This book is meant to be a practical introduction to data analysis in high energy physics experiments, especially collider experiments using high-energy accelerators.
The field requires a very wide range of knowledge,
...
This book is meant to be a practical introduction to data analysis in high energy physics experiments, especially collider experiments using high-energy accelerators.
The field requires a very wide range of knowledge, not only for the theoretical particle physics, but also for the detector technology and computing science. We often find beginners in this field suffering from understanding how data analysis is taking place, simply because of too many things one needs to know. Reading journal papers typically does not help since comprehensive understanding and training are required, which are not described in the papers themselves. It is quite difficult to obtain such skills unless you do once a data analysis by yourself. We hope that
this book helps reduce such difficulties by providing a one-stop “explanation” on key aspects of data analysis.
This book should also serve as an introductory textbook for those who are learning about individual subjects in data analysis, such as
• Basic idea on methods to reconstruct and identify particles;
• Detector calibration in collider experiments;
• Statistical methods used in collider experiments;
• Methods to increase sensitivities of an experiment through data analysis
techniques;
• Simulation of particle collisions and detector responses.
This book is intended for undergraduate and first-year graduate students who have taken basic-level courses in particle physics. Throughout the book, we tried to explain what happens without explicitly using many equations. We neither cover the formalism on the interaction of particles in matter nor the theory of the particle physics Standard Model. Instead, we, experimental physicists, provide a “practical” explanation of how to understand after considering those formalism and theories.
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