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.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
1
63 farbige Abbildungen, 1 s/w Abbildung
XXXVII, 134 p. 64 illus., 63 illus. in color.
Dateigröße
ISBN-13
978-3-031-88083-4 (9783031880834)
DOI
10.1007/978-3-031-88083-4
Schweitzer Klassifikation
