Springer Theses

Jalas, Sören

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

Published by: Springer

Publication Date: 2025-06-10

Format: Hardcover

ISBN-13: 9783031880827

DOI: 10.1007/978-3-031-88083-4

Dimensions: 235cm x155cm

Pages: 134