Speaker
Description
We present a data-driven characterisation of the photocathode gun at the Argonne Wakefield Accelerator (AWA) using Bayesian inference, combined with OPAL beam dynamics simulations. Our methodology employs readily available YAG screen diagnostics to perform calibration across a range of experimental conditions, including varying cathode voltages, laser profiles, and beam currents. By integrating these diagnostics with forward beam dynamics simulations from OPAL, we estimate key gun parameters, such as the gun voltage and phase from beam current and solenoid currents. Ongoing work will further refine the calibration process and explore the integration of other diagnostics to enhance the inference process. This allows for more efficient and flexible calibration of complex accelerator systems, particularly with limited readily available measurements
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