Automated control and optimisation of laser driven ion acceleration

• URL: http://arxiv.org/abs/2303.00823v1
• Date: Wed, 1 Mar 2023 21:08:51 GMT
• Title: Automated control and optimisation of laser driven ion acceleration
• Authors: B. Loughran, M. J. V. Streeter, H. Ahmed, S. Astbury, M. Balcazar, M. Borghesi, N. Bourgeois, C. B. Curry, S. J. D. Dann, S. DiIorio, N. P. Dover, T. Dzelzanis, O. C. Ettlinger, M. Gauthier, L. Giuffrida, G. D. Glenn, S. H. Glenzer, J. S. Green, R. J. Gray, G. S. Hicks, C. Hyland, V. Istokskaia, M. King, D. Margarone, O. McCusker, P. McKenna, Z. Najmudin, C. Parisua\~na, P. Parsons, C. Spindloe, D. R. Symes, A. G. R. Thomas, F. Treffert, N. Xu and C. A. J. Palmer
• Abstract summary: An automated, HRR-compatible system produced high fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimisation of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually-optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimisation of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimisation of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimisation. Here, an automated, HRR-compatible system produced high fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimisation of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually-optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimisation of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

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