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Automation and control of laser wakefield accelerators using Bayesian optimization.
Shalloo, R J; Dann, S J D; Gruse, J-N; Underwood, C I D; Antoine, A F; Arran, C; Backhouse, M; Baird, C D; Balcazar, M D; Bourgeois, N; Cardarelli, J A; Hatfield, P; Kang, J; Krushelnick, K; Mangles, S P D; Murphy, C D; Lu, N; Osterhoff, J; Põder, K; Rajeev, P P; Ridgers, C P; Rozario, S; Selwood, M P; Shahani, A J; Symes, D R; Thomas, A G R; Thornton, C; Najmudin, Z; Streeter, M J V.
Affiliation
  • Shalloo RJ; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK. r.shalloo@imperial.ac.uk.
  • Dann SJD; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Gruse JN; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK.
  • Underwood CID; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Antoine AF; Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, MI, 48109-2099, USA.
  • Arran C; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Backhouse M; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK.
  • Baird CD; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Balcazar MD; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Bourgeois N; Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, MI, 48109-2099, USA.
  • Cardarelli JA; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Hatfield P; Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, MI, 48109-2099, USA.
  • Kang J; Clarendon Laboratory, University of Oxford, Parks Road, Oxford, OX1 3PU, UK.
  • Krushelnick K; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Mangles SPD; Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, MI, 48109-2099, USA.
  • Murphy CD; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK.
  • Lu N; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Osterhoff J; Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Põder K; Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, 22607, Hamburg, Germany.
  • Rajeev PP; Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, 22607, Hamburg, Germany.
  • Ridgers CP; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Rozario S; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Selwood MP; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK.
  • Shahani AJ; Department of Physics, York Plasma Institute, University of York, York, YO10 5DD, UK.
  • Symes DR; Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Thomas AGR; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Thornton C; Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, MI, 48109-2099, USA.
  • Najmudin Z; Central Laser Facility, STFC Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK.
  • Streeter MJV; The John Adams Institute for Accelerator Science, Imperial College London, London, SW7 2AZ, UK.
Nat Commun ; 11(1): 6355, 2020 Dec 11.
Article in En | MEDLINE | ID: mdl-33311487
ABSTRACT
Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2020 Document type: Article Affiliation country:
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2020 Document type: Article Affiliation country: