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J. Kaiser1, C. Xu2, A. Eichler1, A. Santamaria Garcia2, O. Stein1, E. Bründermann2, W. Kuropka1, H. Dinter1, F. Mayet1, T. Vinatier1, F. Burkart1, H. Schlarb1 1Deutsches Elektronen-Synchrotron DESY, 2 Karlsruhe Institute of Technology KIT arXiv Abstract Online tuning of real-world plants is a complex optimisation problem that continues to require manual intervention by experienced human operators. Autonomous tuning is a rapidly expanding field of research, where learning-based methods, such as Reinforcement Learning-trained Optimisation (RLO) and Bayesian optimisation (BO), hold great promise for achieving outstanding plant performance and reducing tuning times. Which algorithm to choose in different scenarios, however, remains an open question. Here we present a comparative study using a routine task in a real particle accelerator as an example, showing that RLO generally outperforms BO, but is not always the best choice. Based on the study’s results, we provide a clear set of criteria to guide the choice of algorithm for a given tuning task. These can ease the adoption of learning-based autonomous tuning solutions to the operation of complex real-world plants, ultimately improving the availability and pushing the limits of operability of these facilities, thereby enabling scientific and engineering advancements. ...

Reinforcement learning is the most difficult learning paradigms to understand and to efficiently use, but it holds a lot of promise in the field of accelerator physics. The applications of reinforcement learning to accelerators today are not very numerous yet, but the interest of the community is growing considerably. This is how the 1st collaboration workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA'23) came to be! The AI4Accelerators team organized and hosted the workshop at KIT, gathering colleagues involved in reinforcement learning. The workshop offered introductory lectures to reinforcement learning, a Python tutorial that studied the real deployment of such an algorithm in a real accelerator, and guided discussion sessions on the most pressing topics. The contents of the discussion will be published in the form of proceedings later. ...

T. Boltz Karlsruhe Insitute of Technology KIT PhD thesis Abstract At the time this thesis is written, the world finds itself amidst and partly in the process of recovering from the COVID-19 pandemic caused by the SARS-Cov-2 virus. One major contribution to the worldwide efforts of bringing this pandemic to an end are the vaccines developed by different research teams all around the globe. Produced in a remarkably short time frame, a crucial first step for the discovery of these vaccines was mapping out the atomic structure of the proteins making up the virus and their interactions. Due to the bright X-rays required in the process, synchrotron light sources play an active role in the ongoing efforts of accomplishing that goal. Synchrotron light sources are particle accelerators that are capable of providing intense electromagnetic radiation by accelerating packages of electrons, called bunches, and forcing them on curved trajectories. Besides the support of research on the SARS-Cov-2 virus, the remarkable properties of synchrotron radiation lead to a multitude of applications in a variety of scientific fields such as materials science, geology, biology and medicine. As a special form of synchrotron radiation, this thesis is concerned with the coherent synchrotron radiation (CSR) generated by short electron bunches in a storage ring. At wavelengths larger than the size of the emitting electron structure, the particles within a bunch radiate coherently. This coherent emission of synchrotron radiation scales with the number of involved particles and can thus enhance the intensity of the emitted radiation by several orders of magnitude. As a consequence, modern synchrotron light sources, such as the Karlsruhe Research Accelerator (KARA) at the Karlsruhe Institute of Technology (KIT), are deliberately operating with short bunch lengths to extend the radiated CSR spectrum to higher frequencies and to increase the intensity of the emitted radiation. Yet, the continuous reduction of the bunch length at high beam intensities eventually leads to complex longitudinal dynamics caused by the self-interaction of the electron bunches with their own emitted CSR. This phenomenon, generally referred to as micro-bunching or micro-wave instability, can lead to the formation of dynamically changing micro-structures within the charge distribution of the electron bunches and thus to a uctuating emission of CSR. Moreover, it can cause oscillations of the bunch length and the energy spread, which can be detrimental to the operation of a synchrotron light source. On the other hand, as electron structures smaller than the full electron bunch, the micro-structures created by the instability lead to an increased emission of CSR at frequencies up to the THz frequency range. The instability can thus also be beneficial for a variety of applications that rely on intense radiation in that particular frequency range. ...

W. Wang1, M. Caselle1, T. Boltz1, E. Blomley1, M. Brosi1, T. Dritschler1, A. Ebersoldt1, A. Kopmann1, A. Santamaria Garcia1, P. Schreiber1, E. Bründermann1, M. Weber1, A.-S. Müller1, Y. Fang2 1Karlsruhe Insitute of Technology KIT, 2Northwestern Polytechnical University IEEE Transactions on Nuclear Science Abstract Coherent synchrotron radiation (CSR) is generated when the electron bunch length is in the order of the magnitude of the wavelength of the emitted radiation. The self-interaction of short electron bunches with their own electromagnetic fields changes the longitudinal beam dynamics significantly. Above a certain current threshold, the micro-bunching instability develops, characterized by the appearance of distinguishable substructures in the longitudinal phase space of the bunch. To stabilize the CSR emission, a real-time feedback control loop based on reinforcement learning (RL) is proposed. Informed by the available THz diagnostics, the feedback is designed to act on the radio frequency (RF) system of the storage ring to mitigate the micro-bunching dynamics. To satisfy low-latency requirements given by the longitudinal beam dynamics, the RL controller has been implemented on hardware (FPGA). In this article, a real-time feedback loop architecture and its performance is presented and compared with a software implementation using Keras-RL on CPU/GPU. The results obtained with the CSR simulation Inovesa demonstrate that the functionality of both platforms is equivalent. The training performance of the hardware implementation is similar to software solution, while it outperforms the Keras-RL implementation by an order of magnitude. The presented RL hardware controller is considered as an essential platform for the development of intelligent CSR control systems. ...

A. Eichler1, F. Burkart1, J. Kaiser1, W. Kuropka1, O. Stein1, E. Bründermann2, A. Santamaria Garcia2, C. Xu2 1Deutsches Elektronen-Synchrotron DESY, 2Karlsruhe Institute of Technology KIT 12th International Particle Accelerator Conference Abstract Reinforcement learning algorithms have risen in pop-ularity in the accelerator physics community in recentyears, showing potential in beam control and in the opti-mization and automation of tasks in accelerator operation.The Helmholtz AI project “Machine Learning Toward Au-tonomous Accelerators” is a collaboration between DESYand KIT that works on investigating and developing rein-forcement learning applications for the automatic start-upof electron linear accelerators. The work is carried out inparallel at two similar research accelerators: ARES at DESYand FLUTE at KIT, giving the unique opportunity of trans-fer learning between facilities. One of the first steps of thisproject is the establishment of a common interface betweenthe simulations and the machine, in order to test and applyvarious optimization approaches interchangeably betweenthe two accelerators. In this paper we present first results onthe common interface and its application to beam focusingin ARES as well as the idea of laser shaping with spatiallight modulators at FLUTE. ...

T. Boltz, M. Brosi, E. Bründermann, B. Haerer, P. Kaiser, C. Pohl, P. Schreiber, M. Yan,T. Asfour, A.-S. Müller Karlsruhe Insitute of Technology KIT 10th International Particle Accelerator Conference Abstract The operation of ring-based synchrotron light sourceswith short electron bunches increases the emission of co-herent synchrotron radiation (CSR) in the THz frequencyrange. However, the micro-bunching instability resultingfrom self-interaction of the bunch with its own radiationfield limits stable operation with constant intensity of CSRemission to a particular threshold current. Above this thresh-old, the longitudinal charge distribution and thus the emittedradiation vary rapidly and continuously. Therefore, a fastand adaptive feedback system is the appropriate approach tostabilize the dynamics and to overcome the limitations givenby the instability. In this contribution, we discuss first effortstowards a longitudinal feedback design that acts on the RFsystem of the KIT storage ring KARA (Karlsruhe ResearchAccelerator) and aims for stabilization of the emitted THzradiation. Our approach is based on methods of adaptive con-trol that were developed in the field of reinforcement learningand have seen great success in other fields of research overthe past decade. We motivate this particular approach andcomment on different aspects of its implementation. ...