HIAT2022 - List of Keywords (quadrupole)

Paper	Title	Other Keywords	Page
TU2C4	Beam Tuning Automation Activities at TRIUMF	controls, linac, framework, database	52
	S. Kiy, F. Ames, A. Andres, R.A. Baartman, H. Bagri, K. Ezawa, W. Fedorko, P.M. Jung, O.K. Kester, K.E. Lucow, J. Nasser, T. Planche, S.D. Rädel, B.E. Schultz, O. Shelbaya, B. Stringer, D.C. Thomson, D.Y. Wang, K.C. Wu TRIUMF, Vancouver, Canada J.A. Adegun UVIC, Victoria, Canada
	Funding: This activity is supported by MITACS IT23740 The particle accelerator complex at TRIUMF provides beams for secondary particle production including rare isotopes. The post acceleration of rare isotope ions demands frequent changes of beam properties like energy and changes of the ion species in terms of isotope and charge state. To facilitate these changes to beam properties and species, a High Level Applications (HLA) framework has been developed that provides the essential elements necessary for app development: access to sophisticated envelope simulations and any necessary beamline data, integration with the control system, version control, deployment and issue tracking, and training materials. With this framework, one can automate collection of beam data and subsequently pull that data into a model which then outputs the necessary adjustments to beam optics. Tuning based on this method is model coupled accelerator tuning (MCAT) and includes pursuits like the training of machine learning (ML) agents to optimize corrections benders. A summary of the framework will be provided followed by a description of the different applications of the MCAT method - both those currently being pursued, and those envisioned for the future.
	Slides TU2C4 [1.890 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TU2C4
About •	Received ※ 21 June 2022 — Revised ※ 30 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUP05	Prototype Room Temperature Quadrupole Chamber with Cryogenic Installations	cryogenics, vacuum, simulation, synchrotron	75
	S. Aumüller, L.H.J. Bozyk, P.J. Spiller GSI, Darmstadt, Germany K. Blaum MPI-K, Heidelberg, Germany
	The synchrotron SIS100 at FAIR accelerator complex at the GSI Helmholtzzentrum will generate heavy ion beams of ultimate intensities. As medium charge states have to be used, the probability for charge exchange in collisions with residual gas particles of such ions is much lager than for higher charge states. In the last years, several measures have lowered the residual gas density to extreme high vacuum conditions. For example 55% of the circumference of SIS18 have already been coated with NEG, which provides high and distributed pumping speed. Nevertheless, this coating does not pump nobel and nobel-like components, which have very high ionization cross sections. A cryogenic environment at e.g. 50-80K provides a high pumping speed for all heavy residual gas particles. The only typical residual gas particle that cannot be pumped at this temperature is hydrogen. With the pumping speed of an additional NEG coating in these areas, the pumping will be optimized for all residual gas particles. The installation of cryogenic installations in the existing room temperature synchrotron SIS18 at GSI has been investigated. Measurements on a prototype chamber and simulations of SIS18 with cryogenic installations based on these measurements are presented.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TUP05
About •	Received ※ 21 June 2022 — Revised ※ 30 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUP14	Study of Injection Line of the Cyclotrons C70XP of Arronax	emittance, injection, cyclotron, experiment	100
	T. Durand, R. Bellamy, C. Castel, F. Haddad, C. Koumeir, F. Poirier, H. Trichet Cyclotron ARRONAX, Saint-Herblain, France T. Adam, P.G. Graehling, M. Heine, C. Maazouzi, F.R. Osswald IPHC, Strasbourg Cedex 2, France F. Haddad SUBATECH, Nantes, France
