Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer

A recent study published in Physical Review Accelerators and Beams introduces advanced methods for reconstructing electron beam parameters and betatron radiation spectra using a Compton spectrometer. This work is particularly relevant for high-energy plasma wakefield acceleration experiments, such as those planned at the FACET-II facility at SLAC National Accelerator Laboratory.

Displayed are example spectra for beams with different spot sizes, featuring both 1D and double differential spectra. Each spectrum is tagged with its actual spot size followed by the predicted spot size, as determined by the direct 1D or double differential ML models.(M.Yadav, et al.,Phys. Rev. Accel. Beams 28, 042802 CC BY 4.0)

The research team, comprising scientists from institutions including the University of California, Los Angeles; the University of Liverpool; and the University of Manchester, focused on analysing the photon flux generated when high-energy electron beams interact with intense electromagnetic fields. These interactions produce betatron radiation, which carries valuable information about the electron beam's characteristics. However, extracting precise beam parameters from the resulting photon spectra is a complex challenge.

To address this, the researchers employed simulated data modelling betatron radiation from plasma wakefield acceleration scenarios. They compared traditional maximum likelihood estimation techniques with modern machine learning approaches, including multilayer neural networks, to interpret the energy and angular distributions of the detected photons. By applying these methods, they successfully reconstructed key beam properties such as spot size, energy, and emittance with high accuracy.

Notably, the study demonstrated that machine learning algorithms could effectively handle the intricate relationship between the observed photon spectra and the underlying beam dynamics. This capability is crucial for optimizing beam performance in high-field environments and advancing our understanding of beam-plasma interactions.

The findings underscore the potential of integrating advanced computational techniques into beam diagnostics, paving the way for more precise control and analysis in next-generation accelerator experiments. As the field moves toward increasingly sophisticated setups, such methodologies will be instrumental in achieving desired beam qualities and enhancing experimental outcomes.

Further reading:

M. Yadav et al. Physical review Accelerators and Beams 28(4), 042802 (April 2025) https://doi.org/10.1103/PhysRevAccelBeams.28.042802