Book:Quantum Collection/Data Analysis Techniques in Particle Physics: Difference between revisions
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Latest revision as of 09:32, 22 May 2026
Collection of Physics:Quantum Book IV
Data Analysis Techniques in Particle Physics
Data Analysis Techniques in Particle Physics is a child volume of the Quantum Collection. It organizes methods used to extract physics from particle-collision data, including event reconstruction, detector simulations, statistical methods, Standard Model measurements, searches for new physics, data processing, fit optimisation, advanced data comprehension, and machine learning.
Table of contents (60 articles)
Index
Foundations and experiments
Analysis, measurements and discovery
Full contents
1. Introduction to Particle Physics (5) Back to index
2. Nuts and Bolts (4) Back to index
3. Overview of Particle Collision Experiments (3) Back to index
4. Collision Kinematics and Complex Observables (8) Back to index
5. Basic Measurements (4) Back to index
6. Data Acquisition Electronics and Systems (1) Back to index
7. Event Reconstruction (3) Back to index
8. Monte Carlo Simulations (4) Back to index
9. General Statistical Methods and Data Visualisation (6) Back to index
10. Standard Model Measurements (6) Back to index
11. Searches for New Physics (4) Back to index
12. Data Processing Techniques (4) Back to index
13. Fit Optimisation Techniques (4) Back to index
14. Advanced Data Comprehension Techniques (3) Back to index
15. Machine Learning (1) Back to index
60. Machine Learning
References
Further reading
Source attribution: Book:Quantum Collection/Data Analysis Techniques in Particle Physics
