Tobias Boltz

Information

Institute: IBPT
Room: 225 in Bldg. 345 at CN
Phone: 0721/608-22152
Email: tobias.boltz@kit.edu
Advisor: Prof. Dr. Anke-Susanne Müller

PhD Thesis

Thesis: Micro-Bunching Control at Electron Storage Rings with Reinforcement Learning
DOI: 10.5445/IR/1000140271
Date of Defense: November 12, 2021

Publications

Title	Journal	Date	Authors
Comprehensive Analysis of Micro-Structure Dynamics in Longitudinal Electron Bunch Profiles	KIT Open (Master's Thesis)	2017	Tobias Boltz
Studies of Longitudinal Dynamics in the Micro-Bunching Instability using Machine Learning	Proceedings of the 9th International Particle Accelerator Conference	2018	Tobias Boltz et al.
Continuous Bunch-by-Bunch Spectroscopic Investigation of the Micro-Bunching Instability	Phys. Rev. Accel. Beams	2018	Johannes L. Steinmann, Tobias Boltz et al.
Systematic studies of the microbunching instability at very low bunch charges	Phys. Rev. Accel. Beams	2019	Miriam Brosi, Tobias Boltz et al.
Feedback Design for Control of the Micro-Bunching Instability based on Reinforcement Learning	Proceedings of the 10th International Particle Accelerator Conference	2019	Tobias Boltz et al.
Perturbation of Synchrotron Motion in the Micro-Bunching Instability	Proceedings of the 10th International Particle Accelerator Conference	2019	Tobias Boltz et al.
Accelerating Machine Learning for Machine Physics (an Amalea-Project at KIT)	Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems	2019	Tobias Boltz et al.
Feedback Design for Control of the Micro-Bunching Instability based on Reinforcement Learning	Proceedings of the ICFA Workshop on Mitigation of Coherent Beam Instabilities in Particle Accelerators	2020	Tobias Boltz et al.
Alpha-buckets in High Energy Electron Storage Rings (Review of Existing Experiments and Feasibility Studies for Future Developments)	Adv. Theo. Comp. Phy.	2021	Alexander Papash, Tobias Boltz et al.
Accelerated Deep Reinforcement Learning for Fast Feedback of Beam Dynamics at KARA	IEEE transactions on nuclear science	2021	Weijia Wang, Tobias Boltz et al.
Excitation of Micro-Bunching in Short Electron Bunches Using RF Amplitude Modulation	Proceedings of the 12th International Particle Accelerator Conference	2021	Tobias Boltz et al.
Micro-Bunching Control at Electron Storage Rings with Reinforcement Learning	KIT Open (Dissertation)	2021	Tobias Boltz

Conferences and Workshops

Title	Conference	Date	Authors
Comprehensive Analysis of Micro-Structure Dynamics in Longitudinal Profiles	DPG-Frühjahrstagung Dresden	2017	Tobias Boltz et al.
Machine Learning Applications at a Storage Ring	5th ARD ST3 Workshop - Matter and Technology	2017	Tobias Boltz et al.
Machine Learning Application on the Investigation of the Micro-Bunching Instability at Storage Rings	ICFA Beam Dynamics Workshop: Machine Learning Applications for Particle Accelerators	2018	Tobias Boltz et al.
Optimization of Synchrotron Light Sources using Machine Learning	DPG-Frühjahrstagung Würzburg	2018	Tobias Boltz et al.
Feedback Design for Control of the Micro-Bunching Instability based on Reinforcement Learning	ICFA Workshop on Machine Learning for Charged Particle Accelerators	2019	Tobias Boltz et al.
Feedback Design for Control of the Micro-Bunching Instability based on Reinforcement Learning	DPG-Frühjahrstagung München	2019	Tobias Boltz et al.
Feedback Design for Control of the Micro-Bunching Instability based on Reinforcement Learning	ICFA Workshop on Mitigation of Coherent Beam Instabilities in Particle Accelerators	2019	Tobias Boltz et al.
Accelerating Machine Learning for Machine Physics (an Amalea-Project at KIT)	International Conference on Accelerator and Large Experimental Physics Control Systems	2019	Tobias Boltz et al.
Towards Micro-Bunching Control at Storage Rings with Reinforcement Learning	DPG AKBP Machine Learning Seminar Bad Honnef	2020	Tobias Boltz et al.
Excitation of micro-bunching in short electron bunches using RF amplitude modulation	DPG-Frühjahrstagung (Online)	2021	Tobias Boltz et al.

KSETA Annual Reports

Annual Report 2018
Annual Report 2019
Annual Report 2020