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Data analysis techniques for high-energy physics.

"Now thoroughly revised and up-dated, this book describes techniques for handling and analysing data obtained from high-energy and nuclear physics experiments." "This guide will appeal to graduate students, researchers and computer and electronic engineers involved with experimental p...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Frühwirth, R. (Rudolf), Regler, M.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, U.K. ; New York : Cambridge University Press, 2000.
Edición:2nd ed. /
Colección:Cambridge monographs on particle physics, nuclear physics, and cosmology ; 11.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Data analysis techniques for high-energy physics. 
250 |a 2nd ed. /  |b R. Frühwirth [and others] ; edited by M. Regler and R. Frühwirth. 
260 |a Cambridge, U.K. ;  |a New York :  |b Cambridge University Press,  |c 2000. 
300 |a 1 online resource (xxiv, 384 pages) :  |b illustrations 
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490 1 |a Cambridge monographs on particle physics, nuclear physics, and cosmology ;  |v 11 
500 |a Revised edition of: Data analysis techniques for high-energy physics experiments. 1990. 
504 |a Includes bibliographical references (pages 358-374) and index. 
505 0 |a 1. Real-time data triggering and filtering -- 1.1. Definitions and goals of triggers and filters -- 1.2. Trigger schemes -- 1.3. Queuing theory, queuing simulation and reliability -- 1.4. Classifications of triggers -- 1.5. Examples of triggers -- 1.6. Implementation of triggers -- 1.7. Multiprogramming -- 1.8. Communication lines, bus systems -- 2. Pattern recognition -- 2.1. Foundations of track finding -- 2.2. Principles of pattern recognition -- 2.3. Basic aspects of track finding -- 2.4. Methods of track finding -- 2.5. Finding of particle showers -- 2.6. Identifying particles in ring-imaging Cherenkov counters -- 3. Track and vertex fitting -- 3.1. The task of track fitting -- 3.2. Estimation of track parameters -- 3.3. Fitting the tracks of charged particles -- 3.4. Association of tracks to vertices -- 3.5. Track reconstruction: examples and final remarks -- 4. Tools and concepts for data analysis -- 4.1. Abstracting formulae and data in the computer -- 4.2. Data access methods -- 4.3. Graphics -- 4.4. Multidimensional analysis -- 4.5. Data selection -- 4.6. Data accumulation, projection, and presentation. 
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700 1 |a Regler, M. 
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