IPAC2022 - List of Authors (Biedron, S.)

Paper	Title	Page
TUPOMS058	C-Band High Gradient Testing of the Benchmark a/λ=0.105 Cavity	1564
	E.I. Simakov, V. Gorelov, T. Tajima, M.R.A. Zuboraj LANL, Los Alamos, New Mexico, USA S. Biedron Element Aero, Chicago, USA S. Biedron UNM-ECE, Albuquerque, USA M.E. Middendorf ORNL RAD, Oak Ridge, Tennessee, USA
	Funding: Los Alamos National Laboratory LDRD Program This poster will report the results of high gradient testing of the benchmark C-band RF cavity. Modern applications such as X-ray sources require accelerators with optimized cost of construction and operation, naturally calling for high-gradient acceleration. At LANL we commissioned a test stand (CERF-NM) powered by a 50 MW, 5.712 GHz Canon klystron. The test stand is capable of conditioning accelerating cavities for operation at surface electric fields in excess of 300 MV/m. CERF-NM is the first high gradient C-band test facility in the United States. An important milestone for this test stand is to demonstrate conditioning and high gradient testing of the most basic high gradient RF cavity with a geometry that has been extensively studied at other frequencies, such as X-band. The cavity is the three-cell structure with the highest gradient in the central cell and two coupling cells, and the ratio of the radius of the coupling iris to the wavelength a/\lamda=0.105. This presentation will report achieved gradients, breakdown probabilities, and other characteristics measured during the high power operation of this cavity.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS058
About •	Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 17 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEINGD1	Industry and Accelerator Science, Technology, and Engineering - the Need to Integrate (Building Bridges)	1644
	R. Geometrante KYMA, Trieste, Italy S. Biedron Element Aero, Chicago, USA E. Braidotti CAEN ELS srl, Trieste, Italy J.M.A. Priem VDL ETG, Eindhoven, The Netherlands J.C. Rugsancharoenphol FTI, Bangkok, Thailand S.L. Sheehy The University of Melbourne, Melbourne, Victoria, Australia M. Vretenar CERN, Meyrin, Switzerland
	Abstract
	Slides WEINGD1 [36.079 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEINGD1
About •	Received ※ 05 July 2022 — Accepted ※ 04 July 2022 — Issue date ※ 05 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPOPT057	Updates in Efforts to Data Science Enabled MeV Ultrafast Electron Diffraction System	397
	S. Biedron, T.B. Bolin, M. Martínez-Ramón, S.I. Sosa Guitron UNM-ECE, Albuquerque, USA M. Babzien, M.G. Fedurin, J.J. Li, M.A. Palmer BNL, Upton, New York, USA S. Biedron UNM-ME, Albuquerque, New Mexico, USA D. Martin, M.E. Papka ANL, Lemont, Illinois, USA
	Funding: Work supported by DOEs EPSCoR award DE-SC0021365, used resources of the Brookhaven National Laboratory’s Accelerator Test Facility and of the Argonne Leadership Computing Facility. MeV ultrafast electron diffraction (MUED) is a pump-probe characterization technique to study ultrafast phenomena in materials with high temporal and spatial resolution. This complex instrument can be advanced into a turn-key, high-throughput tool with the aid of machine learning (ML) mechanisms and high-performance computing. The MUED instrument at the Accelerator Test Facility in Brookhaven National Laboratory was employed to test different ML approaches for both data analysis and control. We characterized different materials using MUED, mainly polycrystalline gold and single crystal Ta2NiS5. Diffraction patterns were acquired in single shot mode and convolutional neural network autoenconder models were evaluated for noise reduction and the reconstruction error was studied to identify anomalous diffraction patterns. Electron beam energy jitter was analyzed from single shot diffraction patterns to be used as a novel diagnostic tool. The MUED beamline was also simulated using VSim to construct a surrogate model for control of beam shape and energy. Progress towards ML-based controls leveraging off Argonne Leadership Computing Facility resources will also be presented.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOPT057
About •	Received ※ 02 July 2022 — Accepted ※ 26 June 2022 — Issue date ※ 08 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPOMS029	HPC Modeling of a High-Gradient C-Band Linac for Hard X-Ray Free-Electron Lasers	703
	T.B. Bolin, S. Biedron UNM-ECE, Albuquerque, USA S. Sosa ODU, Norfolk, Virginia, USA
