Welch's method transform of strange attractors of argon glow discharge plasmas: symmetric zero point energy fluctuations of particles, anti-particles and virtual particles

TL;DR

This paper applies Welch's method transform to analyze strange attractors in argon glow discharge plasmas, revealing symmetric zero-point energy fluctuations and fractal structures through advanced pattern recognition and machine learning techniques.

Contribution

It introduces a novel application of Welch's transform to plasma attractors, uncovering symmetric zero-point energy fluctuations and complex fractal energy structures.

Findings

Chaos increases with magnetic field and pressure.

Zero-point energy fluctuations are symmetric and cancel out.

Fractal structures emerge from energy field interactions.

Abstract

Substantial developments in pattern recognition and machine learning offer unique advancements to study the deeper structures of plasma physics. We have employed the Kernel principal component analysis(KPCA) of Argon glow discharge plasmas over time-resolved UV-Vis spectra for different pressure scans. 3D vector fields obtained by KPCA reveal the chaotic structure, strange attractors. The presence of the cross magnetic field (B=100G) and the addition of pressure increase the degree of chaos. Lower scale vector fields show that phonon sinks and traps and cool the plasma electron temperatures. The average electron and ion density profiles are provided by the 2D particle in cell simulation. Welch's transformation of the lower to higher scale vector fields illuminates the symmetric zero-point energy fluctuations of particles, antiparticles, and virtual particles. These positive and negative energies cancel each other and the combination of these energy fields form another type of fractal structure.