Overview
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.
The book, Machine Learning Based Optimization of Laser-Plasma Accelerators (Springer Theses) [Bulk, Wholesale, Quantity] ISBN#9783031880827 in Hardcover by Sören Jalas may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
Format:
Hardcover
Publication Date:
06/10/2025
ISBN-13:
9783031880827
Pages:
134
Publisher:
Springer Nature Switzerland
