
Artificial Intelligence For High Energy Physics
World Scientific Publishing Co Pte Ltd
Published on 14. March 2022
Book
Hardback
828 pages
978-981-12-3402-6 (ISBN)
Description
The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics (HEP) has applied modern machine learning (ML) 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 (which rarely are image-like), 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.
More details
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
College/higher education
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 238 mm
Width: 165 mm
Thickness: 30 mm
Weight
1057 gr
ISBN-13
978-981-12-3402-6 (9789811234026)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Editor
Lawrence Berkeley Nat'l Lab, Usa
Laboratoire De Physique Des 2 Infinis Irene Joliot-curie, France
Slac National Accelerator Lab, Usa