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Beschreibung
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.
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 10. Juni 2025 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 459 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783031880827 |
| Seiten | 134 |
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