IPAC2021 - List of Authors (Sosa Guitron, S.I.)

Paper	Title	Page
MOPAB286	Towards a Data Science Enabled MeV Ultrafast Electron Diffraction System	906
	M.A. Fazio, S. Biedron, M. Martínez-Ramón, D.J. Monk, S.I. Sosa Guitron UNM-ECE, Albuquerque, USA M. Babzien, K.A. Brown, M.G. Fedurin, J.J. Li, M.A. Palmer, J. Tao BNL, Upton, New York, USA S. Biedron, T. Talbott UNM-ME, Albuquerque, New Mexico, USA J. Chen, A.J. Hurd, N.A. Moody, R. Prasankumar, C. Sweeney LANL, Los Alamos, New Mexico, USA D. Martin, M.E. Papka ANL, Lemont, Illinois, USA
	Funding: US DOE, SC, BES, MSE, award DE-SC0021365 and DOE NNSA award 89233218CNA000001 through DOE’s EPSCoR program in Office of BES with resources of DOE SC User Facilities BNL’s ATF and ALCF. A MeV ultrafast electron diffraction (MUED) instrument is a unique characterization technique to study ultrafast processes in materials by a pump-probe technique. This relatively young technology can be advanced further into a turn-key instrument by using data science and artificial intelligence (AI) mechanisms in conjunctions with high-performance computing. This can facilitate automated operation, data acquisition and real time or near- real time processing. AI based system controls can provide real time feedback on the electron beam which is currently not possible due to the use of destructive diagnostics. Deep learning can be applied to the MUED diffraction patterns to recover valuable information on subtle lattice variations that can lead to a greater understanding of a wide range of material systems. A data science enabled MUED facility will also facilitate the application of this technique, expand its user base, and provide a fully automated state-of-the-art instrument. We will discuss the progress made on the MUED instrument in the Accelerator Test Facility of Brookhaven National Laboratory.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB286
About •	paper received ※ 20 May 2021 paper accepted ※ 09 June 2021 issue date ※ 25 August 2021
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MOPAB314	Surrogate Modeling for MUED with Neural Networks	970
	D.J. Monk, S. Biedron, M.A. Fazio, M. Martínez-Ramón, S.I. Sosa Guitron UNM-ECE, Albuquerque, USA M. Babzien, K.A. Brown, M.A. Palmer, J. Tao BNL, Upton, New York, USA D. Martin, M.E. Papka ANL, Lemont, Illinois, USA T. Talbott UNM-ME, Albuquerque, New Mexico, USA
	Electron diffraction is among the most complex and influential inventions of the last century and contributes to research in many areas of physics and engineering. Not only does it aid in problems like materials and plasma research, electron diffraction systems like the MeV ultra-fast electron diffraction(MUED) instrument at the Brookhaven National Lab(BNL) also present opportunities to explore/implement surrogate modeling methods using artificial intelligence/machine learning/deep learning algorithms. Running the MUED system requires extended periods of uninterrupted runtime, skilled operators, and many varying parameters that depend on the desired output. These problems lend themselves to techniques based on neural networks(NNs), which are suited to modeling, system controls, and analysis of time-varying/multi-parameter systems. NNs can be deployed in model-based control areas and can be used simulate control designs, planned experiments, and to simulate employment of new components. Surrogate models based on NNs provide fast and accurate results, ideal for real-time control systems during continuous operation and may be used to identify irregular beam behavior as they develop.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB314
About •	paper received ※ 20 May 2021 paper accepted ※ 07 June 2021 issue date ※ 15 August 2021
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TUPAB203	Electromagnetic Simulations of a Novel Proton Linac Using VSim on HPC	1887
	S.I. Sosa Guitron, S. Biedron, T.B. Bolin UNM-ECE, Albuquerque, USA J.R. Cary Tech-X, Boulder, Colorado, USA M.S. Curtin, B. Hartman, T. Pressnall, D.A. Swenson Ion Linac Systems, Inc., Albuquerque, USA
	Funding: This work is supported by the U.S. Department of Energy, award number DE-SC0019468; It used resources of the Argonne Leadership Computing Facility, contract DE-AC02-06CH11357, and from Element Aero. We discuss electromagnetic simulations of accelerating structures in a high performance computing (HPC) system. Our overarching goal is to resolve the linac operation in a large ensemble of initial beam conditions. This requires a symbiotic relation between the electromagnetic solver and HPC. The linac is being developed by Ion Linac Systems to produce a low-energy, high-current, proton beam. We use VSim, an electromagnetic solver and PIC software developed by Tech-X to determine the electromagnetic fundamental mode of operation of the accelerating structures and discuss its implementation at the THETA supercomputer in the Argonne Leadership Computing Facility.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB203
About •	paper received ※ 20 May 2021 paper accepted ※ 17 June 2021 issue date ※ 10 August 2021
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WEPAB411	Ion Coulomb Crystals in Storage Rings for Quantum Information Science	3667
	K.A. Brown, G.J. Mahler, T. Roser, T.V. Shaftan, Z. Zhao BNL, Upton, New York, USA A. Aslam, S. Biedron, T.B. Bolin, C. Gonzalez-Zacarias, S.I. Sosa Guitron UNM-ECE, Albuquerque, USA R. Chen, T.G. Robertazzi Stony Brook University, Stony Brook, New York, USA B. Huang SBU, Stony Brook, USA
	Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. We discuss the possible use of crystalline beams in storage rings for applications in quantum information science (QIS). Crystalline beams have been created in ion trap systems and proven to be useful as a computational basis for QIS applications. The same structures can be created in a storage ring, but the ions necessarily have a constant velocity and are rotating in a circular trap. The basic structures that are needed are ultracold crystalline beams, called ion Coulomb crystals (ICC’s). We will describe different applications of ICC’s for QIS, how QIS information is obtained and can be used for quantum computing, and some of the challenges that need to be resolved to realize practical QIS applications in storage rings.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB411
About •	paper received ※ 19 May 2021 paper accepted ※ 20 July 2021 issue date ※ 20 August 2021
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THPAB069	Design Concepts for a High-Gradient C-Band Linac	3919
	T.B. Bolin, S.I. Sosa Guitron UNM-ECE, Albuquerque, USA S. Biedron UNM-ME, Albuquerque, New Mexico, USA J.R. Cary Tech-X, Boulder, Colorado, USA M. Dal Forno SLAC, Menlo Park, California, USA
	Funding: This work was performed under Contract No. 89233218CNA000001, supported by the U.S. DOE’s National Nuclear Security Administration, for the operation of Los Alamos National Laboratory (LANL). During the last decade, the production of soft to hard x-rays (up to 25 keV) at XFEL facilities has enabled new developments in a broad range of disciplines. One caveat is that these instruments can require a large amount of real estate. For example, the XFEL driver is typically an electron beam linear accelerator (LINAC) and the need for higher electron beam energies capable of generating higher energy X-rays can require longer linacs; costs quickly become prohibitive, requiring state of art methods. One cost-saving measure is to produce a high accelerating gradient while reducing cavity size. Compact accelerating structures are also high-frequency. Here, we describe design concepts for a high-gradient, cryo-cooled LINAC for XFEL facilities in the C-band regime (~4-8 GHz). We are also exploring C-band for different applications including drivers for security applications. We investigate 2 different traveling wave (TW) geometries optimized for high-gradient operation as modeled with VSim software.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB069
About •	paper received ※ 20 May 2021 paper accepted ※ 02 July 2021 issue date ※ 14 August 2021
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Towards a Data Science Enabled MeV Ultrafast Electron Diffraction System

