Betatron radiation that arises during plasma wakefield acceleration can be measured by a UCLA-built Compton spectrometer, which records the energy and angular position of incoming photons. Because information about the properties of the beam is encoded in the betatron radiation, measurements of the radiation can be used to reconstruct beam parameters. One method of extracting information about beam parameters from measurements of radiation is maximum likelihood estimation (MLE), a statistical technique which is used to determine unknown parameters from a distribution of observed data. In addition, machine learning methods, which are increasingly being implemented for different fields of beam diagnostics, can also be applied. We assess the ability of both MLE and other machine learning methods to accurately extract beam parameters from measurements.
Proceedings of the 13th International Particle Accelerator Conference, IPAC2022, Bangkok, Thailand