Many different types of correlation function exist. Their exact definitions depend on what field you’re working in. For example:
- In statistics, a correlation function can find the correlation of two random variables or systems. “Correlation” is a measure of how one value or system responds to another.
The strength of correlation depends on the spatial or temporal distance between the random variables.
- Also in statistics, the Auto Correlation Function (also called a correlogram) shows serial correlation in data (where error terms transfer from one period to another) that change over time.
- In statistical mechanics, a mathematical correlation function measures order in a system and describes spatial correlation—how microscopic variables, like density or spin, are related at different positions. For example, the function is often used to describe how spins of ferro- and antiferromagnetic materials align with respect to their nearest neighbors. One application in physics assesses the probability of finding a particle’s center relative to another particle’s center . This can be extended to galaxies, as a measure of the excess probability of finding a galaxy at a certain distance from another galaxy, compared to what you would expect with a random distribution of galaxies. See  for a slightly different definition and more details on cosmology applications.
Time Correlation Function
Time correlation functions, or time-dependent correlation functions, are used in the theory of noise and stochastic processes including statistical physics and spectroscopy. They are a measure of the correlation of two dynamical properties over time. Mathematically, the correlation function is defined as :
Cαβ(t) = <α(0)β(t)>
The brackets <> indicate an average for the equilibrium ensemble.
If the two properties αβ are the same, the correlation function is called an autocorrelation function. If they are different, it’s a cross-correlation function.
Time-correlation functions are also used in quantum mechanics, where they represent the dynamics of a system. They give a statistical description of an ensemble variable’s time-evolution of at thermal equilibrium. These functions are often used to model both random and stochastic irreversible processes in condensed phases .
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 MIT Open Courseware. (2009). 5.74 Introductory Quantum Mechanics II. Retrieved April 4, 2021 from: https://ocw.mit.edu/courses/chemistry/5-74-introductory-quantum-mechanics-ii-spring-2009/lecture-notes/MIT5_74s09_lec05.pdf CC Sharealike 4.0.