Data Analysis Techniques for High-Energy Physics Experiments
Cambridge University Press
Published on 22. February 1990
Book
Hardback
448 pages
978-0-521-34195-0 (ISBN)
Article exhausted; check for reprint
Description
High-energy physics - the science of the fundamental particles nature - has become one of the most complex and demanding disciplines of natural science. The observation of particle interactions involves the analysis of large and intricate data samples. The very high cost of these experiments makes the full and correct use of the information imperative. Successful interpretation of the data requires the application of advanced mathematical algorithms and computer techniques in all stages of the analysis. The necessary and available techniques of all steps of the analysis have been assembled in a single book. All four authors have had many years' involvement with high-energy physics experiments at CERN, DESY and other particle accelerators around the world. They have written this book both as an introduction and to inform the reader on the most advanced techniques of data analysis in this field. It will be of great value to people involved in experimental research in particle physics, including beginning graduates, computer electronic engineers and senior academics.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Dimensions
Height: 228 mm
Width: 152 mm
Thickness: 23 mm
Weight
745 gr
ISBN-13
978-0-521-34195-0 (9780521341950)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

R. Fruehwirth | M. Regler | R. K. Bock
Data Analysis Techniques for High-Energy Physics
Book
08/2000
2nd Edition
Cambridge University Press
€146.08
Article exhausted; check for reprint
Content
Preface; Abbreviations; Introduction; 1. Real-time data triggering and filtering; 2. Pattern recognition; 3. Track and vertex fitting; 4. Tools and concepts for statistical data analysis; 5. Program development and software management; 6. Some final remarks; References; Index.