Machine Learning Based Optimization of Laser-Plasma Accelerators (Springer Theses)

Machine Learning Based Optimization of Laser-Plasma Accelerators (Springer Theses)

Machine Learning Based Optimization of Laser-Plasma Accelerators (Springer Theses)

by: Sören Jalas (Author)

Publisher: Springer

Publication Date: 2025-06-10

Language: English

Print Length: 171 pages

ISBN-10: 303188082X

ISBN-13: 9783031880827

Book Description

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.

Editorial Reviews

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.

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