Keyword: interface
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MOPA44 Utilizing Python to Prepare the VENUS Ion Source for Machine Learning controls, ion-source, PLC, ECR 151
  • A. Kireeff, L. Phair, M.J. Regis, M. Salathe, D.S. Todd
    LBNL, Berkeley, California, USA
  Funding: This work was supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Contract No. DE-AC02-05CH11231.
The fully superconducting electron cyclotron resonance (ECR) ion source VENUS is one of the world’s two highest-performing ECR ion sources, and a copy of this source will soon be used to produce ion beams at FRIB. The tuning and optimization of ECR ion sources is time consuming, and there are few detailed theoretical models to guide this work. To aid in this process, we are working toward utilizing machine learning to both efficiently optimize VENUS and reliably maintain its stability for long campaigns. We have created a Python library to interface with the programmable logic controller (PLC) in order to operate VENUS and collect and store source and beam data. We will discuss the design and safety considerations that went into creating this library, the implementation of the library, and some of the capabilities it enables.
poster icon Poster MOPA44 [0.862 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-MOPA44  
About • Received ※ 17 July 2022 — Revised ※ 27 July 2022 — Accepted ※ 05 August 2022 — Issue date ※ 16 August 2022
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TUYD4 Towards High Brightness from Plasmon-Enhanced Photoemitters cathode, electron, laser, emittance 285
  • C.M. Pierce, I.V. Bazarov, J.M. Maxson
    Cornell University (CLASSE), Cornell Laboratory for Accelerator-Based Sciences and Education, Ithaca, New York, USA
  • D.B. Durham, D. Filippetto, F. Riminucci
    LBNL, Berkeley, USA
  • A.H. Kachwala, S.S. Karkare
    Arizona State University, Tempe, USA
  • A. Minor
    UC Berkeley, Berkeley, California, USA
  Funding: This work is supported by DOE BES Contract No. DE-AC02-05CH11231. C.P. acknowledges NSF Award PHY-1549132 (CBB) and the US DOE SCGSR program. DD was supported by NSF Grant No. DMR-1548924 (STROBE).
Plasmonic cathodes, whose nanoscale features may locally enhance optical energy from the driving laser trapped at the vacuum interface, have emerged as a promising technology for improving the brightness of metal cathodes. A six orders of magnitude improvement [1] in the non-linear yield of metals has been experimentally demonstrated through this type of nanopatterning. Further, nanoscale lens structures may focus light below its free-space wavelength offering multiphoton photoemission from a region near 10 times smaller [2] than that achievable in typical photoinjectors. In this proceeding, we report on our efforts to characterize the brightness of two plasmonic cathode concepts: a spiral lens and a nanogroove array. We demonstrate an ability to engineer and fabricate nanoscale patterned cathodes by comparing their optical properties with those computed with a finite difference time domain (FDTD) code. The emittance and nonlinear yield of the cathodes are measured under ultrafast laser irradiation. Finally, prospects of this technology for the control and acceleration of charged particle beams are discussed.
[1] Polyakov, A., et al. (2013). Physical Review Letters, 110(7), 076802.
[2] Durham, D. B., et al. (2019). Physical Review Applied, 12(5), 054057.
slides icon Slides TUYD4 [7.160 MB]  
DOI • reference for this paper ※ doi:10.18429/JACoW-NAPAC2022-TUYD4  
About • Received ※ 05 August 2022 — Revised ※ 08 August 2022 — Accepted ※ 11 August 2022 — Issue date ※ 13 September 2022
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