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Intermittent feedback induces attractor selection.

Kiran Yadav1, Neeraj Kumar Kamal1, Manish Dev Shrimali1

  • 1Department of Physics, Central University of Rajasthan, Ajmer 305 817 India.

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Summary
This summary is machine-generated.

This study introduces a novel feedback method for controlling multistable dynamical systems. The technique effectively selects desired attractors, enabling applications like logic gate construction.

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Area of Science:

  • Complex Systems
  • Nonlinear Dynamics
  • Computational Neuroscience

Background:

  • Multistable dynamical systems exhibit multiple stable states (attractors).
  • Controlling transitions between attractors is crucial for various applications.
  • Existing methods for attractor selection can be complex or system-specific.

Purpose of the Study:

  • To develop a generalizable method for attractor selection in multistable systems.
  • To demonstrate the efficacy of the proposed method on different dynamical systems.
  • To explore practical applications of the attractor selection technique.

Main Methods:

  • Introduced a space-dependent feedback term activated within specific regions of the state space.
  • Implemented the feedback method on a chaotic flow and a bistable neuronal model.
  • Analyzed the system dynamics to confirm attractor annihilation and selection.

Main Results:

  • The feedback term successfully drove system dynamics to the desired attractor while suppressing others.
  • Demonstrated effective attractor selection in both chaotic and bistable neuronal systems.
  • Confirmed the annihilation of undesired attractors by the feedback mechanism.

Conclusions:

  • The proposed space-dependent feedback method offers a robust approach to attractor selection.
  • This technique is applicable to diverse multistable dynamical systems.
  • The method's utility is shown through the construction of logic gates, highlighting its practical potential.