Journal article
Automation and control of laser wakefield accelerators using Bayesian optimization
- 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%.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 2.2MB, Terms of use)
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- Publisher copy:
- 10.1038/s41467-020-20245-6
Authors
- Publisher:
- Nature Research
- Journal:
- Nature Communications More from this journal
- Volume:
- 11
- Issue:
- 1
- Article number:
- 6355
- Publication date:
- 2020-12-11
- Acceptance date:
- 2020-11-20
- DOI:
- EISSN:
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2041-1723
- Pmid:
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33311487
- Language:
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English
- Keywords:
- Pubs id:
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1150976
- Local pid:
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pubs:1150976
- Deposit date:
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2021-02-23
Terms of use
- Copyright holder:
- Shalloo et al.
- Copyright date:
- 2020
- Rights statement:
- Copyright © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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