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Machine Learning Based Optimization of Laser-Plasma Accelerators : Physics and Astronomy (R0) - Sören Jalas

Machine Learning Based Optimization of Laser-Plasma Accelerators

By: Sören Jalas

eText | 9 June 2025

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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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