	The production of soft to hard x-rays (up to 25 keV) at XFEL (x-ray free-electron laser) facilities has enabled new developments in a broad range of disciplines. Great potential exists for new scientific discovery at higher energies (42+ keV) such as envisioned at MaRIE (Matter-Radiation Interactions in Extremes) at Los Alamos National Laboratory. These instruments can require a large amount of real estate, which quickly escalates costs: The driver of the FEL is typically an electron beam linear accelerator (LINAC) and the need for higher beam energies capable of generating these X-rays can dictate that the linac becomes longer. State of art accelerating technology is required to reduce the linac length by reducing the size of the cavities, providing for compact, high-frequency, high acceleration gradients. Here, we describe using the Argonne Leadership Computing Facility (ALCF) to facilitate our investigations into design concepts for future XFEL high-gradient LINAC’s in the C-band (~4-8 GHz). We investigate two different traveling wave (TW) geometries optimized for high-gradient operation as modeled at the ALCF using VSim software.* * https://www.txcorp.com
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOMS029
About •	Received ※ 03 July 2022 — Accepted ※ 04 July 2022 — Issue date ※ 08 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPOST027	Machine Learning-Based Tuning of Control Parameters for LLRF System of Superconducting Cavities	915
	J.A. Diaz Cruz, S. Biedron UNM-ECE, Albuquerque, USA J.A. Diaz Cruz SLAC, Menlo Park, California, USA R. Pirayesh UNM-ME, Albuquerque, New Mexico, USA S. Sosa ODU, Norfolk, Virginia, USA
	The multiple systems involved in the operation of particle accelerators use diverse control systems to reach the desired operating point for the machine. Each system needs to tune several control parameters to achieve the required performance. Traditional Low-Level RF (LLRF) systems are implemented as proportional-integral feedback loops, whose gains need to be optimized. In this paper, we explore Machine Learning (ML) as a tool to improve a traditional LLRF controller by tuning its gains using a Neural Network (NN). We present the data production scheme and a control parameter optimization using a NN. The NN training is performed using the THETA supercomputer.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST027
About •	Received ※ 14 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 20 June 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPOMS057	Design Study of HOM Couplers for the C-Band Accelerating Structure	1561
	D. Kim, E.I. Simakov LANL, Los Alamos, New Mexico, USA S. Biedron UNM-ECE, Albuquerque, USA Z. Li SLAC, Menlo Park, California, USA
	Funding: High Energy Physics (HEP) at the U.S. Department of Energy (DOE) A cold copper distributed coupling accelerator, with a high accelerating gradient at cryogenic temperatures (~77 K), is proposed as a baseline structure for the next generation of linear colliders. This novel technology improves accelerator performance and allows more degrees of freedom for optimization of individual cavities. It has been suggested that C-band accelerating structures at 5.712 GHz may allow to maintain high efficiency, achieve high accelerating gradient, and be suitable beam dynamics with wakefield damping and detuning of the cavities. The optimization of the cavity shape was performed and we computed quality factor, shunt impedance, and beam kick factor for each of the proposed cavity geometries using CST microwave studio. Next, we proposed a configuration for higher order mode (HOM) suppression that includes waveguide slots running parallel to the axis of the accelerator. This presentation will report details of the parametric study of performance of the HOM suppression waveguide, and the dependence of HOM Q-factors and kick-factors on the cavity’s and HOM waveguide’s geometries.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS057
About •	Received ※ 08 June 2022 — Revised ※ 10 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 09 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WEPOTK005	Electromagnetic Analysis of a Circular Storage Ring for Quantum Computing Using Vsim	2034
	S.I. Sosa Guitron, S. Biedron, T.B. Bolin UNM-ECE, Albuquerque, USA S. Biedron UNM-ME, Albuquerque, New Mexico, USA K.A. Brown BNL, Upton, New York, USA B. Huang SBU, Stony Brook, USA
	We discuss design considerations for a circular ion trap based on electromagnetic and particle beam simulations. This is a circular radiofrequency quadrupole (rfq) being designed for quantum information applications. The circular rfq should have good electromagnetic properties to accumulate and store the beam for prolonged times, while providing apertures for laser cooling and lower voltage electrodes to provide control over the beam. We use the electromagnetic and particle-in-cell software VSim, which uses finite difference time-domain and particle-in-cell methods, together with high performance computing tools.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOTK005
About •	Received ※ 30 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 30 June 2022 — Issue date ※ 08 July 2022
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

