A neural network-based synthetic diagnostic of laser-accelerated proton energy spectra

A neural network-based synthetic diagnostic of laser-accelerated proton energy spectra

Abstract Machine learning can revolutionize the development of laser-plasma accelerators by enabling real-time optimization, predictive modeling and experimental automation. Given the broad range of laser and plasma parameters and shot-to-shot variability in laser-driven ion acceleration at present,...

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Autors principals: Christopher J. G. McQueen, Robbie Wilson, Timothy P. Frazer, Martin King, Matthew Alderton, Ewan F. J. Bacon, Ewan J. Dolier, Thomas Dzelzainis, Jesel K. Patel, Maia P. Peat, Ben C. Torrance, Ross J. Gray, Paul McKenna
Format: Article
Idioma:English
Publicat: Nature Portfolio 2025-02-01
Col·lecció:Communications Physics
Accés en línia:https://doi.org/10.1038/s42005-025-01984-8

Internet

https://doi.org/10.1038/s42005-025-01984-8

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