IPAC2021 - List of Authors (Eichler, A.)

Paper	Title	Page
TUPAB291	Subsystem Level Data Acquisition for the Optical Synchronization System at European XFEL	2167
	M. Schütte, A. Eichler, T. Lamb, V. Rybnikov, H. Schlarb, T. Wilksen DESY, Hamburg, Germany
	The optical synchronization system for the European X-Ray Free-Electron Laser provides sub-10 femtosecond timing precision * for the accelerator subsystems and experiments. This is achieved by phase locking a mode-locked laser oscillator to the main RF reference and distributing the optical pulse train carrying the time information via actively propagation-time stabilized optical fibers to multiple end-stations. Making up roughly one percent of the entire European XFEL, it is the first subsystem to receive a large-scale data acquisition system [2] for storing not just hand-selected information, but in fact all diagnostic, monitoring, and configuration data relevant to the optical synchronization available from the distributed control system infrastructure. A minimum of 100 TB per year may be stored in a persistent archive for long-term health monitoring and data mining whereas excess data is stored in a short-term ring buffer for high-resolution fault analysis and feature extraction algorithm development. This paper describes scale, challenges and first experiences from the optical synchronization data acquisition system. * S. Schulz et al., "Few-Femtosecond Facility-Wide Sync. of the European XFEL," in Proc. FEL’19 ** T. Wilksen et al., "A Bunch-Sync. DAQ System for the European XFEL," in Proc. ICALEPCS’17
	Poster TUPAB291 [0.281 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB291
About •	paper received ※ 14 May 2021 paper accepted ※ 17 June 2021 issue date ※ 24 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPAB298	First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT	2182
	A. Eichler, F. Burkart, J. Kaiser, W. Kuropka, O. Stein DESY, Hamburg, Germany E. Bründermann, A. Santamaria Garcia, C. Xu KIT, Eggenstein-Leopoldshafen, Germany
	Funding: Helmholtz Artificial Cooperation Unit Reinforcement Learning algorithms have risen in popularity in recent years in the accelerator physics community, showing potential in beam control and in the optimization and automation of tasks in accelerator operation. The Helmholtz AI project "Machine Learning toward Autonomous Accelerators" is a collaboration between DESY and KIT that works on investigating and developing RL applications for the automatic start-up of electron linear accelerators. The work is carried out in parallel at two similar research accelerators: ARES at DESY and FLUTE at KIT, giving the unique opportunity of transfer learning between facilities. One of the first steps of this project is the establishment of a common interface between the simulations and the machine, in order to test and apply various optimization approaches interchangeably between the two accelerators. In this paper we present the first results on the common interface and its application to beam focusing in ARES, and the idea of laser shaping with spatial light modulators at FLUTE.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB298
About •	paper received ※ 19 May 2021 paper accepted ※ 02 August 2021 issue date ※ 17 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB289	Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE	3332
	C. Xu, E. Bründermann, A.-S. Müller, M.J. Nasse, A. Santamaria Garcia, C. Sax, C. Widmann KIT, Karlsruhe, Germany A. Eichler DESY, Hamburg, Germany
	Funding: C. Xu acknowledges the support by the DFG-funded Doctoral School "Karlsruhe School of Elementary and Astroparticle Physics: Science and Technology". FLUTE (Ferninfrarot Linac- und Test-Experiment) at KIT is a compact linac-based test facility for novel accelerator technology and a source of intense THz radiation. FLUTE is designed to provide a wide range of electron bunch charges from the pC- to nC-range, high electric fields up to 1.2 GV/m, and ultra-short THz pulses down to the fs-timescale. The electrons are generated at the RF photoinjector, where the electron gun is driven by a commercial titanium sapphire laser. In this kind of setup the electron beam properties are determined by the photoinjector, but more importantly by the characteristics of the laser pulses. Spatial light modulators can be used to transversely and longitudinally shape the laser pulse, offering a flexible way to shape the laser beam and subsequently the electron beam, influencing the produced THz pulses. However, nonlinear effects inherent to the laser manipulation (transportation, compression, third harmonic generation) can distort the original pulse. In this paper we propose to use machine learning methods to manipulate the laser and electron bunch, aiming to generate tailor-made THz pulses. The method is demonstrated experimentally in a test setup.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB289
About •	paper received ※ 19 May 2021 paper accepted ※ 06 July 2021 issue date ※ 26 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB293	The Trip Event Logger for Online Fault Diagnosis at the European XFEL	3344
	J.H.K. Timm, J. Branlard, A. Eichler, H. Schlarb DESY, Hamburg, Germany
	The low-level RF (LLRF) system at the European XFEL, DESY, is of major importance for a high-performant and reliable operation. Faults here can jeopardize the overall operation. Therefore, the trip event logger is currently developped, - a fault diagnosis tool to detect errors online, inform the operators and trigger automatic supervisory actions. Further goals are to provide information for a fault tree and event tree analysis as well as a database of labeled faulty data sets for offline analysis. The tool is based on the C++ framework ChimeraTK Application Core. With this close interconnection to the control system it is possible not only to monitor but also to intervene as it is of great importance for supervisory tasks. The core of the tool consists of fault analysis modules ranging from simple ones (e.g., limit checking) to advanced ones (model-based, machine learning, etc.). Within this paper the architecture and the implementation of the trip event logger are presented.
	Poster WEPAB293 [7.919 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB293
About •	paper received ※ 19 May 2021 paper accepted ※ 02 July 2021 issue date ※ 10 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPAB191	Physics-Enhanced Reinforcement Learning for Optimal Control	4150
	A.N. Ivanov, I.V. Agapov, A. Eichler, S. Tomin DESY, Hamburg, Germany
	We propose an approach for incorporating accelerator physics models into reinforcement learning agents. The proposed approach is based on the Taylor mapping technique for simulation of the particle dynamics. The resulting computational graph is represented as a polynomial neural network and embedded into the traditional reinforcement learning agents. The application of the model is demonstrated in a nonlinear simulation model of beam transmission. The comparison of the approach with the traditional numerical optimization as well as neural networks based agents demonstrates better convergence of the proposed technique.
	Poster THPAB191 [0.846 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB191
About •	paper received ※ 11 May 2021 paper accepted ※ 29 July 2021 issue date ※ 24 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPAB287	Providing Computing Power for High Level Controllers in MicroTCA-based LLRF Systems via PCI Express Extension	4363
	P. Nonn, A. Eichler, S. Pfeiffer, H. Schlarb, J.H.K. Timm DESY, Hamburg, Germany
	It is possible to connect the PCIe bus of a high performance computer to a MicroTCA crate. This allows the software on the computer to communicate with the modules in the crate, as if they were peripherals of the computer. This article will discuss the use of this feature in respect to accelerator control with a focus on High Level Controllers.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB287
About •	paper received ※ 19 May 2021 paper accepted ※ 26 July 2021 issue date ※ 16 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Subsystem Level Data Acquisition for the Optical Synchronization System at European XFEL

