IPAC2022 - List of Authors (Velotti, F.M.)

Paper	Title	Page
TUPOST040	Automated Intensity Optimisation Using Reinforcement Learning at LEIR	941
	N. Madysa, R. Alemany-Fernández, N. Biancacci, B. Goddard, V. Kain, F.M. Velotti CERN, Meyrin, Switzerland
	High intensities in the CERN Low Energy Ion Ring (LEIR) are achieved by stacking up to seven consecutive multi-turn injections from Linac3. Two inclined septa combined with a collapsing horizontal orbit bump allow a 6-D phase space painting via a linearly ramped mean momentum along the Linac3 pulse and injection at high dispersion. The beam is cooled and dragged longitudinally via electron cooling (e-cooling) into a stacking momentum. For optimal accumulation, the electron energy and trajectory need to match the ion energy and orbit at the e-cooler section. In this paper, a reinforcement learning (RL) agent is trained to adjust various e-cooler and Linac3 parameters to maximise the intensity at the end of the injection plateau. Variational Auto-Encoders (VAE) are used to compress longitudinal Schottky spectra into a compact representation as input for the RL agent. The RL agent is pre-trained on a surrogate model of the LEIR e-cooling dynamics, which in turn is learned from the data collected for the training of the VAE. The performance of the VAE, the surrogate model, and the RL agent is investigated in this paper. An overview of planned tests in the upcoming LEIR runs is given.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST040
About •	Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 10 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPOST044	Fortune Telling or Physics Prediction? Deep Learning for On-Line Kicker Temperature Forecasting	957
	F.M. Velotti, M.J. Barnes, B. Goddard, I. Revuelta CERN, Meyrin, Switzerland
	The injection kicker system MKP of the Super Proton Synchrotron SPS at CERN is composed of 4 kicker tanks. The MKP-L tank provides additional kick needed to inject 26 GeV Large Hadron Collider LHC 25 ns type beams. This device has been a limiting factor for operation with high intensity, due to the magnet’s broadband beam coupling impedance and consequent beam induced heating. To optimise the usage of the SPS and avoid idle (kicker cooling) time, studies were conducted to develop a recurrent deep learning model that could predict the measured temperature evolution of the MKP-L, using the beam conditions and temperature history as input. In a second stage, the ferrite temperature is also estimated putting together the external temperature predictions from accurate thermo-mechanical simulations of the kicker magnet. In this paper, the methodology is described and details of the neural network architecture used, together with the implementation of an ad-hoc loss function, are given. The results applied to the SPS 2021 operational data are presented.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST044
About •	Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 18 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPOST045	Overview of the Machine Learning and Numerical Optimiser Applications on Beam Transfer Systems for LHC and Its Injectors	961
	F.M. Velotti, M.J. Barnes, E. Carlier, Y. Dutheil, M.A. Fraser, B. Goddard, N. Magnin, R.L. Ramjiawan, E. Renner, P. Van Trappen CERN, Meyrin, Switzerland E. Waagaard Uppsala University, Uppsala, Sweden
	Machine learning and numerical optimisation algorithms are getting more and more popular in the accelerator physics community and, thanks to the computing power available, their application in daily operation more likely. In the CERN accelerator complex, and specifically on the beam transfer systems, many promising exploitation of these numerical tools have been put in place in the last years. Some of the state-of-the-art machine learning models have been explored and used to solve problems that were never fully addressed in the past. In this paper, the most recent results of application of machine learning and numerical optimisation for injection, extraction and transfer of beam from machine and to experimental areas are presented. An overview of the possible next steps and shortcomings is finally discussed.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST045
About •	Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 10 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEIYGD1	Achievements and Performance Prospects of the Upgraded LHC Injectors	1610
	V. Kain, S.C.P. Albright, R. Alemany-Fernández, M.E. Angoletta, F. Antoniou, T. Argyropoulos, F. Asvesta, B. Balhan, M.J. Barnes, D. Barrientos, H. Bartosik, P. Baudrenghien, G. Bellodi, N. Biancacci, A. Boccardi, J.C.C.M. Borburgh, C. Bracco, E. Carlier, D.G. Cotte, J. Coupard, H. Damerau, G.P. Di Giovanni, A. Findlay, M.A. Fraser, A. Funken, B. Goddard, G. Hagmann, K. Hanke, A. Huschauer, M. Jaussi, I. Karpov, T. Koevener, D. Küchler, J.-B. Lallement, A. Lasheen, T.E. Levens, K.S.B. Li, A.M. Lombardi, N. Madysa, E. Mahner, M. Meddahi, L. Mether, B. Mikulec, J.C. Molendijk, E. Montesinos, D. Nisbet, F.-X. Nuiry, G. Papotti, K. Paraschou, F. Pedrosa, T. Prebibaj, S. Prodon, D. Quartullo, E. Renner, F. Roncarolo, G. Rumolo, B. Salvant, M. Schenk, R. Scrivens, E.N. Shaposhnikova, P.K. Skowroński, A. Spierer, F. Tecker, D. Valuch, F.M. Velotti, R. Wegner, C. Zannini CERN, Meyrin, Switzerland
