Machine Learning Based Optimization of Laser-Plasma Accelerators (Springer Theses)
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- Synopsis
- 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.
- Copyright:
- 2025
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783031880834
- Related ISBNs:
- 9783031880827
- Publisher:
- Springer Nature Switzerland
- Date of Addition:
- 06/09/25
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Science, Computers and Internet, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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