C-Band High Gradient Testing of the Benchmark a/λ=0.105 Cavity

1564

E.I. Simakov, V. Gorelov, T. Tajima, M.R.A. Zuboraj
LANL, Los Alamos, New Mexico, USA
S. Biedron
Element Aero, Chicago, USA
S. Biedron
UNM-ECE, Albuquerque, USA
M.E. Middendorf
ORNL RAD, Oak Ridge, Tennessee, USA

Funding: Los Alamos National Laboratory LDRD Program
This poster will report the results of high gradient testing of the benchmark C-band RF cavity. Modern applications such as X-ray sources require accelerators with optimized cost of construction and operation, naturally calling for high-gradient acceleration. At LANL we commissioned a test stand (CERF-NM) powered by a 50 MW, 5.712 GHz Canon klystron. The test stand is capable of conditioning accelerating cavities for operation at surface electric fields in excess of 300 MV/m. CERF-NM is the first high gradient C-band test facility in the United States. An important milestone for this test stand is to demonstrate conditioning and high gradient testing of the most basic high gradient RF cavity with a geometry that has been extensively studied at other frequencies, such as X-band. The cavity is the three-cell structure with the highest gradient in the central cell and two coupling cells, and the ratio of the radius of the coupling iris to the wavelength a/\lamda=0.105. This presentation will report achieved gradients, breakdown probabilities, and other characteristics measured during the high power operation of this cavity.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS058

About •

Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 17 June 2022

Cite •

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

WEINGD1

Industry and Accelerator Science, Technology, and Engineering - the Need to Integrate (Building Bridges)

1644

R. Geometrante
KYMA, Trieste, Italy
S. Biedron
Element Aero, Chicago, USA
E. Braidotti
CAEN ELS srl, Trieste, Italy
J.M.A. Priem
VDL ETG, Eindhoven, The Netherlands
J.C. Rugsancharoenphol
FTI, Bangkok, Thailand
S.L. Sheehy
The University of Melbourne, Melbourne, Victoria, Australia
M. Vretenar
CERN, Meyrin, Switzerland

Abstract

Slides WEINGD1 [36.079 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEINGD1

About •

Received ※ 05 July 2022 — Accepted ※ 04 July 2022 — Issue date ※ 05 July 2022

Cite •

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

MOPOPT057

Updates in Efforts to Data Science Enabled MeV Ultrafast Electron Diffraction System

397

S. Biedron, T.B. Bolin, M. Martínez-Ramón, S.I. Sosa Guitron
UNM-ECE, Albuquerque, USA
M. Babzien, M.G. Fedurin, J.J. Li, M.A. Palmer
BNL, Upton, New York, USA
S. Biedron
UNM-ME, Albuquerque, New Mexico, USA
D. Martin, M.E. Papka
ANL, Lemont, Illinois, USA

Funding: Work supported by DOEs EPSCoR award DE-SC0021365, used resources of the Brookhaven National Laboratory’s Accelerator Test Facility and of the Argonne Leadership Computing Facility.
MeV ultrafast electron diffraction (MUED) is a pump-probe characterization technique to study ultrafast phenomena in materials with high temporal and spatial resolution. This complex instrument can be advanced into a turn-key, high-throughput tool with the aid of machine learning (ML) mechanisms and high-performance computing. The MUED instrument at the Accelerator Test Facility in Brookhaven National Laboratory was employed to test different ML approaches for both data analysis and control. We characterized different materials using MUED, mainly polycrystalline gold and single crystal Ta2NiS5. Diffraction patterns were acquired in single shot mode and convolutional neural network autoenconder models were evaluated for noise reduction and the reconstruction error was studied to identify anomalous diffraction patterns. Electron beam energy jitter was analyzed from single shot diffraction patterns to be used as a novel diagnostic tool. The MUED beamline was also simulated using VSim to construct a surrogate model for control of beam shape and energy. Progress towards ML-based controls leveraging off Argonne Leadership Computing Facility resources will also be presented.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOPT057

About •

Received ※ 02 July 2022 — Accepted ※ 26 June 2022 — Issue date ※ 08 July 2022

Cite •

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

MOPOMS029

HPC Modeling of a High-Gradient C-Band Linac for Hard X-Ray Free-Electron Lasers

703

T.B. Bolin, S. Biedron
UNM-ECE, Albuquerque, USA
S. Sosa
ODU, Norfolk, Virginia, USA

