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Enhancing Chaos Complexity of a Plasma Model through Power Input with Desirable Random Features.

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Summary
This summary is machine-generated.

This study analyzes a 3D plasma model for tokamak pellet injection, revealing a transition from chaos to periodic behavior. Increased power input induces multi-stability and generates complex, pseudorandom sequences.

Keywords:
multistabilityrandomnesssample entropytransient chaotic behavior

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Area of Science:

  • Plasma Physics
  • Nonlinear Dynamics
  • Fusion Energy Research

Background:

  • Tokamak devices are crucial for fusion energy research.
  • Pellet injection is a key technique for plasma control in tokamaks.
  • Understanding plasma dynamics is essential for stable fusion reactions.

Purpose of the Study:

  • To develop an analysis framework for a 3D plasma model simulating tokamak pellet injection.
  • To investigate the transition from chaotic to periodic behavior in the plasma model.
  • To explore the potential for generating pseudorandom sequences from the plasma model dynamics.

Main Methods:

  • Development of a novel analysis framework for 3D plasma dynamics.
  • Numerical simulation of the plasma model under varying power input.
  • Complexity analysis using Sample Entropy to quantify randomness.

Main Results:

  • Observed a complex transition from transient chaos to steady periodic behavior.
  • Demonstrated the induction of multi-stability by increasing power input without external forcing.
  • Showcased the shift from chaotic attractors to infinite quasi-periodic attractors with higher power.
  • Sample Entropy analysis confirmed increased trajectory spread and enhanced time series complexity.

Conclusions:

  • The 3D plasma model exhibits rich dynamical transitions influenced by power input.
  • Increased power input can transform the system into a multi-stable state with diverse attractors.
  • The model's ability to generate complex, pseudorandom sequences holds potential for applications in secure communications or simulations.