	To provide HL-LHC performance, the CERN LHC injector chain underwent a major upgrade during an almost 2-year-long shutdown. In the first half of 2021 the injectors were gradually re-started with the aim to reach at least pre-shutdown parameters for LHC as well as for fixed target beams. The strategy of the commissioning across the complex, a summary of the many challenges and finally the achievements will be presented. Several lessons were learned and have been integrated to define the strategy for the performance ramp-up over the coming years. Remaining limitations and prospects for LHC beam parameters at the exit of the LHC injector chain in the years to come will be discussed. Finally, the emerging need for improved operability of the CERN complex will be addressed, with a description of the first efforts to meet the availability and flexibility requirements of the HL-LHC era while at the same time maximizing fixed target physics output.
	Slides WEIYGD1 [5.905 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEIYGD1
About •	Received ※ 08 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 09 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPOST013	Exploitation of Crystal Shadowing via Multi-Crystal Array, Optimisers and Reinforcement Learning	1707
	F.M. Velotti, M. Di Castro, L.S. Esposito, M.A. Fraser, S.S. Gilardoni, B. Goddard, V. Kain, E. Matheson CERN, Meyrin, Switzerland
	The CERN Super Proton Synchrotron (SPS) routinely delivers proton and heavy ion beams to the North experimental Area (NA) in the form of 4.8 s spills. To produce such a long flux of particles, resonant third integer slow extraction is used, which, by design, foresees primary beam lost on the electrostatic septum wires to separate circulating from extracted beam. Shadowing with thin bent crystal has been proposed and successfully tested in the SPS, as detailed in . In 2021, a thin crystal was used for physics production showing results compatible with what measured during early testing. In this paper, the results from the 2021 physics run are presented also comparing particle losses at extraction with previous operational years. The setting up of the crystal using numerical optimisers is detailed, with possible implementation of reinforcement learning (RL) agents to improve the setting up time. Finally, the full exploitation of crystal shadowing via multi-array crystals is discussed, together with the performance reach in the SPS. F.Velotti, et. al, "Septum shadowing by means of a bent crystal to reduce slow extraction beam loss", Phys. Rev. Accel. Beams 22, 093502 - Published 27 September 2019*
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST013
About •	Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 02 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPOST014	Studies on Pre-Computation of SPS-to-LHC Transfer Line Corrections	1711
	C. Bracco, F.M. Velotti CERN, Meyrin, Switzerland
	The injection process in the LHC gives a non-negligible contribution to the turnaround time between two consecutive physics fills. Mainly due to orbit drifts in the SPS, the steering of the SPS-to-LHC transfer lines (TL) had to be regularly performed in view of minimising injection oscillations and losses, which otherwise would trigger beam dumps. Moreover, for machine protection purposes, a maximum of twelve bunches had to be injected after any TL steering to validate the actual applied corrections. This implied at several occasions the need to interrupt a fill to steer the lines and introduced a further delay between fills. Studies were performed to evaluate the option of pre-calculating the required TL corrections based on SPS orbit measurements during the LHC magnet ramp down and the reconstruction of the beam position and angle at the SPS extraction point.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST014
About •	Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 16 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPOST015	Implementation of a Tune Sweep Slow Extraction with Constant Optics at MedAustron	1715
	P.A. Arrutia Sota, M.A. Fraser, B. Goddard, V. Kain, F.M. Velotti CERN, Meyrin, Switzerland P. Burrows JAI, Oxford, United Kingdom A. De Franco QST Rokkasho, Aomori, Japan F. Kuehteubl, M.T.F. Pivi, D.A. Prokopovich EBG MedAustron, Wr. Neustadt, Austria
	Conventional slow extraction driven by a tune sweep perturbs the optics and changes the presentation of the beam separatrix to the extraction septum during the spill. The constant optics slow extraction (COSE) technique, recently developed and deployed operationally at the CERN Super Proton Synchrotron to reduce beam loss on the extraction septum, was implemented at MedAustron to facilitate extraction with a tune sweep of operational beam quality. COSE fixes the optics of the extracted beam by scaling all machine settings with the beam rigidity following the extracted beam’s momentum. In this contribution the implementation of the COSE extraction technique is described before it is compared to the conventional tune sweep and operational betatron core driven cases using both simulations and recent measurements.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST015
About •	Received ※ 07 June 2022 — Revised ※ 16 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 18 June 2022
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WEPOPT055	Linac3, LEIR and PS Performance with Ions in 2021 and Prospects for 2022	1983
	N. Biancacci, S.C.P. Albright, R. Alemany-Fernández, D. Alves, M.E. Angoletta, D. Barrientos, H. Bartosik, G. Bellodi, S.B. Bertolo, D. Bodart, M. Bozzolan, H. Damerau, F.D.L. Di Lorenzo, A. Frassier, D. Gamba, A. Huschauer, S. Jensen, V. Kain, T. Koevener, G. Kotzian, D. Küchler, A. Lasheen, G. Le Godec, T.E. Levens, N. Madysa, E. Mahner, O. Marqversen, C.M. Mastrostefano, P.D. Meruga, C. Mutin, M. O’Neil, G. Piccinini, R. Scrivens, P.S. Solvang, D. Valuch, F.M. Velotti, R. Wegner, C. Wetton, M. Zampetakis CERN, Meyrin, Switzerland
	CERN accelerators underwent a period of long shutdown from the end of 2018 to 2020. During this time frame, significant hardware and software upgrades have been put in place to increase the performance of both proton and ion accelerator chains in the High Luminosity LHC era. In the context of the CERN lead ion chain, 2021 has been mainly devoted to restore the injectors’ performance and to successfully prove the slip-stacking technique in SPS. In this paper we summarise the key milestones of the ion beam commissioning and the achieved beam performance for the Linac 3 (including the source), LEIR and PS accelerators, together with an outlook on 2022 operation.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOPT055
About •	Received ※ 03 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 17 June 2022
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WEPOTK028	Implementation of RF Channeling at the CERN PS for Spill Quality Improvements	2114
	P.A. Arrutia Sota, H. Damerau, M.A. Fraser, M. Vadai, F.M. Velotti CERN, Meyrin, Switzerland P. Burrows JAI, Oxford, United Kingdom
	Resonant slow extraction from synchrotrons aims at providing constant intensity spills over timescales much longer than the revolution period of the machine. However, the extracted intensity is undesirably modulated by noise on the machine’s power converters with a frequency range of between 50 Hz and a few kHz. The impact of power converter noise can be suppressed by exploiting a Radio Frequency (RF) technique known as empty bucket channelling, which increases the speed at which particles cross the tune resonance boundary. In this contribution the implementation of empty bucket channelling in the CERN Proton Synchrotron (PS) is described via simulation and measurement. The technique was tested with both a resonant RF cavity and an inductive Finemet cavity, which can produce non-sinusoidal waveforms, to significantly reduce the low frequency noise observed on the extracted spill.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOTK028
About •	Received ※ 07 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 22 June 2022
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THPOST039	SPS Beam Dump System (SBDS) Commissioning After Relocation and Upgrade	2530
	P. Van Trappen, E. Carlier, L. Ducimetière, V. Namora, V. Senaj, F.M. Velotti, N. Voumard CERN, Meyrin, Switzerland
	In order to overcome several machine limitations, the SBDS has been relocated from LSS1 (Long Straight Section 1) to LSS5 during LS2 (Long Shutdown 2) with an important upgrade of the extraction kicker installation. An additional vertical deflection kicker magnet (MKDV) was produced and installed while the high voltage (HV) pulse generators have been upgraded by changing gas-discharge switches (thyratrons and ignitrons) to semiconductor stacks operating in oil. Furthermore the horizontal sweep generators have been upgraded to allow for a lower kick strengths. The controls, previously consolidated during LS1, went through an additional light consolidation phase with among others the upgrade of the trigger & retrigger distribution system and the installation of a new fast-interlocks detection system. This paper describes the commissioning without and with beam and elaborates on the measured improvements and encountered problems with corrective mitigations.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-THPOST039
About •	Received ※ 07 June 2022 — Accepted ※ 12 June 2022 — Issue date ※ 15 June 2022
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THPOTK043	Mitigation of High Voltage Breakdown of the Beam Screen of a CERN SPS Injection Kicker Magnet	2868
	M.J. Barnes, W. Bartmann, M. Díaz Zumel, L. Ducimetière, L.M.C. Feliciano, T. Kramer, V. Namora, T. Stadlbauer, D. Standen, P. Trubacova, F.M. Velotti, C. Zannini CERN, Meyrin, Switzerland
	The SPS injection kicker magnets (MKP) were developed in the 1970’s, before beam induced power deposition was considered an issue. These magnets are very lossy from a beam impedance perspective: this is expected to be an issue during SPS operation with the higher intensity beams needed for HL-LHC. A design, with serigraphy applied to an alumina carrier, has been developed to significantly reduce the broadband beam coupling impedance and hence mitigate the heating issues. During high voltage pulse testing there were electrical discharges associated with the serigraphy. Detailed mathematical models have been developed to aid in understanding the transiently induced voltages and to reduce the magnitude and duration of electric field. In this paper, we discuss the solutions implemented to mitigate the electrical discharges while maintaining an adequately low beam-coupling impedance. In addition, the results of high voltage tests are reported. The alumina substrate has a high secondary electron yield and thus electron-cloud could be an issue, with SPS beam, if mitigating measures were not taken: this paper also discusses the measures implemented.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-THPOTK043
About •	Received ※ 07 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 17 June 2022
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Paper

Title

Page

Automated Intensity Optimisation Using Reinforcement Learning at LEIR

941

N. Madysa, R. Alemany-Fernández, N. Biancacci, B. Goddard, V. Kain, F.M. Velotti
CERN, Meyrin, Switzerland

High intensities in the CERN Low Energy Ion Ring (LEIR) are achieved by stacking up to seven consecutive multi-turn injections from Linac3. Two inclined septa combined with a collapsing horizontal orbit bump allow a 6-D phase space painting via a linearly ramped mean momentum along the Linac3 pulse and injection at high dispersion. The beam is cooled and dragged longitudinally via electron cooling (e-cooling) into a stacking momentum. For optimal accumulation, the electron energy and trajectory need to match the ion energy and orbit at the e-cooler section. In this paper, a reinforcement learning (RL) agent is trained to adjust various e-cooler and Linac3 parameters to maximise the intensity at the end of the injection plateau. Variational Auto-Encoders (VAE) are used to compress longitudinal Schottky spectra into a compact representation as input for the RL agent. The RL agent is pre-trained on a surrogate model of the LEIR e-cooling dynamics, which in turn is learned from the data collected for the training of the VAE. The performance of the VAE, the surrogate model, and the RL agent is investigated in this paper. An overview of planned tests in the upcoming LEIR runs is given.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST040

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Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 10 July 2022

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TUPOST044

Fortune Telling or Physics Prediction? Deep Learning for On-Line Kicker Temperature Forecasting

957

F.M. Velotti, M.J. Barnes, B. Goddard, I. Revuelta
CERN, Meyrin, Switzerland

The injection kicker system MKP of the Super Proton Synchrotron SPS at CERN is composed of 4 kicker tanks. The MKP-L tank provides additional kick needed to inject 26 GeV Large Hadron Collider LHC 25 ns type beams. This device has been a limiting factor for operation with high intensity, due to the magnet’s broadband beam coupling impedance and consequent beam induced heating. To optimise the usage of the SPS and avoid idle (kicker cooling) time, studies were conducted to develop a recurrent deep learning model that could predict the measured temperature evolution of the MKP-L, using the beam conditions and temperature history as input. In a second stage, the ferrite temperature is also estimated putting together the external temperature predictions from accurate thermo-mechanical simulations of the kicker magnet. In this paper, the methodology is described and details of the neural network architecture used, together with the implementation of an ad-hoc loss function, are given. The results applied to the SPS 2021 operational data are presented.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST044

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Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 18 June 2022

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TUPOST045

Overview of the Machine Learning and Numerical Optimiser Applications on Beam Transfer Systems for LHC and Its Injectors

961

F.M. Velotti, M.J. Barnes, E. Carlier, Y. Dutheil, M.A. Fraser, B. Goddard, N. Magnin, R.L. Ramjiawan, E. Renner, P. Van Trappen
CERN, Meyrin, Switzerland
E. Waagaard
Uppsala University, Uppsala, Sweden

Machine learning and numerical optimisation algorithms are getting more and more popular in the accelerator physics community and, thanks to the computing power available, their application in daily operation more likely. In the CERN accelerator complex, and specifically on the beam transfer systems, many promising exploitation of these numerical tools have been put in place in the last years. Some of the state-of-the-art machine learning models have been explored and used to solve problems that were never fully addressed in the past. In this paper, the most recent results of application of machine learning and numerical optimisation for injection, extraction and transfer of beam from machine and to experimental areas are presented. An overview of the possible next steps and shortcomings is finally discussed.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST045

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Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 10 July 2022

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

WEIYGD1

Achievements and Performance Prospects of the Upgraded LHC Injectors

1610

V. Kain, S.C.P. Albright, R. Alemany-Fernández, M.E. Angoletta, F. Antoniou, T. Argyropoulos, F. Asvesta, B. Balhan, M.J. Barnes, D. Barrientos, H. Bartosik, P. Baudrenghien, G. Bellodi, N. Biancacci, A. Boccardi, J.C.C.M. Borburgh, C. Bracco, E. Carlier, D.G. Cotte, J. Coupard, H. Damerau, G.P. Di Giovanni, A. Findlay, M.A. Fraser, A. Funken, B. Goddard, G. Hagmann, K. Hanke, A. Huschauer, M. Jaussi, I. Karpov, T. Koevener, D. Küchler, J.-B. Lallement, A. Lasheen, T.E. Levens, K.S.B. Li, A.M. Lombardi, N. Madysa, E. Mahner, M. Meddahi, L. Mether, B. Mikulec, J.C. Molendijk, E. Montesinos, D. Nisbet, F.-X. Nuiry, G. Papotti, K. Paraschou, F. Pedrosa, T. Prebibaj, S. Prodon, D. Quartullo, E. Renner, F. Roncarolo, G. Rumolo, B. Salvant, M. Schenk, R. Scrivens, E.N. Shaposhnikova, P.K. Skowroński, A. Spierer, F. Tecker, D. Valuch, F.M. Velotti, R. Wegner, C. Zannini
CERN, Meyrin, Switzerland

To provide HL-LHC performance, the CERN LHC injector chain underwent a major upgrade during an almost 2-year-long shutdown. In the first half of 2021 the injectors were gradually re-started with the aim to reach at least pre-shutdown parameters for LHC as well as for fixed target beams. The strategy of the commissioning across the complex, a summary of the many challenges and finally the achievements will be presented. Several lessons were learned and have been integrated to define the strategy for the performance ramp-up over the coming years. Remaining limitations and prospects for LHC beam parameters at the exit of the LHC injector chain in the years to come will be discussed. Finally, the emerging need for improved operability of the CERN complex will be addressed, with a description of the first efforts to meet the availability and flexibility requirements of the HL-LHC era while at the same time maximizing fixed target physics output.

Slides WEIYGD1 [5.905 MB]

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEIYGD1

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Received ※ 08 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 09 July 2022

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WEPOST013

Exploitation of Crystal Shadowing via Multi-Crystal Array, Optimisers and Reinforcement Learning

1707

F.M. Velotti, M. Di Castro, L.S. Esposito, M.A. Fraser, S.S. Gilardoni, B. Goddard, V. Kain, E. Matheson
CERN, Meyrin, Switzerland

The CERN Super Proton Synchrotron (SPS) routinely delivers proton and heavy ion beams to the North experimental Area (NA) in the form of 4.8 s spills. To produce such a long flux of particles, resonant third integer slow extraction is used, which, by design, foresees primary beam lost on the electrostatic septum wires to separate circulating from extracted beam. Shadowing with thin bent crystal has been proposed and successfully tested in the SPS, as detailed in *. In 2021, a thin crystal was used for physics production showing results compatible with what measured during early testing. In this paper, the results from the 2021 physics run are presented also comparing particle losses at extraction with previous operational years. The setting up of the crystal using numerical optimisers is detailed, with possible implementation of reinforcement learning (RL) agents to improve the setting up time. Finally, the full exploitation of crystal shadowing via multi-array crystals is discussed, together with the performance reach in the SPS.
F.Velotti, et. al, "Septum shadowing by means of a bent crystal to reduce slow extraction beam loss", Phys. Rev. Accel. Beams 22, 093502 - Published 27 September 2019

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST013

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Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 02 July 2022

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WEPOST014

Studies on Pre-Computation of SPS-to-LHC Transfer Line Corrections

1711

C. Bracco, F.M. Velotti
CERN, Meyrin, Switzerland

The injection process in the LHC gives a non-negligible contribution to the turnaround time between two consecutive physics fills. Mainly due to orbit drifts in the SPS, the steering of the SPS-to-LHC transfer lines (TL) had to be regularly performed in view of minimising injection oscillations and losses, which otherwise would trigger beam dumps. Moreover, for machine protection purposes, a maximum of twelve bunches had to be injected after any TL steering to validate the actual applied corrections. This implied at several occasions the need to interrupt a fill to steer the lines and introduced a further delay between fills. Studies were performed to evaluate the option of pre-calculating the required TL corrections based on SPS orbit measurements during the LHC magnet ramp down and the reconstruction of the beam position and angle at the SPS extraction point.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST014

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Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 16 June 2022

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

WEPOST015

Implementation of a Tune Sweep Slow Extraction with Constant Optics at MedAustron

1715

P.A. Arrutia Sota, M.A. Fraser, B. Goddard, V. Kain, F.M. Velotti
CERN, Meyrin, Switzerland
P. Burrows
JAI, Oxford, United Kingdom
A. De Franco
QST Rokkasho, Aomori, Japan
F. Kuehteubl, M.T.F. Pivi, D.A. Prokopovich
EBG MedAustron, Wr. Neustadt, Austria

Conventional slow extraction driven by a tune sweep perturbs the optics and changes the presentation of the beam separatrix to the extraction septum during the spill. The constant optics slow extraction (COSE) technique, recently developed and deployed operationally at the CERN Super Proton Synchrotron to reduce beam loss on the extraction septum, was implemented at MedAustron to facilitate extraction with a tune sweep of operational beam quality. COSE fixes the optics of the extracted beam by scaling all machine settings with the beam rigidity following the extracted beam’s momentum. In this contribution the implementation of the COSE extraction technique is described before it is compared to the conventional tune sweep and operational betatron core driven cases using both simulations and recent measurements.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOST015

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Received ※ 07 June 2022 — Revised ※ 16 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 18 June 2022

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WEPOPT055

Linac3, LEIR and PS Performance with Ions in 2021 and Prospects for 2022

1983

N. Biancacci, S.C.P. Albright, R. Alemany-Fernández, D. Alves, M.E. Angoletta, D. Barrientos, H. Bartosik, G. Bellodi, S.B. Bertolo, D. Bodart, M. Bozzolan, H. Damerau, F.D.L. Di Lorenzo, A. Frassier, D. Gamba, A. Huschauer, S. Jensen, V. Kain, T. Koevener, G. Kotzian, D. Küchler, A. Lasheen, G. Le Godec, T.E. Levens, N. Madysa, E. Mahner, O. Marqversen, C.M. Mastrostefano, P.D. Meruga, C. Mutin, M. O’Neil, G. Piccinini, R. Scrivens, P.S. Solvang, D. Valuch, F.M. Velotti, R. Wegner, C. Wetton, M. Zampetakis
CERN, Meyrin, Switzerland

CERN accelerators underwent a period of long shutdown from the end of 2018 to 2020. During this time frame, significant hardware and software upgrades have been put in place to increase the performance of both proton and ion accelerator chains in the High Luminosity LHC era. In the context of the CERN lead ion chain, 2021 has been mainly devoted to restore the injectors’ performance and to successfully prove the slip-stacking technique in SPS. In this paper we summarise the key milestones of the ion beam commissioning and the achieved beam performance for the Linac 3 (including the source), LEIR and PS accelerators, together with an outlook on 2022 operation.

