stable attractors.
Understanding and controlling these transitions is crucial for predicting and manipulating the behavior of complex systems.

Purpose of the Study:

To demonstrate that a small periodic perturbation can significantly control multistate hopping intermittency.
To achieve a qualitative change in the probability distribution of occupation in phase space, favoring one attractor over another.

Main Methods:

Theoretical demonstration using two standard models: Lorenz equations (autonomous) and the periodically driven, damped Toda oscillator (nonautonomous).
Control mechanism involves destroying one attractor (A) via boundary crisis while maintaining the stability of another attractor (B).

Main Results:

A small-amplitude, slow-periodic perturbation can qualitatively alter the system's intermittent behavior.
The perturbation shifts the occupation probability, making the system favor attractor B over attractor A, even when noise pushes it towards A.
Experimental validation using a CO2 laser and an analog circuit of Lorenz equations confirmed the theoretical predictions.

Conclusions:

Periodic perturbations offer an effective method for controlling noise-induced intermittency in multistable systems.
This control strategy can be applied to both autonomous and nonautonomous systems.
The findings have implications for manipulating the dynamics of various complex systems, from lasers to electronic circuits.