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| ISBN: | 9783031880834 |
|---|---|
| Formato: | ePub |
| Idioma: | Inglés |
| Editorial: | Springer Nature |
| Tema: | Computadoras |
| Subtema: | Inteligencia artificial y semántica |
| Año de publicación: | 2025-06-09 |
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.