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

The present work introduces an analysis framework to comprehend the dynamics of a 3D plasma model, which has been proposed to describe the pellet injection in tokamaks. The analysis of the system reveals the existence of a complex transition from transient chaos to steady periodic behavior. Additionally, without adding any kind of forcing term or controllers, we demonstrate that the system can be changed to become a multi-stable model by injecting more power input. In this regard, we observe that increasing the power input can fluctuate the numerical solution of the system from coexisting symmetric chaotic attractors to the coexistence of infinitely many quasi-periodic attractors. Besides that, complexity analyses based on Sample entropy are conducted, and they show that boosting power input spreads the trajectory to occupy a larger range in the phase space, thus enhancing the time series to be more complex and random. Therefore, our analysis could be important to further understand the dynamics of such models, and it can demonstrate the possibility of applying this system for generating pseudorandom sequences.

Automated summary

This study introduces an analysis framework to understand the dynamics of a 3D plasma model, revealing a complex transition from transient chaos to steady periodic behavior. It is shown that by increasing power input, the system can become a multi-stable model with the transition from coexisting symmetric chaotic attractors to the coexistence of infinitely many quasi-periodic attractors. Moreover, complexity analyses based on Sample entropy demonstrate that boosting power input can enhance the complexity and randomness of the system's time series by spreading the trajectory in the phase space.