Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning

J. Goodman; M. King; E. J. Dolier; R. Wilson; R. J. Gray; P. McKenna

doi:10.1017/hpl.2023.11

High Power Laser Science and Engineering, Volume. 11, Issue 3, 03000e34(2023)

Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning On the Cover

J. Goodman¹, M. King^1,2, E. J. Dolier¹, R. Wilson¹, R. J. Gray¹, and P. McKenna^1,2、*

Author Affiliations

¹SUPA Department of Physics, University of Strathclyde, Glasgow, UK

²The Cockcroft Institute, Sci-Tech Daresbury, Warrington, UK

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J. Goodman, M. King, E. J. Dolier, R. Wilson, R. J. Gray, P. McKenna. Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning[J]. High Power Laser Science and Engineering, 2023, 11(3): 03000e34

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Paper Information

Category: Research Articles

Received: Dec. 10, 2022

Accepted: Feb. 6, 2023

Published Online: May. 29, 2023

The Author Email: P. McKenna (paul.mckenna@strath.ac.uk)

DOI:10.1017/hpl.2023.11

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology