Speaker
Description
To minimize beam intensity loss during a cycle in the CERN Super Proton Synchrotron (SPS), several machine parameters must be adjusted as functions of cycle time, spanning injection, injection plateau, acceleration, and extraction plateau. Today, these functions are typically tuned manually – a cumbersome procedure that can require hours of operator effort. This paper presents the progress towards automatically tuning time-dependent parameter functions. Using Bayesian optimization (BO), we aim to minimize intensity loss throughout the cycle with intensity measurements as the primary feedback signal. We report results from applying this method to an intentionally detuned machine development beam in the SPS, as a step towards deployment on the operational fixed-target beams. The approach is generic and applicable to time-dependent parameter optimization problems in other machines.
| In which format do you inted to submit your paper? | LaTeX |
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