17–22 May 2026
C.I.D
Europe/Zurich timezone

Bayesian Optimization of Longitudinal Phase Space in the MAX IV Linac

WEP6015
20 May 2026, 16:00
2h
C.I.D

C.I.D

Deauville, France
Poster Presentation MC6.D13: Instrumentation: Artificial Intelligence Poster session

Speaker

Johan Lundquist (Lund University)

Description

Reaching design performance in modern particle accelerators is a challenge involving many tasks which are time-consuming and difficult to perform. It is always an advantage to be able to simplify high-level operational tasks and measurements through the assistance of optimization techniques. In this work we applied Bayesian optimization via the XOpt framework with the aim to simplify and enhance the operations in the MAX IV linac. The focus of this work has been longitudinal phase-space optimization using signals from a transverse deflector system. Further, a new approach in the optimization of longitudinal phase-space parameters with the use of virtual diagnostics has been developed and implemented.

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Author

Johan Lundquist (Lund University)

Co-authors

Erik Mansten (MAX IV Laboratory) Francesca Curbis (Lund University) Jonas Björklund Svensson (Lund University) Sverker Werin (MAX IV Laboratory)

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