	Funding: Work supported by grants from the French National Agency for Research, Arronax-Plus n°ANR-11-EQPX-0004, IRON n°ANR-11-LABX-18-01 and Next n°ANR-16-IDE-0007 and PhD scholarship from the IN2P3/CNRS. The cyclotron C70XP is an accelerator built for the production of non-conventional radionuclides for nuclear medicine, research in physics, radio-chemistry and biology. Its injection section has been designed for 4 types of ions (HH⁺, D-, He2+ & H⁻), 3 types of ions reach the end of the beamline (H⁺, He2+ & D⁺) at the maximum energy of 70 MeV (H⁻ & He2+). It is important that regular and standard runs provide similar beam features with a good emittance quality. An investigation, focused on the beam in the injection, cover beam measurements and potential beam geometry constraints. The beam transverse characteristics in the injection line has been studied with an Allison-type emittance meter and a simple instrumented collimator installed inside the injection line . With these 2 devices, it is scrutinized how the beam emittance evolves as a function of settings of the injection magnets and the source parameters . Dependencies found between the emittance, beam hotspots and tunings are discussed, as well as the protection performed by the collimator. Future of this work with a potential collimator design is introduced. F.Poirier and al., ’The Injection and Chopper-Based System at Arronax C70XP Cyclotron’ **F. Poirier and al., ’Installation, Use and Follow-Up of an Emittance-Meter at the Arronax Cyclotron 70XP’
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TUP14
About •	Received ※ 21 June 2022 — Revised ※ 27 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TH1I2	Reinforcement Learning and Bayesian Optimization for Ion Linac Operations	controls, simulation, rfq, experiment	130
	J.L. Martinez Marin, B.R. Blomberg, K.J. Bunnell, G.M. Dunn, E. Letcher, B. Mustapha, D. Stanton ANL, Lemont, Illinois, USA
	Funding: This work was supported by the U.S. Department of Energy, under Contract No. DE-AC02-06CH11357. This research used the ATLAS facility, which is a DOE Office of Nuclear Physics User Facility. The use of artificial intelligence can significantly reduce the time needed to tune an accelerator system such as the Argonne Tandem Linear Accelerator System (ATLAS) where a new beam is tuned once or twice a week. After establishing automatic data collection procedures and having analysed the data, machine learning models were developed and tested to tune subsections of the linac. Models based on Reinforcement Learning (RL) and Bayesian Optimization (BO) were developed, their respec-tive results are discussed and compared. RL and BO are well known AI techniques, often used for control systems. The results were obtained for a subsection of ATLAS that contains complex elements such as the radio-frequency quadrupole (RFQ). The models will be later generalized to the whole ATLAS linac, and similar models can be devel-oped for any accelerator with a modern control system.
	Slides TH1I2 [4.617 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TH1I2
About •	Received ※ 09 July 2022 — Revised ※ 10 August 2022 — Accepted ※ 19 September 2022 — Issue date ※ 19 September 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TH3C3	Recent UNILAC Upgrade Activities	operation, heavy-ion, rfq, linac	166
	U. Scheeler, W.A. Barth, M. Miski-Oglu, H. Vormann, M. Vossberg, S. Yaramyshev GSI, Darmstadt, Germany W.A. Barth, M. Miski-Oglu, S. Yaramyshev HIM, Mainz, Germany W.A. Barth KPH, Mainz, Germany
	The GSI UNILAC is the section of the GSI accelerator facility that has been in operation the longest. UNILAC is able to accelerate ions from hydrogen to ura-nium up to 20 MeV (p⁺) and 13 MeV/u (uranium). The main focus of the recent upgrade measures is to meet the FAIR requirements and to provide reliable and long term beam operation conditions. Besides post stripper upgrade and upgrade of the UNILAC controls, a particular atten-tion is paid to improve the performance of the High Current Injector (HSI) [1-7] and to intensify spare part management for the ageing accelerator. In order to en-sure operational reliability, the main focus lies on exten-sive spare part management and replacement of outdated equipment. Modified beam dynamics design for the frontend system and the use of advanced technologies are needed to improve the UNILAC performance. Among other things, a modified Low and Medium Energy Beam Transport section design for the HSI and installation of reliable (non-destructive) high intensity beam diagnos-tics devices are in progress. This paper addresses the status of current development efforts and specific plans for the UNILAC upgrade.
	Slides TH3C3 [1.595 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TH3C3
About •	Received ※ 20 June 2022 — Revised ※ 28 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

