AI Algorithms for Plasma Particle Tracking

Detecting micron-sized particles is crucial for analyzing complex plasmas, with machine learning and artificial intelligence algorithms showing significant advancements over classical methods. This study employs architectures for detecting and tracking particles in the Plasmakristallexperiment 4 (PK-4). Given the constraints of parabolic flight experiments, the research explores optimized, less complex models to balance efficiency and accuracy. Comparative analysis is conducted identifying the most effective approach for application to PK-4 experimental data.