Linear accelerators with dispersive elements experience projected emittance growth due to coherent synchrotron radiation (CSR) effects which become relevant for highly compressed beams. Even though this is a widely known effect, conventional measurement techniques are not precise enough to resolve the multi-dimensional effects in detail, namely the different rotations of transverse phase space slices throughout the longitudinal coordinate of the bunch. In this work, we apply our generative-model-based six-dimensional phase space reconstruction method in the detailed measurement of CSR effects at the Argonne Wakefield Accelerator Facility in simulations. Additionally, we study the current resolution limitations of the phase space reconstruction method and perform an analysis of its accuracy and precision in simulated cases.

Next-generation accelerator concepts, which hinge on the precise shaping of beam distributions, demand equally precise diagnostic methods capable of reconstructing beam distributions within 6-dimensional position-momentum spaces. However, the characterization of intricate features within 6-dimensional beam distributions using current diagnostic techniques necessitates a substantial number of measurements, using many hours of valuable beam time. Novel phase space reconstruction techniques are needed to reduce the number of measurements required to reconstruct detailed, high-dimensional beam features in order to resolve complex beam phenomena, and as feedback in precision beam shaping applications. In this study, we present a novel approach to reconstructing detailed 6-dimensional phase space distributions from experimental measurements using generative machine learning and differentiable beam dynamics simulations. We demonstrate that this approach can be used to resolve 6-dimensional phase space distributions from scratch, using basic beam manipulations and as few as 20 2-dimensional measurements of the beam profile. We also demonstrate an application of the reconstruction method in an experimental setting at the Argonne Wakefield Accelerator, where it is able to reconstruct the beam distribution and accurately predict previously unseen measurements 75x faster than previous methods.

Many accelerator physics problems such as beamline design, beam dynamics model calibration or interpreting experimental measurements rely on solving an optimization problem that use a simulation of beam dynamics. However, it is difficult to solve high dimensional optimization problems using current beam dynamics simulations because calculating gradients of simulated objectives with respect to input parameters is computationally expensive in high dimensions. To address this problem, backwards differentiable beam dynamics simulations have been developed that enable computationally inexpensive calculations of objective gradients that are independent of the number of input parameters. In this work, we highlight current and future applications of differentiable beam dynamics simulations in accelerator physics, such as improving accelerator design, model calibration, and machine learning. We also describe current collaborative efforts between SLAC, DESY, KIT, and LBNL to implement fast, backwards differentiable beam dynamics simulations in Python. These tools will enable unprecedented improvements in optimization efficiency and speed when using beam dynamics simulations, leading to enhanced control and detailed understanding of physical accelerator systems.

Linear accelerators with dispersive elements experience projected emittance growth due to coherent synchrotron radiation (CSR) effects which become relevant for highly compressed beams. Even though this is a widely known effect, conventional measurement techniques are not precise enough to resolve the multi-dimensional effects in detail, namely the different rotations of transverse phase space slices throughout the longitudinal coordinate of the bunch. In this work, we apply our generative-model-based six-dimensional phase space reconstruction method in the detailed measurement of CSR effects at the Argonne Wakefield Accelerator Facility in simulations. Additionally, we study the current resolution limitations of the phase space reconstruction method and perform an analysis of its accuracy and precision in simulated cases.