TU2C4

Beam Tuning Automation Activities at TRIUMF

controls, linac, framework, database

52

S. Kiy, F. Ames, A. Andres, R.A. Baartman, H. Bagri, K. Ezawa, W. Fedorko, P.M. Jung, O.K. Kester, K.E. Lucow, J. Nasser, T. Planche, S.D. Rädel, B.E. Schultz, O. Shelbaya, B. Stringer, D.C. Thomson, D.Y. Wang, K.C. Wu
TRIUMF, Vancouver, Canada
J.A. Adegun
UVIC, Victoria, Canada

Funding: This activity is supported by MITACS IT23740
The particle accelerator complex at TRIUMF provides beams for secondary particle production including rare isotopes. The post acceleration of rare isotope ions demands frequent changes of beam properties like energy and changes of the ion species in terms of isotope and charge state. To facilitate these changes to beam properties and species, a High Level Applications (HLA) framework has been developed that provides the essential elements necessary for app development: access to sophisticated envelope simulations and any necessary beamline data, integration with the control system, version control, deployment and issue tracking, and training materials. With this framework, one can automate collection of beam data and subsequently pull that data into a model which then outputs the necessary adjustments to beam optics. Tuning based on this method is model coupled accelerator tuning (MCAT) and includes pursuits like the training of machine learning (ML) agents to optimize corrections benders. A summary of the framework will be provided followed by a description of the different applications of the MCAT method - both those currently being pursued, and those envisioned for the future.

Slides TU2C4 [1.890 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TU2C4

About •

Received ※ 21 June 2022 — Revised ※ 30 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022

Cite •

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

TUP05

Prototype Room Temperature Quadrupole Chamber with Cryogenic Installations

cryogenics, vacuum, simulation, synchrotron

75

S. Aumüller, L.H.J. Bozyk, P.J. Spiller
GSI, Darmstadt, Germany
K. Blaum
MPI-K, Heidelberg, Germany

The synchrotron SIS100 at FAIR accelerator complex at the GSI Helmholtzzentrum will generate heavy ion beams of ultimate intensities. As medium charge states have to be used, the probability for charge exchange in collisions with residual gas particles of such ions is much lager than for higher charge states. In the last years, several measures have lowered the residual gas density to extreme high vacuum conditions. For example 55% of the circumference of SIS18 have already been coated with NEG, which provides high and distributed pumping speed. Nevertheless, this coating does not pump nobel and nobel-like components, which have very high ionization cross sections. A cryogenic environment at e.g. 50-80K provides a high pumping speed for all heavy residual gas particles. The only typical residual gas particle that cannot be pumped at this temperature is hydrogen. With the pumping speed of an additional NEG coating in these areas, the pumping will be optimized for all residual gas particles. The installation of cryogenic installations in the existing room temperature synchrotron SIS18 at GSI has been investigated. Measurements on a prototype chamber and simulations of SIS18 with cryogenic installations based on these measurements are presented.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TUP05

About •

Received ※ 21 June 2022 — Revised ※ 30 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022

Cite •

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

TUP14

Study of Injection Line of the Cyclotrons C70XP of Arronax

emittance, injection, cyclotron, experiment

100

T. Durand, R. Bellamy, C. Castel, F. Haddad, C. Koumeir, F. Poirier, H. Trichet
Cyclotron ARRONAX, Saint-Herblain, France
T. Adam, P.G. Graehling, M. Heine, C. Maazouzi, F.R. Osswald
IPHC, Strasbourg Cedex 2, France
F. Haddad
SUBATECH, Nantes, France