2167

M. Schütte, A. Eichler, T. Lamb, V. Rybnikov, H. Schlarb, T. Wilksen
DESY, Hamburg, Germany

The optical synchronization system for the European X-Ray Free-Electron Laser provides sub-10 femtosecond timing precision * for the accelerator subsystems and experiments. This is achieved by phase locking a mode-locked laser oscillator to the main RF reference and distributing the optical pulse train carrying the time information via actively propagation-time stabilized optical fibers to multiple end-stations. Making up roughly one percent of the entire European XFEL, it is the first subsystem to receive a large-scale data acquisition system [2] for storing not just hand-selected information, but in fact all diagnostic, monitoring, and configuration data relevant to the optical synchronization available from the distributed control system infrastructure. A minimum of 100 TB per year may be stored in a persistent archive for long-term health monitoring and data mining whereas excess data is stored in a short-term ring buffer for high-resolution fault analysis and feature extraction algorithm development. This paper describes scale, challenges and first experiences from the optical synchronization data acquisition system.
* S. Schulz et al., "Few-Femtosecond Facility-Wide Sync. of the European XFEL," in Proc. FEL’19
** T. Wilksen et al., "A Bunch-Sync. DAQ System for the European XFEL," in Proc. ICALEPCS’17

Poster TUPAB291 [0.281 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB291

About •

paper received ※ 14 May 2021 paper accepted ※ 17 June 2021 issue date ※ 24 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPAB298

First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT

2182

A. Eichler, F. Burkart, J. Kaiser, W. Kuropka, O. Stein
DESY, Hamburg, Germany
E. Bründermann, A. Santamaria Garcia, C. Xu
KIT, Eggenstein-Leopoldshafen, Germany

Funding: Helmholtz Artificial Cooperation Unit
Reinforcement Learning algorithms have risen in popularity in recent years in the accelerator physics community, showing potential in beam control and in the optimization and automation of tasks in accelerator operation. The Helmholtz AI project "Machine Learning toward Autonomous Accelerators" is a collaboration between DESY and KIT that works on investigating and developing RL applications for the automatic start-up of electron linear accelerators. The work is carried out in parallel at two similar research accelerators: ARES at DESY and FLUTE at KIT, giving the unique opportunity of transfer learning between facilities. One of the first steps of this project is the establishment of a common interface between the simulations and the machine, in order to test and apply various optimization approaches interchangeably between the two accelerators. In this paper we present the first results on the common interface and its application to beam focusing in ARES, and the idea of laser shaping with spatial light modulators at FLUTE.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB298

