Speaker
Minghao Song
(Brookhaven National Laboratory)
Description
The NSLS-II is a cutting-edge 3 GeV storage ring light source around the world. The electron beam is initially accelerated in a linear accelerator to an energy of 170 MeV and subsequently accelerated in a booster synchrotron to a beam energy of 3 GeV. Therefore, the performance of the Linac and the Linac-to-Booster beam lines is imperative for beam injection to the booster. Online optimization is an effective solution to improve accelerator performance when there is degradation. This paper presents the results of online optimization employing a machine learning method.
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Author
Minghao Song
(Brookhaven National Laboratory)
Co-authors
Guimei Wang
(Brookhaven National Laboratory)
Yoshiteru Hidaka
(Brookhaven National Laboratory)
Xi Yang
(Brookhaven National Laboratory)
