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000646123 1001_ $$0P:(DE-H253)PIP1095111$$aKaiser, Jan$$b0$$eCorresponding author$$gmale
000646123 245__ $$aReinforcement Learning and Differentiable Simulations for Autonomous Tuning and Control of Linear Particle Accelerators$$cvon Jan Kaiser ; 1. Gutachter: Prof. Dr.-Ing. Annika Eichler Maschine Strahlkontollen Deutsches Elektonen-Synchrotron DESY Institut für Regelungstechnik Technische Universität Hamburg, 2. Gutachter: Prof. Dr.-Ing. Görschwin Fey Institut für Eingebettete Systeme Technische Universität Hamburg$$f2020-12-01 - 2025-06-04
000646123 260__ $$aMünchen$$bDr. Hut Verlag$$c2025
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000646123 500__ $$aSonstige Körperschaft: Technische Universität Hamburg, Institute of Control Systems;
000646123 502__ $$aDissertation, Technische Universität Hamburg, 2025$$bDissertation$$cTechnische Universität Hamburg$$d2025$$o2025-06-04
000646123 520__ $$aParticle accelerators are sophisticated scientific facilities that require precise but time-consuming optimisation to achieve optimal performance. Considering benchmark tasks at the ARES and LCLS facilities, this dissertation proposes methods to deploy simulation-trained reinforcement learning (RL) policies for accelerator tuning zero-shot to the real world and novel tuning tasks, while comparing their performance to traditional methods. A high-speed differentiable beam dynamics simulator is developed to make collecting large datasets for RL feasible, and to enable a multitude of novel gradient-based accelerator applications. These contributions lay the groundwork for faster accelerator tuning to better working points, and enable new scientific discoveries.
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000646123 650_7 $$2Other$$adifferentiable simulation
000646123 650_7 $$2Other$$aparticle accelerators
000646123 650_7 $$2Other$$aNatural Sciences and Mathematics::539: Matter; Molecular Physics; Atomic and Nuclear physics; Radiation; Quantum Physics
000646123 650_7 $$2Other$$aComputer Science, Information and General Works::006: Special computer methods::006.3: Artificial Intelligence::006.31: Machine Learning
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000646123 7001_ $$0P:(DE-H253)PIP1087213$$aEichler, Annika$$b1$$eThesis advisor$$udesy
000646123 7001_ $$0P:(DE-HGF)0$$aFey, Görschwin$$b2$$eThesis advisor
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