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

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.