Spatial analysis of femtosecond laser generated plasma using principal component analysis

Area of Science:

• Physics
• Materials Science
• Laser Technology

Background:

• Plasma generation during femtosecond laser machining is influenced by sample surface features.
• Theoretical understanding of femtosecond light-matter interactions and plasma generation is complex and challenging.

Purpose of the Study:

• To apply principal component analysis (PCA) to experimental images of plasma generated during femtosecond laser machining of silicon.
• To identify orthogonal spatial patterns of plasma variance (plasma modes) and their association with sample variance (sample modes).

Main Methods:

• Utilized principal component analysis (PCA) on experimental images.
• Analyzed plasma generated during femtosecond laser machining of silicon.
• Calculated plasma modes and identified associated sample modes.

Main Results:

• Identified orthogonal spatial patterns (plasma modes) of plasma variance.
• Established correlations between specific sample features (sample modes) and observed plasma modes.
• Demonstrated the effectiveness of PCA in analyzing complex laser-induced plasma phenomena.

Conclusions:

• Principal component analysis offers a powerful data-driven approach for scientific discovery in femtosecond laser-matter interactions.
• The study highlights the link between initial sample topography and plasma characteristics.
• PCA can simplify the analysis of complex experimental data in laser processing.