IBIC2019 - List of Keywords (damping)

Paper	Title	Other Keywords	Page
MOPP031	Optimisation of the ISIS Proton Synchrotron Experimental Damping System	kicker, synchrotron, feedback, betatron	167
	A. Pertica, D.W. Posthuma de Boer, R.E. Williamson STFC/RAL/ISIS, Chilton, Didcot, Oxon, United Kingdom J. Komppula CERN, Meyrin, Switzerland
	The ISIS Neutron and Muon Source, located in the UK, consists of a H⁻ linear accelerator, a rapid cycling proton synchrotron and two extraction lines delivering protons onto heavy metal targets. One of the limiting factors for achieving higher intensities in the accelerator is the head-tail instability present in the synchrotron, around 2ms after injection. In order to mitigate this instability, an experimental damping system is being developed for the ISIS synchrotron. Initial tests using a split electrode BPM as a pickup and a ferrite loaded kicker as a damper showed positive results. This paper describes the different developments made to the damping system and planned improvements to optimize its performance for use in normal operations.
	Poster MOPP031 [1.557 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-MOPP031
About •	paper received ※ 04 September 2019 paper accepted ※ 09 September 2019 issue date ※ 10 November 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPP018	Synchrotron Radiation Monitor for SuperKEKB Damping Ring in Phase-III Operation	operation, injection, positron, MMI	336
	H. Ikeda, J.W. Flanagan, H. Fukuma, H. Sugimoto, M. Tobiyama KEK, Ibaraki, Japan
	The SuperKEKB damping ring (DR) commissioned in March 2019, before main ring (MR) Phase-III operation. The design luminosity of SuperKEKB is 40 times that of KEKB with high current and low emittance. We constructed the DR in order to deliver a low-emittance positron beam. A synchrotron radiation monitor (SRM) was installed for beam diagnostics at the DR. Streak camera and gated camera were used for measurement of the damping time and the beam size. This paper shows the design of DR SRM and the result of the measurement.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-TUPP018
About •	paper received ※ 04 September 2019 paper accepted ※ 08 September 2019 issue date ※ 10 November 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPP040	Digital Cameras for Photon Diagnostics at the Advanced Photon Source	controls, injection, detector, diagnostics	425
	K.P. Wootton, N.D. Arnold, W. Berg, T. Fors, N. Sereno, H. Shang, G. Shen, S.E. Shoaf, B.X. Yang ANL, Lemont, Illinois, USA
	Funding: This research used resources of the Advanced Photon Source, operated for the U.S. Department of Energy Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. Cameras can be a very useful accelerator diagnostic, particularly because an image of the beam distribution can be quickly interpreted by human operators, and increasingly can serve as an input to machine learning algorithms. We present an implementation of digital cameras for triggered photon diagnostics at the Advanced Photon Source using the areaDetector framework in the Experimental Physics and Industrial Controls System. Beam size measurements from the synchrotron light monitors in the Particle Accumulator Ring using the new architecture are presented.
	Poster TUPP040 [0.708 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-TUPP040
About •	paper received ※ 04 September 2019 paper accepted ※ 08 September 2019 issue date ※ 10 November 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPP021	Machine Learning Image Processing Technology Application in Bunch Longitudinal Phase Data Information Extraction	network, injection, synchrotron, SRF	568
	X.Y. Xu, Y.M. Zhou SINAP, Shanghai, People’s Republic of China Y.B. Leng, Y.M. Zhou SSRF, Shanghai, People’s Republic of China X.Y. Xu University of Chinese Academy of Sciences, Beijing, People’s Republic of China
	To achieve the bunch-by-bunch longitudinal phase measurement, Shanghai Synchrotron Radiation Facility (SSRF) has developed a high resolution measurement system. We used this measurement system to study the injection transient process, and obtained the longitudinal phase of the refilled bunch and the longitudinal phase of the original stored bunch. A large number of parameters of the synchronous damping oscillation are included in this large amount of longitudinal phase data, which are important for the evaluation of machine state and bunch stability. The multi-turn phase data of a multi-bunch is a large two-dimensional array that can be converted into an image. The convolutional neural network (CNN) is a machine learning model with strong capabilities in image processing. We hope to use the convolutional neural network to process the longitudinal phase two-dimensional array data, and extract important parameters such as the oscillation amplitude and the synchrotron damping time.
	Poster WEPP021 [1.292 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-WEPP021
About •	paper received ※ 23 August 2019 paper accepted ※ 10 September 2019 issue date ※ 10 November 2019
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MOPP031

