Machine learning–based longitudinal phase space tuning for X-ray free-electron laser

Precise control of the longitudinal phase space (LPS) in X-ray free-electron laser (XFEL) is critical for optimizing beam qualities and X-ray pulses properties required by the experimental stations. We present results of using machine learning techniques for LPS shaping and control with Bayesian optimization.