Speaker
Description
In the SIS18 heavy-ion synchrotron at GSI, loss-induced vacuum degradation and reduced beam lifetime limit high-intensity operation with uranium ions. During multi-turn injection (MTI), even small localized losses can trigger pressure bump instabilities, making optimized injection control essential to reach FAIR intensity goals. We present a comprehensive study on optimizing the MTI process in the SIS18 synchrotron at GSI, combining experimental measurements and simulations. Online optimization using the derivative-free BOBYQA algorithm enabled direct improvement of machine performance. Multi-objective Bayesian optimization (BO) was applied to reconstruct the Pareto front experimentally between injection efficiency and beam losses, providing insight into the best achievable performance. On this basis, we introduce a multi-fidelity BO framework that integrates prior knowledge from low-fidelity models with high-fidelity experimental measurements, achieving improved sample efficiency. Complementary simulation studies on two-plane injection indicate a further potential for loss reduction. The results demonstrate effective, adaptive MTI optimization and support future autonomous tuning strategies.
Funding Agency
The EURO-LABS project has received funding from the European Union's Horizon Europe Research and Innovation programme under Grant Agreement no. 101057511.
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