Data Analysis Techniques for High Energy Physics
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Book Description
Now thoroughly revised and up-dated, this volume describes techniques for handling and analyzing data obtained from high-energy and nuclear physics experiments. Beginning with a chapter on real-time data triggering and filtering, the book describes methods of selecting the relevant events from a large background. The use of pattern recognition techniques to group the huge number of measurements into physically meaningful objects such as particle tracks or showers is then examined and the track and vertex fitting methods necessary to extract the maximum amount of information from the available measurements are explained. The final chapter describes tools and methods useful for the physical interpretation and presentation of results.
Book Info
A text describing techniques for handling and analyzing data obtained from high-energy and nuclear physics experiments. For graduate students, researchers and computer and electronic engineers involved with experimental physics. DLC: Particles (Nuclear physics)--Experiments--Data processing.
Data Analysis Techniques for High Energy Physics,R. Frühwirth,M. Regler,R. K. Bock,H. Grote,D. Notz,T. Ericson,P. Y. Landshoff,Cambridge University Press,0521632196,Data processing,Experiments,General,Nuclear Physics,Particle Physics,Particles (Nuclear physics),Physics,Research & Methodology,Science,Science/Mathematics,Atomic & molecular physics,Particle & high-energy physics,Particles (Nuclear physics)--Experiments--Data processing,Science / Nuclear Physics
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