Physics:Quantum data analysis/Correlation Functions: Difference between revisions
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'''Correlation functions''' quantify how particles, detector signals, or event-level quantities are related beyond independent random occurrence. In particle physics they are used to study jets, collective flow, femtoscopy, resonance structure, background shapes, and fluctuations. A correlation function can reveal structure that is invisible in a single-particle distribution.<ref name="cowan">{{cite book |last=Cowan |first=Glen |title=Statistical Data Analysis |publisher=Oxford University Press |year=1998 |isbn=978-0-19-850156-5}}</ref> | |||
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[[File:Quantum_data_analysis_correlation_functions_yellow.png|thumb|280px|Correlation | [[File:Quantum_data_analysis_correlation_functions_yellow.png|thumb|280px|Correlation functions represented as relationships among particles in an event sample.]] | ||
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== Pair and multiparticle correlations == | |||
Two-particle correlations compare the joint distribution of particle pairs with a reference distribution. Higher-order correlations extend the idea to groups of particles and can test collective behavior or nontrivial event structure.<ref name="cowan">{{cite book |last=Cowan |first=Glen |title=Statistical Data Analysis |publisher=Oxford University Press |year=1998 |isbn=978-0-19-850156-5}}</ref> | |||
== Physics interpretation == | |||
Correlations may arise from conservation laws, decays, jets, quantum statistics, final-state interactions, collective flow, or detector effects. Interpreting them requires careful construction of reference samples and systematic checks.<ref name="pdg2024">{{cite journal |collaboration=Particle Data Group |title=Review of Particle Physics |journal=Physical Review D |volume=110 |issue=3 |pages=030001 |year=2024 |doi=10.1103/PhysRevD.110.030001}}</ref> | |||
== Analysis choices == | |||
Binning, normalization, event mixing, acceptance correction, and background subtraction define the meaning of a measured correlation. Small changes in these choices can alter the visible structure.<ref name="lyons">{{cite book |last=Lyons |first=Louis |title=Statistics for Nuclear and Particle Physicists |publisher=Cambridge University Press |year=1986 |isbn=978-0-521-37934-2}}</ref> | |||
=See also= | =See also= | ||
Revision as of 20:57, 19 May 2026
Correlation functions quantify how particles, detector signals, or event-level quantities are related beyond independent random occurrence. In particle physics they are used to study jets, collective flow, femtoscopy, resonance structure, background shapes, and fluctuations. A correlation function can reveal structure that is invisible in a single-particle distribution.[1]
Pair and multiparticle correlations
Two-particle correlations compare the joint distribution of particle pairs with a reference distribution. Higher-order correlations extend the idea to groups of particles and can test collective behavior or nontrivial event structure.[1]
Physics interpretation
Correlations may arise from conservation laws, decays, jets, quantum statistics, final-state interactions, collective flow, or detector effects. Interpreting them requires careful construction of reference samples and systematic checks.[2]
Analysis choices
Binning, normalization, event mixing, acceptance correction, and background subtraction define the meaning of a measured correlation. Small changes in these choices can alter the visible structure.[3]
See also
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
- ↑ 1.0 1.1 Cowan, Glen (1998). Statistical Data Analysis. Oxford University Press. ISBN 978-0-19-850156-5.
- ↑ "Review of Particle Physics". Physical Review D 110 (3): 030001. 2024. doi:10.1103/PhysRevD.110.030001.
- ↑ Lyons, Louis (1986). Statistics for Nuclear and Particle Physicists. Cambridge University Press. ISBN 978-0-521-37934-2.
Author: Sergei V. Chekanov
Author: Claude Pruneau
Author: Harold Foppele
Source attribution: Physics:Quantum data analysis/Correlation Functions
