Search

Abstract Radio-frequency particle accelerators are engines of discovery, powering high-energy physics and photon science, but are also large and expensive due to their limited accelerating fields. Plasma-wakefield accelerators (PWFAs) provide orders-of-magnitude stronger fields in the charge-density wave behind a particle bunch travelling in a plasma, promising particle accelerators of greatly reduced size and cost. However, PWFAs can easily degrade the beam quality of the bunches they accelerate. Emittance, which determines how tightly beams can be focused, is a critical beam quality in for instance colliders and free-electron lasers, but is particularly prone to degradation. We demonstrate, for the first time, emittance preservation in a high-gradient and high-efficiency PWFA while simultaneously preserving charge and energy spread. This establishes that PWFAs can accelerate without degradation—an essential step toward energy boosters in photon science and multistage facilities for compact high-energy particle colliders.

Laser wakefield accelerators are compact sources of ultra-relativistic electrons which are highly sensitive to many control parameters. Here the authors present an automated machine learning based method for the efficient multi-dimensional optimization of these plasma-based particle accelerators.

Controlled particle acceleration in plasmas requires precise measurements of the excited wakefield. Here the authors report and demonstrate a high-resolution method to measure the effective longitudinal electric field of a beam-driven plasma-wakefield accelerator.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20676-1