Probability distribution of a stochastic variable

In summary, the article discusses the use of a generator functional to define the probability distribution of a stochastic potential V. The author equates it to a specific equation, but it is unclear how the steps are mathematically derived. Any relevant references or hints would be appreciated.
  • #1
Ravi Mohan
196
21
I am studying an article which involves stochastic variables http://www.rmki.kfki.hu/~diosi/prints/1985pla112p288.pdf.

The author defines a probability distribution of a stochastic potential [itex]V[/itex] by a generator functional
[tex]
G[h] = \left<exp\left(i\int V(\vec{r},t)h(\vec{r},t)d\vec{r}dt\right)\right>,
[/tex]
where [itex]h[/itex] is an arbitrary function and [itex]\langle\rangle[/itex] stands for expectation values evaluated by means of the probabil-
ity distribution of [itex]V[/itex].

He, then equates it to (equation 1 in the article)
[tex]
G[h] = exp\left(-\frac{1}{2}\iint h(\vec{r},t)h(\vec{r}^{\prime},t)f(\vec{r}-\vec{r}^{\prime})d\vec{r}d\vec{r}^{\prime}dt\right).
[/tex]

How do we mathematically work out the steps? Any relevant reference or hint will be of great help. Thanks.
 
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  • #2
I don't understand the author's justification. However it looks like something of the form:

[tex]<\sqrt(A,A*)>[/tex], where A is the exponential integral.
 

What is a probability distribution?

A probability distribution is a mathematical function that describes the likelihood of different outcomes of a random experiment or stochastic variable. It shows the possible values that a variable can take and the corresponding probabilities of each value occurring.

What is a stochastic variable?

A stochastic variable, also known as a random variable, is a variable whose value is determined by chance or randomness. It can take on different values in different trials of an experiment and its behavior is described by a probability distribution.

What is the difference between a discrete and continuous probability distribution?

A discrete probability distribution is one where the possible values of the variable are countable and finite, such as the number of heads when flipping a coin. A continuous probability distribution is one where the possible values of the variable are infinite and uncountable, such as the height of individuals in a population.

What is the mean of a probability distribution?

The mean, also known as the expected value, of a probability distribution is the weighted average of all possible values of the variable, where the weights are the corresponding probabilities. It represents the central tendency of the distribution and is a measure of the most likely value to occur.

How is the standard deviation of a probability distribution calculated?

The standard deviation of a probability distribution is a measure of the spread or variability of the distribution. It is calculated by taking the square root of the variance, which is the weighted average of the squared differences between each value and the mean. It represents how much the values of the variable deviate from the mean.

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