906

M.A. Fazio, S. Biedron, M. Martínez-Ramón, D.J. Monk, S.I. Sosa Guitron
UNM-ECE, Albuquerque, USA
M. Babzien, K.A. Brown, M.G. Fedurin, J.J. Li, M.A. Palmer, J. Tao
BNL, Upton, New York, USA
S. Biedron, T. Talbott
UNM-ME, Albuquerque, New Mexico, USA
J. Chen, A.J. Hurd, N.A. Moody, R. Prasankumar, C. Sweeney
LANL, Los Alamos, New Mexico, USA
D. Martin, M.E. Papka
ANL, Lemont, Illinois, USA

Funding: US DOE, SC, BES, MSE, award DE-SC0021365 and DOE NNSA award 89233218CNA000001 through DOE’s EPSCoR program in Office of BES with resources of DOE SC User Facilities BNL’s ATF and ALCF.
A MeV ultrafast electron diffraction (MUED) instrument is a unique characterization technique to study ultrafast processes in materials by a pump-probe technique. This relatively young technology can be advanced further into a turn-key instrument by using data science and artificial intelligence (AI) mechanisms in conjunctions with high-performance computing. This can facilitate automated operation, data acquisition and real time or near- real time processing. AI based system controls can provide real time feedback on the electron beam which is currently not possible due to the use of destructive diagnostics. Deep learning can be applied to the MUED diffraction patterns to recover valuable information on subtle lattice variations that can lead to a greater understanding of a wide range of material systems. A data science enabled MUED facility will also facilitate the application of this technique, expand its user base, and provide a fully automated state-of-the-art instrument. We will discuss the progress made on the MUED instrument in the Accelerator Test Facility of Brookhaven National Laboratory.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB286

About •

paper received ※ 20 May 2021 paper accepted ※ 09 June 2021 issue date ※ 25 August 2021

Export •

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

MOPAB314

Surrogate Modeling for MUED with Neural Networks

970

D.J. Monk, S. Biedron, M.A. Fazio, M. Martínez-Ramón, S.I. Sosa Guitron
UNM-ECE, Albuquerque, USA
M. Babzien, K.A. Brown, M.A. Palmer, J. Tao
BNL, Upton, New York, USA
D. Martin, M.E. Papka
ANL, Lemont, Illinois, USA
T. Talbott
UNM-ME, Albuquerque, New Mexico, USA

