Speaker
Description
The injector of the NSLS-II consists of a linear accelerator (LINAC) that accelerates the electron beam to 170 MeV, followed by a linac-to-booster (LTB) transport line and a booster synchrotron that further increases the beam energy to 3 GeV. The performance of the LINAC and LTB is critical for achieving efficient and stable beam injection. Automated online tuning is a useful method for improving injector performance. In this paper, we present an automated tuning approach based on Bayesian optimization, using different packages to optimize the LINAC and LTB subsystems. We evaluate and compare these packages based on how well they improve injection efficiency. Our results show that Bayesian optimization can significantly improve injector performance and reveal differences in performance across the packages.
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