About •

paper received ※ 19 May 2021 paper accepted ※ 02 August 2021 issue date ※ 17 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB289

Machine Learning Based Spatial Light Modulator Control for the Photoinjector Laser at FLUTE

3332

C. Xu, E. Bründermann, A.-S. Müller, M.J. Nasse, A. Santamaria Garcia, C. Sax, C. Widmann
KIT, Karlsruhe, Germany
A. Eichler
DESY, Hamburg, Germany

Funding: C. Xu acknowledges the support by the DFG-funded Doctoral School "Karlsruhe School of Elementary and Astroparticle Physics: Science and Technology".
FLUTE (Ferninfrarot Linac- und Test-Experiment) at KIT is a compact linac-based test facility for novel accelerator technology and a source of intense THz radiation. FLUTE is designed to provide a wide range of electron bunch charges from the pC- to nC-range, high electric fields up to 1.2 GV/m, and ultra-short THz pulses down to the fs-timescale. The electrons are generated at the RF photoinjector, where the electron gun is driven by a commercial titanium sapphire laser. In this kind of setup the electron beam properties are determined by the photoinjector, but more importantly by the characteristics of the laser pulses. Spatial light modulators can be used to transversely and longitudinally shape the laser pulse, offering a flexible way to shape the laser beam and subsequently the electron beam, influencing the produced THz pulses. However, nonlinear effects inherent to the laser manipulation (transportation, compression, third harmonic generation) can distort the original pulse. In this paper we propose to use machine learning methods to manipulate the laser and electron bunch, aiming to generate tailor-made THz pulses. The method is demonstrated experimentally in a test setup.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB289

About •

paper received ※ 19 May 2021 paper accepted ※ 06 July 2021 issue date ※ 26 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPAB293

The Trip Event Logger for Online Fault Diagnosis at the European XFEL

3344

J.H.K. Timm, J. Branlard, A. Eichler, H. Schlarb
DESY, Hamburg, Germany

The low-level RF (LLRF) system at the European XFEL, DESY, is of major importance for a high-performant and reliable operation. Faults here can jeopardize the overall operation. Therefore, the trip event logger is currently developped, - a fault diagnosis tool to detect errors online, inform the operators and trigger automatic supervisory actions. Further goals are to provide information for a fault tree and event tree analysis as well as a database of labeled faulty data sets for offline analysis. The tool is based on the C++ framework ChimeraTK Application Core. With this close interconnection to the control system it is possible not only to monitor but also to intervene as it is of great importance for supervisory tasks. The core of the tool consists of fault analysis modules ranging from simple ones (e.g., limit checking) to advanced ones (model-based, machine learning, etc.). Within this paper the architecture and the implementation of the trip event logger are presented.

Poster WEPAB293 [7.919 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB293

About •

paper received ※ 19 May 2021 paper accepted ※ 02 July 2021 issue date ※ 10 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPAB191

Physics-Enhanced Reinforcement Learning for Optimal Control

4150

A.N. Ivanov, I.V. Agapov, A. Eichler, S. Tomin
DESY, Hamburg, Germany

We propose an approach for incorporating accelerator physics models into reinforcement learning agents. The proposed approach is based on the Taylor mapping technique for simulation of the particle dynamics. The resulting computational graph is represented as a polynomial neural network and embedded into the traditional reinforcement learning agents. The application of the model is demonstrated in a nonlinear simulation model of beam transmission. The comparison of the approach with the traditional numerical optimization as well as neural networks based agents demonstrates better convergence of the proposed technique.

Poster THPAB191 [0.846 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB191

About •

paper received ※ 11 May 2021 paper accepted ※ 29 July 2021 issue date ※ 24 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPAB287

Providing Computing Power for High Level Controllers in MicroTCA-based LLRF Systems via PCI Express Extension

4363

P. Nonn, A. Eichler, S. Pfeiffer, H. Schlarb, J.H.K. Timm
DESY, Hamburg, Germany

It is possible to connect the PCIe bus of a high performance computer to a MicroTCA crate. This allows the software on the computer to communicate with the modules in the crate, as if they were peripherals of the computer. This article will discuss the use of this feature in respect to accelerator control with a focus on High Level Controllers.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB287

About •

paper received ※ 19 May 2021 paper accepted ※ 26 July 2021 issue date ※ 16 August 2021

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)