Machine Learning Based Optimization of Laser-Plasma Accelerators
Springer Nature Switzerland
ISBN 978-3-031-88083-4
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eBook. PDF
2025
XXXVII, 134 p. 64 illus., 63 illus. in color..
In englischer Sprache
Umfang: 134 S.
Verlag: Springer Nature Switzerland
ISBN: 978-3-031-88083-4
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Das Werk ist Teil der Reihe: Springer Theses
Produktbeschreibung
This book explores the application of machine learning-based methods, particularly Bayesian optimization, within the realm of laser-plasma accelerators. The book involves the implementation of Bayesian optimization to fine tune the parameters of the lux accelerator, encompassing simulations and real-time experimentation.
In combination, the methods presented in this book provide valuable tools for effectively managing the inherent complexity of LPAs, spanning from the design phase in simulations to real-time operation, potentially paving the way for LPAs to cater to a wide array of applications with diverse demands.
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