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOPT055

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Received ※ 03 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 17 June 2022

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WEPOTK028

Implementation of RF Channeling at the CERN PS for Spill Quality Improvements

2114

P.A. Arrutia Sota, H. Damerau, M.A. Fraser, M. Vadai, F.M. Velotti
CERN, Meyrin, Switzerland
P. Burrows
JAI, Oxford, United Kingdom

Resonant slow extraction from synchrotrons aims at providing constant intensity spills over timescales much longer than the revolution period of the machine. However, the extracted intensity is undesirably modulated by noise on the machine’s power converters with a frequency range of between 50 Hz and a few kHz. The impact of power converter noise can be suppressed by exploiting a Radio Frequency (RF) technique known as empty bucket channelling, which increases the speed at which particles cross the tune resonance boundary. In this contribution the implementation of empty bucket channelling in the CERN Proton Synchrotron (PS) is described via simulation and measurement. The technique was tested with both a resonant RF cavity and an inductive Finemet cavity, which can produce non-sinusoidal waveforms, to significantly reduce the low frequency noise observed on the extracted spill.

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOTK028

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Received ※ 07 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 22 June 2022

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THPOST039

SPS Beam Dump System (SBDS) Commissioning After Relocation and Upgrade

2530

P. Van Trappen, E. Carlier, L. Ducimetière, V. Namora, V. Senaj, F.M. Velotti, N. Voumard
CERN, Meyrin, Switzerland

In order to overcome several machine limitations, the SBDS has been relocated from LSS1 (Long Straight Section 1) to LSS5 during LS2 (Long Shutdown 2) with an important upgrade of the extraction kicker installation. An additional vertical deflection kicker magnet (MKDV) was produced and installed while the high voltage (HV) pulse generators have been upgraded by changing gas-discharge switches (thyratrons and ignitrons) to semiconductor stacks operating in oil. Furthermore the horizontal sweep generators have been upgraded to allow for a lower kick strengths. The controls, previously consolidated during LS1, went through an additional light consolidation phase with among others the upgrade of the trigger & retrigger distribution system and the installation of a new fast-interlocks detection system. This paper describes the commissioning without and with beam and elaborates on the measured improvements and encountered problems with corrective mitigations.

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-THPOST039

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Received ※ 07 June 2022 — Accepted ※ 12 June 2022 — Issue date ※ 15 June 2022

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THPOTK043

Mitigation of High Voltage Breakdown of the Beam Screen of a CERN SPS Injection Kicker Magnet

2868

M.J. Barnes, W. Bartmann, M. Díaz Zumel, L. Ducimetière, L.M.C. Feliciano, T. Kramer, V. Namora, T. Stadlbauer, D. Standen, P. Trubacova, F.M. Velotti, C. Zannini
CERN, Meyrin, Switzerland

The SPS injection kicker magnets (MKP) were developed in the 1970’s, before beam induced power deposition was considered an issue. These magnets are very lossy from a beam impedance perspective: this is expected to be an issue during SPS operation with the higher intensity beams needed for HL-LHC. A design, with serigraphy applied to an alumina carrier, has been developed to significantly reduce the broadband beam coupling impedance and hence mitigate the heating issues. During high voltage pulse testing there were electrical discharges associated with the serigraphy. Detailed mathematical models have been developed to aid in understanding the transiently induced voltages and to reduce the magnitude and duration of electric field. In this paper, we discuss the solutions implemented to mitigate the electrical discharges while maintaining an adequately low beam-coupling impedance. In addition, the results of high voltage tests are reported. The alumina substrate has a high secondary electron yield and thus electron-cloud could be an issue, with SPS beam, if mitigating measures were not taken: this paper also discusses the measures implemented.

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reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-THPOTK043

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Received ※ 07 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 17 June 2022

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