Speaker
Description
Beam parameters at the interaction point (IP) of a particle driven wakefield accelerator (PWFA) are carefully controlled to optimize the output energy and beam quality. However, regardless of the parameters achieved, misalignments of beams at a PWFA IP has been shown to produce significant detrimental effects to the output energy and quality. Online monitoring of pointing stability, or beam jitter, at the IP is therefore essential to discern between beam quality optimisation needs and misalignment issues. However, it is not possible to use standard beam position monitors (BPMs) at these locations. Presented in this contribution is the demonstration of a proposed virtual beam position monitor (vBPM), applied to the IP of AWAKE. Upstream BPMs on the proton transfer line as used to infer the transverse position at the IP. A simulation study has been conducted to train a convolutional neural network (CNN) model to perform this inference. Dominant BPMs are highlighted, pointing towards areas of future optimisation to improve the proton beam jitter. Application to recent data collected at AWAKE is also presented, demonstrating the online reconstruction potential for future AWAKE runs.
Funding Agency
This project has received funding from the European Union’s Horizon Europe Research and Innovation programme via the PACRI project under Grant Agreement No 101188004.
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