The production of soft to hard x-rays (up to 25 keV) at XFEL (x-ray free-electron laser) facilities has enabled new developments in a broad range of disciplines. Great potential exists for new scientific discovery at higher energies (42+ keV) such as envisioned at MaRIE (Matter-Radiation Interactions in Extremes) at Los Alamos National Laboratory. These instruments can require a large amount of real estate, which quickly escalates costs: The driver of the FEL is typically an electron beam linear accelerator (LINAC) and the need for higher beam energies capable of generating these X-rays can dictate that the linac becomes longer. State of art accelerating technology is required to reduce the linac length by reducing the size of the cavities, providing for compact, high-frequency, high acceleration gradients. Here, we describe using the Argonne Leadership Computing Facility (ALCF) to facilitate our investigations into design concepts for future XFEL high-gradient LINAC’s in the C-band (~4-8 GHz). We investigate two different traveling wave (TW) geometries optimized for high-gradient operation as modeled at the ALCF using VSim software.*
* https://www.txcorp.com

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOMS029

About •

Received ※ 03 July 2022 — Accepted ※ 04 July 2022 — Issue date ※ 08 July 2022

Cite •

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

TUPOST027

Machine Learning-Based Tuning of Control Parameters for LLRF System of Superconducting Cavities

915

J.A. Diaz Cruz, S. Biedron
UNM-ECE, Albuquerque, USA
J.A. Diaz Cruz
SLAC, Menlo Park, California, USA
R. Pirayesh
UNM-ME, Albuquerque, New Mexico, USA
S. Sosa
ODU, Norfolk, Virginia, USA

The multiple systems involved in the operation of particle accelerators use diverse control systems to reach the desired operating point for the machine. Each system needs to tune several control parameters to achieve the required performance. Traditional Low-Level RF (LLRF) systems are implemented as proportional-integral feedback loops, whose gains need to be optimized. In this paper, we explore Machine Learning (ML) as a tool to improve a traditional LLRF controller by tuning its gains using a Neural Network (NN). We present the data production scheme and a control parameter optimization using a NN. The NN training is performed using the THETA supercomputer.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST027

About •

Received ※ 14 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 20 June 2022

Cite •

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

TUPOMS057

Design Study of HOM Couplers for the C-Band Accelerating Structure

1561

D. Kim, E.I. Simakov
LANL, Los Alamos, New Mexico, USA
S. Biedron
UNM-ECE, Albuquerque, USA
Z. Li
SLAC, Menlo Park, California, USA

Funding: High Energy Physics (HEP) at the U.S. Department of Energy (DOE)
A cold copper distributed coupling accelerator, with a high accelerating gradient at cryogenic temperatures (~77 K), is proposed as a baseline structure for the next generation of linear colliders. This novel technology improves accelerator performance and allows more degrees of freedom for optimization of individual cavities. It has been suggested that C-band accelerating structures at 5.712 GHz may allow to maintain high efficiency, achieve high accelerating gradient, and be suitable beam dynamics with wakefield damping and detuning of the cavities. The optimization of the cavity shape was performed and we computed quality factor, shunt impedance, and beam kick factor for each of the proposed cavity geometries using CST microwave studio. Next, we proposed a configuration for higher order mode (HOM) suppression that includes waveguide slots running parallel to the axis of the accelerator. This presentation will report details of the parametric study of performance of the HOM suppression waveguide, and the dependence of HOM Q-factors and kick-factors on the cavity’s and HOM waveguide’s geometries.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS057

About •

Received ※ 08 June 2022 — Revised ※ 10 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 09 July 2022

Cite •

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

WEPOTK005

Electromagnetic Analysis of a Circular Storage Ring for Quantum Computing Using Vsim

2034

S.I. Sosa Guitron, S. Biedron, T.B. Bolin
UNM-ECE, Albuquerque, USA
S. Biedron
UNM-ME, Albuquerque, New Mexico, USA
K.A. Brown
BNL, Upton, New York, USA
B. Huang
SBU, Stony Brook, USA

We discuss design considerations for a circular ion trap based on electromagnetic and particle beam simulations. This is a circular radiofrequency quadrupole (rfq) being designed for quantum information applications. The circular rfq should have good electromagnetic properties to accumulate and store the beam for prolonged times, while providing apertures for laser cooling and lower voltage electrodes to provide control over the beam. We use the electromagnetic and particle-in-cell software VSim, which uses finite difference time-domain and particle-in-cell methods, together with high performance computing tools.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOTK005

About •

Received ※ 30 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 30 June 2022 — Issue date ※ 08 July 2022

Cite •

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