Optimisation of the ISIS Proton Synchrotron Experimental Damping System

kicker, synchrotron, feedback, betatron

167

A. Pertica, D.W. Posthuma de Boer, R.E. Williamson
STFC/RAL/ISIS, Chilton, Didcot, Oxon, United Kingdom
J. Komppula
CERN, Meyrin, Switzerland

The ISIS Neutron and Muon Source, located in the UK, consists of a H⁻ linear accelerator, a rapid cycling proton synchrotron and two extraction lines delivering protons onto heavy metal targets. One of the limiting factors for achieving higher intensities in the accelerator is the head-tail instability present in the synchrotron, around 2ms after injection. In order to mitigate this instability, an experimental damping system is being developed for the ISIS synchrotron. Initial tests using a split electrode BPM as a pickup and a ferrite loaded kicker as a damper showed positive results. This paper describes the different developments made to the damping system and planned improvements to optimize its performance for use in normal operations.

Poster MOPP031 [1.557 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-MOPP031

About •

paper received ※ 04 September 2019 paper accepted ※ 09 September 2019 issue date ※ 10 November 2019

Export •

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

TUPP018

Synchrotron Radiation Monitor for SuperKEKB Damping Ring in Phase-III Operation

operation, injection, positron, MMI

336

H. Ikeda, J.W. Flanagan, H. Fukuma, H. Sugimoto, M. Tobiyama
KEK, Ibaraki, Japan

The SuperKEKB damping ring (DR) commissioned in March 2019, before main ring (MR) Phase-III operation. The design luminosity of SuperKEKB is 40 times that of KEKB with high current and low emittance. We constructed the DR in order to deliver a low-emittance positron beam. A synchrotron radiation monitor (SRM) was installed for beam diagnostics at the DR. Streak camera and gated camera were used for measurement of the damping time and the beam size. This paper shows the design of DR SRM and the result of the measurement.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-TUPP018

About •

paper received ※ 04 September 2019 paper accepted ※ 08 September 2019 issue date ※ 10 November 2019

Export •

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

TUPP040

Digital Cameras for Photon Diagnostics at the Advanced Photon Source

controls, injection, detector, diagnostics

425

K.P. Wootton, N.D. Arnold, W. Berg, T. Fors, N. Sereno, H. Shang, G. Shen, S.E. Shoaf, B.X. Yang
ANL, Lemont, Illinois, USA

Funding: This research used resources of the Advanced Photon Source, operated for the U.S. Department of Energy Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357.
Cameras can be a very useful accelerator diagnostic, particularly because an image of the beam distribution can be quickly interpreted by human operators, and increasingly can serve as an input to machine learning algorithms. We present an implementation of digital cameras for triggered photon diagnostics at the Advanced Photon Source using the areaDetector framework in the Experimental Physics and Industrial Controls System. Beam size measurements from the synchrotron light monitors in the Particle Accumulator Ring using the new architecture are presented.

Poster TUPP040 [0.708 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-TUPP040

About •

paper received ※ 04 September 2019 paper accepted ※ 08 September 2019 issue date ※ 10 November 2019

Export •

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

WEPP021

Machine Learning Image Processing Technology Application in Bunch Longitudinal Phase Data Information Extraction

network, injection, synchrotron, SRF

568

X.Y. Xu, Y.M. Zhou
SINAP, Shanghai, People’s Republic of China
Y.B. Leng, Y.M. Zhou
SSRF, Shanghai, People’s Republic of China
X.Y. Xu
University of Chinese Academy of Sciences, Beijing, People’s Republic of China

To achieve the bunch-by-bunch longitudinal phase measurement, Shanghai Synchrotron Radiation Facility (SSRF) has developed a high resolution measurement system. We used this measurement system to study the injection transient process, and obtained the longitudinal phase of the refilled bunch and the longitudinal phase of the original stored bunch. A large number of parameters of the synchronous damping oscillation are included in this large amount of longitudinal phase data, which are important for the evaluation of machine state and bunch stability. The multi-turn phase data of a multi-bunch is a large two-dimensional array that can be converted into an image. The convolutional neural network (CNN) is a machine learning model with strong capabilities in image processing. We hope to use the convolutional neural network to process the longitudinal phase two-dimensional array data, and extract important parameters such as the oscillation amplitude and the synchrotron damping time.

Poster WEPP021 [1.292 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IBIC2019-WEPP021

About •

paper received ※ 23 August 2019 paper accepted ※ 10 September 2019 issue date ※ 10 November 2019

Export •

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