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Reinforcement learning-trained optimisers and Bayesian optimisation for online particle accelerator tuning
Online tuning of particle accelerators is a complex optimisation problem that continues to require manual intervention by experienced …
Jan Kaiser, Chenran Xu, Annika Eichler, Andrea Santamaria Garcia, Oliver Stein, Erik Bründermann, Willi Kuropka, Hannes Dinter, Frank Mayet, Thomas Vinatier, Florian Burkart, Holger Schlarb
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Reinforcement learning-trained optimisers and Bayesian optimisation for online particle accelerator tuning
Bridging the gap between machine learning and particle accelerator physics with high-speed, differentiable simulations
Machine learning has emerged as a powerful solution to the modern challenges in accelerator physics. However, the limited availability …
Jan Kaiser, Chenran Xu, Annika Eichler, Andrea Santamaria Garcia
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Bridging the gap between machine learning and particle accelerator physics with high-speed, differentiable simulations
Bayesian optimization of the beam injection process into a storage ring
We have evaluated the data-efficient Bayesian optimization method for the specific task of injection tuning in a circular accelerator. …
Chenran Xu, Tobias Boltz, Akira Mochihashi, Andrea Santamaria Garcia, Marcel Schuh, Anke-Susanne Müller
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Bayesian optimization of the beam injection process into a storage ring