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Artificial Intelligence for High Energy Physics

Artificial Intelligence for High Energy Physics

Paolo Calafiura
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The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics has applied modern machine learning techniques to all stages of the data analysis pipeline, from raw data processing to statistical analysis. The unique requirements of HEP data analysis, the availability of high-quality simulators, the complexity of the data structures , the control of uncertainties expected from scientific measurements, and the exabyte-scale datasets require the development of HEP-specific ML techniques. While these developments proceed at full speed along many paths, the nineteen reviews in this book offer a self-contained, pedagogical introduction to ML models' real-life applications in HEP, written by some of the foremost experts in their area.
Pages
630
Format
Hardcover
Publisher
World Scientific Publishing Company
Release
December 30, 2021
ISBN
9811234027
ISBN 13
9789811234026

Artificial Intelligence for High Energy Physics

Paolo Calafiura
0/5 ( ratings)
Read Download
The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics has applied modern machine learning techniques to all stages of the data analysis pipeline, from raw data processing to statistical analysis. The unique requirements of HEP data analysis, the availability of high-quality simulators, the complexity of the data structures , the control of uncertainties expected from scientific measurements, and the exabyte-scale datasets require the development of HEP-specific ML techniques. While these developments proceed at full speed along many paths, the nineteen reviews in this book offer a self-contained, pedagogical introduction to ML models' real-life applications in HEP, written by some of the foremost experts in their area.
Pages
630
Format
Hardcover
Publisher
World Scientific Publishing Company
Release
December 30, 2021
ISBN
9811234027
ISBN 13
9789811234026

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