Funding: Work supported by grants from the French National Agency for Research, Arronax-Plus n°ANR-11-EQPX-0004, IRON n°ANR-11-LABX-18-01 and Next n°ANR-16-IDE-0007 and PhD scholarship from the IN2P3/CNRS.
The cyclotron C70XP is an accelerator built for the production of non-conventional radionuclides for nuclear medicine, research in physics, radio-chemistry and biology. Its injection section has been designed for 4 types of ions (HH⁺, D-, He2+ & H⁻), 3 types of ions reach the end of the beamline (H⁺, He2+ & D⁺) at the maximum energy of 70 MeV (H⁻ & He2+). It is important that regular and standard runs provide similar beam features with a good emittance quality. An investigation, focused on the beam in the injection, cover beam measurements and potential beam geometry constraints. The beam transverse characteristics in the injection line has been studied with an Allison-type emittance meter and a simple instrumented collimator installed inside the injection line *. With these 2 devices, it is scrutinized how the beam emittance evolves as a function of settings of the injection magnets and the source parameters **. Dependencies found between the emittance, beam hotspots and tunings are discussed, as well as the protection performed by the collimator. Future of this work with a potential collimator design is introduced.
*F.Poirier and al., ’The Injection and Chopper-Based System at Arronax C70XP Cyclotron’
**F. Poirier and al., ’Installation, Use and Follow-Up of an Emittance-Meter at the Arronax Cyclotron 70XP’

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TUP14

About •

Received ※ 21 June 2022 — Revised ※ 27 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022

Cite •

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

TH1I2

Reinforcement Learning and Bayesian Optimization for Ion Linac Operations

controls, simulation, rfq, experiment

130

J.L. Martinez Marin, B.R. Blomberg, K.J. Bunnell, G.M. Dunn, E. Letcher, B. Mustapha, D. Stanton
ANL, Lemont, Illinois, USA

Funding: This work was supported by the U.S. Department of Energy, under Contract No. DE-AC02-06CH11357. This research used the ATLAS facility, which is a DOE Office of Nuclear Physics User Facility.
The use of artificial intelligence can significantly reduce the time needed to tune an accelerator system such as the Argonne Tandem Linear Accelerator System (ATLAS) where a new beam is tuned once or twice a week. After establishing automatic data collection procedures and having analysed the data, machine learning models were developed and tested to tune subsections of the linac. Models based on Reinforcement Learning (RL) and Bayesian Optimization (BO) were developed, their respec-tive results are discussed and compared. RL and BO are well known AI techniques, often used for control systems. The results were obtained for a subsection of ATLAS that contains complex elements such as the radio-frequency quadrupole (RFQ). The models will be later generalized to the whole ATLAS linac, and similar models can be devel-oped for any accelerator with a modern control system.

Slides TH1I2 [4.617 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TH1I2

About •

Received ※ 09 July 2022 — Revised ※ 10 August 2022 — Accepted ※ 19 September 2022 — Issue date ※ 19 September 2022

Cite •

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

TH3C3

Recent UNILAC Upgrade Activities

operation, heavy-ion, rfq, linac

166

U. Scheeler, W.A. Barth, M. Miski-Oglu, H. Vormann, M. Vossberg, S. Yaramyshev
GSI, Darmstadt, Germany
W.A. Barth, M. Miski-Oglu, S. Yaramyshev
HIM, Mainz, Germany
W.A. Barth
KPH, Mainz, Germany

The GSI UNILAC is the section of the GSI accelerator facility that has been in operation the longest. UNILAC is able to accelerate ions from hydrogen to ura-nium up to 20 MeV (p⁺) and 13 MeV/u (uranium). The main focus of the recent upgrade measures is to meet the FAIR requirements and to provide reliable and long term beam operation conditions. Besides post stripper upgrade and upgrade of the UNILAC controls, a particular atten-tion is paid to improve the performance of the High Current Injector (HSI) [1-7] and to intensify spare part management for the ageing accelerator. In order to en-sure operational reliability, the main focus lies on exten-sive spare part management and replacement of outdated equipment. Modified beam dynamics design for the frontend system and the use of advanced technologies are needed to improve the UNILAC performance. Among other things, a modified Low and Medium Energy Beam Transport section design for the HSI and installation of reliable (non-destructive) high intensity beam diagnos-tics devices are in progress. This paper addresses the status of current development efforts and specific plans for the UNILAC upgrade.

Slides TH3C3 [1.595 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-HIAT2022-TH3C3

About •

Received ※ 20 June 2022 — Revised ※ 28 June 2022 — Accepted ※ 01 July 2022 — Issue date ※ 10 August 2022

Cite •

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