The Distribution of Delta Functions

In summary, the conversation discusses the distribution D^{m}\delta(x-a)D^{k}\delta(x) and its properties. It is mentioned that the identity \delta(x-a)=e^{-aD}\delta(x)=\sum_{n=0}^{\infty}(-a)^{n}\frac{D^{n}}{n!}\delta(x) is correct for certain test functions, but may not work if the Taylor series does not converge. The question of what happens when x=a or x=0 is raised, but it is clarified that the expression contains terms for both cases. It is also mentioned that the value of D^{m}\delta(-a)D^{k}\delta(0) and D
  • #1
mhill
189
1
let be the distribution

[tex] D^{m} \delta (x-a) D^{k} \delta (x) [/tex]

my questions are , what happens whenever x=a or x=a ??

is this identity correct

[tex] \delta (x-a) = e^{-a D} \delta (x)= \sum_{n=0}^{\infty}(-a)^{n} \frac{D^{n}}{n!}\delta (x) [/tex]
 
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  • #2
I don't understand the first question, but this

mhill said:
is this identity correct

[tex] \delta (x-a) = e^{-a D} \delta (x)= \sum_{n=0}^{\infty}(-a)^{n} \frac{D^{n}}{n!}\delta (x) [/tex]

is correct if you using such test functions that the Taylor series work for them. It can be checked with integration by parts. If the Taylor series don't converge for the test functions, then this distribution thing stops working as well.
 
  • #3
mhill said:
what happens whenever x=a or x=a ??
This doesn't make sense to me. What meaning did you intend?
 
  • #4
Probably meant to say x=a or x=0, since the expression contains the terms δ(x-a) and δ(x-0).
 
  • #5
I meant that the idea of "plugging in" a value for x doesn't appear to make sense in this context.
 
  • #6
the idea is

[tex] D^{m} \delta (x-a) D^{k} \delta (x) [/tex] however the value

[tex] D^{m} \delta (-a) D^{k} \delta (0) [/tex] and [tex] D^{m} \delta (0) D^{k} \delta (a) [/tex]

is not defined since delta functions are just oo

another question , how would we define [tex] \int_{-\infty}^{\infty}dx D^{m} \delta (x-a) D^{k} \delta (x) [/tex]

also , under suitable test function f , then

[tex] < f | \delta (x-a) > = \sum_{n=0}^{\infty} (-a)^{n} \frac{ < \delta | D^{n} f>}{n!} [/tex]

although it would make no sense , i think we could say

[tex] (2\pi ) i^{m}D^{m}\delta (0) = \int_{-\infty}^{\infty}dx x^{m} [/tex] which is divergent... although in Cauchy's principal value the integral should be 0 for m Odd
 
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FAQ: The Distribution of Delta Functions

What is a distribution question?

A distribution question is a type of statistical question that asks about the frequency or spread of a certain variable or data set. It is used to understand the pattern or distribution of a data set and to make inferences about the entire population from a sample.

What are the types of distributions?

There are several types of distributions, including normal distribution, uniform distribution, binomial distribution, and exponential distribution. Each type of distribution has its own unique characteristics and is used to model different types of data.

How do you calculate the mean, median, and mode of a distribution?

The mean, median, and mode are measures of central tendency that can be calculated from a distribution. The mean is calculated by adding all the values in the distribution and dividing by the total number of values. The median is the middle value in a sorted distribution, and the mode is the most frequently occurring value.

What is the difference between a population and a sample in a distribution question?

A population is the entire group of individuals or items that are being studied. A sample is a smaller subset of the population that is used to make inferences about the entire population. Distribution questions often involve analyzing a sample in order to make conclusions about the larger population.

Why is understanding distributions important in scientific research?

Understanding distributions is crucial in scientific research because it allows researchers to analyze and interpret data, make predictions, and draw conclusions about a larger population. It also helps to identify patterns and outliers in the data that may be significant in understanding the phenomenon being studied.

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