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Springer Theses

Machine Learning at the Belle II Experiment

The Full Event Interpretation and Its Validation on Belle Data

Authors: Keck, Thomas

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  • Nominated as an outstanding Ph.D thesis by the Karlsruhe Institute of Technology, Karlsruhe, Germany
  • Includes a comprehensive introduction into the Full Event Interpretation
  • Provides detailed results on data recorded by the Belle experiment and simulation studies for the Belle II experiment
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  • ISBN 978-3-319-98249-6
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Hardcover $139.99
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  • ISBN 978-3-319-98248-9
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About this book

This book explores how machine learning can be used to improve the efficiency of expensive fundamental science experiments.

The first part introduces the Belle and Belle II experiments, providing a detailed description of the Belle to Belle II data conversion tool, currently used by many analysts. 

The second part covers machine learning in high-energy physics, discussing the Belle II machine learning infrastructure and selected algorithms in detail. Furthermore, it examines several machine learning techniques that can be used to control and reduce systematic uncertainties. 

The third part investigates the important exclusive B tagging technique, unique to physics experiments operating at the Υ resonances, and studies in-depth the novel Full Event Interpretation algorithm, which doubles the maximum tag-side efficiency of its predecessor. 

The fourth part presents a complete measurement of the branching fraction of the rare leptonic B decay “B→tau nu”, which is used to validate the algorithms discussed in previous parts.


About the authors

Thomas Keck is an experimental high-energy physicists. He obtained his PhD at the Karlsruhe Institute of Technology in 2017. As a member of the Belle and Belle II collaboration he was responsible for the development and implementation of machine learning algorithms in the Belle II Software Framework. In particular, his work was focused on hadronic and semileptonic tagging algorithms, and their application to rare B meson decays. His professional interests include any new technologies in the field of computer science in particular deep learning techniques and their application in physics.

Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook $109.00
price for USA in USD (gross)
  • ISBN 978-3-319-98249-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-3-319-98248-9
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning at the Belle II Experiment
Book Subtitle
The Full Event Interpretation and Its Validation on Belle Data
Authors
Series Title
Springer Theses
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-319-98249-6
DOI
10.1007/978-3-319-98249-6
Hardcover ISBN
978-3-319-98248-9
Series ISSN
2190-5053
Edition Number
1
Number of Pages
XI, 174
Number of Illustrations
68 b/w illustrations, 16 illustrations in colour
Topics

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