Nature Communications (Dec 2020)
Automation and control of laser wakefield accelerators using Bayesian optimization
- R. J. Shalloo,
- S. J. D. Dann,
- J.-N. Gruse,
- C. I. D. Underwood,
- A. F. Antoine,
- C. Arran,
- M. Backhouse,
- C. D. Baird,
- M. D. Balcazar,
- N. Bourgeois,
- J. A. Cardarelli,
- P. Hatfield,
- J. Kang,
- K. Krushelnick,
- S. P. D. Mangles,
- C. D. Murphy,
- N. Lu,
- J. Osterhoff,
- K. Põder,
- P. P. Rajeev,
- C. P. Ridgers,
- S. Rozario,
- M. P. Selwood,
- A. J. Shahani,
- D. R. Symes,
- A. G. R. Thomas,
- C. Thornton,
- Z. Najmudin,
- M. J. V. Streeter
Affiliations
- R. J. Shalloo
- The John Adams Institute for Accelerator Science, Imperial College London
- S. J. D. Dann
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- J.-N. Gruse
- The John Adams Institute for Accelerator Science, Imperial College London
- C. I. D. Underwood
- Department of Physics, York Plasma Institute, University of York
- A. F. Antoine
- Center for Ultrafast Optical Science, University of Michigan
- C. Arran
- Department of Physics, York Plasma Institute, University of York
- M. Backhouse
- The John Adams Institute for Accelerator Science, Imperial College London
- C. D. Baird
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- M. D. Balcazar
- Center for Ultrafast Optical Science, University of Michigan
- N. Bourgeois
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- J. A. Cardarelli
- Center for Ultrafast Optical Science, University of Michigan
- P. Hatfield
- Clarendon Laboratory, University of Oxford
- J. Kang
- Department of Chemical Engineering, University of Michigan
- K. Krushelnick
- Center for Ultrafast Optical Science, University of Michigan
- S. P. D. Mangles
- The John Adams Institute for Accelerator Science, Imperial College London
- C. D. Murphy
- Department of Physics, York Plasma Institute, University of York
- N. Lu
- Department of Materials Science and Engineering, University of Michigan
- J. Osterhoff
- Deutsches Elektronen-Synchrotron DESY
- K. Põder
- Deutsches Elektronen-Synchrotron DESY
- P. P. Rajeev
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- C. P. Ridgers
- Department of Physics, York Plasma Institute, University of York
- S. Rozario
- The John Adams Institute for Accelerator Science, Imperial College London
- M. P. Selwood
- Department of Physics, York Plasma Institute, University of York
- A. J. Shahani
- Department of Materials Science and Engineering, University of Michigan
- D. R. Symes
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- A. G. R. Thomas
- Center for Ultrafast Optical Science, University of Michigan
- C. Thornton
- Central Laser Facility, STFC Rutherford Appleton Laboratory
- Z. Najmudin
- The John Adams Institute for Accelerator Science, Imperial College London
- M. J. V. Streeter
- The John Adams Institute for Accelerator Science, Imperial College London
- DOI
- https://doi.org/10.1038/s41467-020-20245-6
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 8
Abstract
Laser wakefield accelerators are compact sources of ultra-relativistic electrons which are highly sensitive to many control parameters. Here the authors present an automated machine learning based method for the efficient multi-dimensional optimization of these plasma-based particle accelerators.