Electron diffraction is among the most complex and influential inventions of the last century and contributes to research in many areas of physics and engineering. Not only does it aid in problems like materials and plasma research, electron diffraction systems like the MeV ultra-fast electron diffraction(MUED) instrument at the Brookhaven National Lab(BNL) also present opportunities to explore/implement surrogate modeling methods using artificial intelligence/machine learning/deep learning algorithms. Running the MUED system requires extended periods of uninterrupted runtime, skilled operators, and many varying parameters that depend on the desired output. These problems lend themselves to techniques based on neural networks(NNs), which are suited to modeling, system controls, and analysis of time-varying/multi-parameter systems. NNs can be deployed in model-based control areas and can be used simulate control designs, planned experiments, and to simulate employment of new components. Surrogate models based on NNs provide fast and accurate results, ideal for real-time control systems during continuous operation and may be used to identify irregular beam behavior as they develop.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB314

About •

paper received ※ 20 May 2021 paper accepted ※ 07 June 2021 issue date ※ 15 August 2021

Export •

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

TUPAB203

Electromagnetic Simulations of a Novel Proton Linac Using VSim on HPC

1887

S.I. Sosa Guitron, S. Biedron, T.B. Bolin
UNM-ECE, Albuquerque, USA
J.R. Cary
Tech-X, Boulder, Colorado, USA
M.S. Curtin, B. Hartman, T. Pressnall, D.A. Swenson
Ion Linac Systems, Inc., Albuquerque, USA

Funding: This work is supported by the U.S. Department of Energy, award number DE-SC0019468; It used resources of the Argonne Leadership Computing Facility, contract DE-AC02-06CH11357, and from Element Aero.
We discuss electromagnetic simulations of accelerating structures in a high performance computing (HPC) system. Our overarching goal is to resolve the linac operation in a large ensemble of initial beam conditions. This requires a symbiotic relation between the electromagnetic solver and HPC. The linac is being developed by Ion Linac Systems to produce a low-energy, high-current, proton beam. We use VSim, an electromagnetic solver and PIC software developed by Tech-X to determine the electromagnetic fundamental mode of operation of the accelerating structures and discuss its implementation at the THETA supercomputer in the Argonne Leadership Computing Facility.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB203

About •

paper received ※ 20 May 2021 paper accepted ※ 17 June 2021 issue date ※ 10 August 2021

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

WEPAB411

Ion Coulomb Crystals in Storage Rings for Quantum Information Science

3667

K.A. Brown, G.J. Mahler, T. Roser, T.V. Shaftan, Z. Zhao
BNL, Upton, New York, USA
A. Aslam, S. Biedron, T.B. Bolin, C. Gonzalez-Zacarias, S.I. Sosa Guitron
UNM-ECE, Albuquerque, USA
R. Chen, T.G. Robertazzi
Stony Brook University, Stony Brook, New York, USA
B. Huang
SBU, Stony Brook, USA

Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy.
We discuss the possible use of crystalline beams in storage rings for applications in quantum information science (QIS). Crystalline beams have been created in ion trap systems and proven to be useful as a computational basis for QIS applications. The same structures can be created in a storage ring, but the ions necessarily have a constant velocity and are rotating in a circular trap. The basic structures that are needed are ultracold crystalline beams, called ion Coulomb crystals (ICC’s). We will describe different applications of ICC’s for QIS, how QIS information is obtained and can be used for quantum computing, and some of the challenges that need to be resolved to realize practical QIS applications in storage rings.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB411

About •

paper received ※ 19 May 2021 paper accepted ※ 20 July 2021 issue date ※ 20 August 2021

Export •

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

THPAB069

Design Concepts for a High-Gradient C-Band Linac

3919

T.B. Bolin, S.I. Sosa Guitron
UNM-ECE, Albuquerque, USA
S. Biedron
UNM-ME, Albuquerque, New Mexico, USA
J.R. Cary
Tech-X, Boulder, Colorado, USA
M. Dal Forno
SLAC, Menlo Park, California, USA

Funding: This work was performed under Contract No. 89233218CNA000001, supported by the U.S. DOE’s National Nuclear Security Administration, for the operation of Los Alamos National Laboratory (LANL).
During the last decade, the production of soft to hard x-rays (up to 25 keV) at XFEL facilities has enabled new developments in a broad range of disciplines. One caveat is that these instruments can require a large amount of real estate. For example, the XFEL driver is typically an electron beam linear accelerator (LINAC) and the need for higher electron beam energies capable of generating higher energy X-rays can require longer linacs; costs quickly become prohibitive, requiring state of art methods. One cost-saving measure is to produce a high accelerating gradient while reducing cavity size. Compact accelerating structures are also high-frequency. Here, we describe design concepts for a high-gradient, cryo-cooled LINAC for XFEL facilities in the C-band regime (~4-8 GHz). We are also exploring C-band for different applications including drivers for security applications. We investigate 2 different traveling wave (TW) geometries optimized for high-gradient operation as modeled with VSim software.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB069

About •

paper received ※ 20 May 2021 paper accepted ※ 02 July 2021 issue date ※ 14 August 2021

Export •

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