تقرير
Automated control and optimisation of laser driven ion acceleration
العنوان: | Automated control and optimisation of laser driven ion acceleration |
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المؤلفون: | Loughran, B., Streeter, M. J. V., Ahmed, H., Astbury, S., Balcazar, M., Borghesi, M., Bourgeois, N., Curry, C. B., Dann, S. J. D., DiIorio, S., Dover, N. P., Dzelzanis, T., Ettlinger, O. C., Gauthier, M., Giuffrida, L., Glenn, G. D., Glenzer, S. H., Green, J. S., Gray, R. J., Hicks, G. S., Hyland, C., Istokskaia, V., King, M., Margarone, D., McCusker, O., McKenna, P., Najmudin, Z., Parisuaña, C., Parsons, P., Spindloe, C., Symes, D. R., Thomas, A. G. R., Treffert, F., Xu, N., Palmer, C. A. J. |
سنة النشر: | 2023 |
المجموعة: | Computer Science Physics (Other) |
مصطلحات موضوعية: | Physics - Plasma Physics, Computer Science - Machine Learning, Physics - Accelerator Physics, Physics - Computational Physics |
الوصف: | 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. Comment: 11 pages |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2303.00823 |
رقم الأكسشن: | edsarx.2303.00823 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |