Machine learning offers transformative potential for laser-plasma accelerators, enabling real-time optimization, predictive modelling, and experimental automation. The authors present a synthetic diagnostic approach using deep neural networks to accurately predict proton energy spectra from laser-plasma interactions, demonstrating a non-intrusive diagnostic for high-repetition-rate operations and future applications.
- Christopher J. G. McQueen
- Robbie Wilson
- Paul McKenna
