Author: Cook, N.M.
Paper Title Page
MOPOPT066 Gas Sheet Diagnostics Using Particle in Cell Code 410
 
  • M. Yadav, P. Manwani, J.B. Rosenzweig
    UCLA, Los Angeles, California, USA
  • G. Andonian
    RadiaBeam, Santa Monica, California, USA
  • Ö. Apsimon, C.P. Welsch
    The University of Liverpool, Liverpool, United Kingdom
  • N.M. Cook, A. Diaw, C.C. Hall
    RadiaSoft LLC, Boulder, Colorado, USA
  • N.P. Norvell
    UCSC, Santa Cruz, California, USA
 
  Funding: This work was supported by the STFC Liverpool Centre for Doctoral Training on Data Intensive Science (LIV. DAT) under grant agreement ST/P006752/1 and DE-SC0019717.
When intense particle beam propagates in dense plasma or gas, ionization can yield valuable information on the drive beam properties. Impact ionization and tunnel ionization are the two ionization regimes that must be accounted for varying beam properties. Due to these ionization mechanisms, new plasma electrons are generated causing different instabilities, dependent on the dominant ionization process considered. In order to accomplish the ambitious experimental goals of sophisticated beam diagnostics using ionization imaging, careful studies on the different ionization regimes, and the cross-over periods, required. Here we will discuss the impact ionization using fully parallel PIC code OSIRIS. We focus on understanding the gas sheet ionization diagnostics for characterizing high intensity charged particle beams. We study the interaction of neutral gas with an electron beam and varying density. We will also investigate the principle of detecting photon emission, rather than direct primary ion imaging, from the ionization induced in the interaction between the gas jet and charged particle beams.
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOPT066  
About • Received ※ 07 June 2022 — Revised ※ 19 June 2022 — Accepted ※ 21 June 2022 — Issue date ※ 26 June 2022
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MOPOPT067 Electron Beam Phase Space Reconstruction From a Gas Sheet Diagnostic 414
 
  • N.M. Cook, A. Diaw, C.C. Hall
    RadiaSoft LLC, Boulder, Colorado, USA
  • G. Andonian
    RadiaBeam, Santa Monica, California, USA
  • N.P. Norvell
    UCSC, Santa Cruz, California, USA
  • M. Yadav
    The University of Liverpool, Liverpool, United Kingdom
 
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number DE-SC0019717.
Next generation particle accelerators craft increasingly high brightness beams to achieve physics goals for applications ranging from colliders to free electron lasers to studies of nonperturbative QED. Such rigorous requirements on total charge and shape introduce diagnostic challenges for effectively measuring bunch parameters prior to or at interaction points. We report on the simulation and training of a non-destructive beam diagnostic capable of characterizing high intensity charged particle beams. The diagnostic consists of a tailored neutral gas curtain, electrostatic microscope, and high sensitivity camera. An incident electron beam ionizes the gas curtain, while the electrostatic microscope transports generated ions to an imaging screen. Simulations of the ionization and transport process are performed using the Warp code. Then, a neural network is trained to provide accurate estimates of the initial electron beam parameters. We present initial results for a range of beam and gas curtain parameters and comment on extensibility to other beam intensity regimes.

 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOPT067  
About • Received ※ 08 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 10 July 2022  
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TUPOST009 Online Correction of Laser Focal Position Using FPGA-Based ML Models 857
 
  • J.A. Einstein-Curtis, S.J. Coleman, N.M. Cook, J.P. Edelen
    RadiaSoft LLC, Boulder, Colorado, USA
  • S.K. Barber, C.E. Berger, J. van Tilborg
    LBNL, Berkeley, California, USA
 
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Numbers DE-SC 00259037 and DE-AC02-05CH11231.
High repetition-rate, ultrafast laser systems play a critical role in a host of modern scientific and industrial applications. We present a prototype diagnostic and correction scheme for controlling and determining laser focal position at 10 s of Hz rate by utilizing fast wavefront sensor measurements from multiple positions to train a focal position predictor. This predictor is used to determine corrections for actuators along the beamline to provide the desired correction to the focal position on millisecond timescales. Our initial proof-of-principle demonstrations leverage pre-compiled data and pre-trained networks operating ex-situ from the laser system. We then discuss the application of a high-level synthesis framework for generating a low-level hardware description of ML-based correction algorithms on FPGA hardware coupled directly to the beamline. Lastly, we consider the use of remote computing resources, such as the Sirepo scientific framework* , to actively update these correction schemes and deploy models to a production environment.
* M.S. Rakitin et al., "Sirepo: an open-source cloud-based software interface for X-ray source and optics simulations", Journal of Synchrotron Radiation 25, 1877-1892 (Nov 2018).
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST009  
About • Received ※ 20 May 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 23 June 2022
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