Proving the Limit of Dirac Delta from Normal Distribution

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Homework Help Overview

The discussion revolves around demonstrating that the Dirac delta function can be understood as the limit of the normal distribution. Participants reference the mathematical definition of the Dirac delta and explore its properties in relation to distributions.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the need to show that the Dirac delta function satisfies specific properties and how the limit of the normal distribution can be approached. There are mentions of convolution with test functions and the role of convergence factors in the integrand.

Discussion Status

Some participants have offered insights into the definitions and properties required for the proof, while others are exploring the implications of these definitions. There is an ongoing examination of the conditions under which the limit holds, particularly regarding the choice of test functions.

Contextual Notes

There are mentions of the need for test functions to be infinitely differentiable, indicating constraints on the types of functions that can be used in the discussion.

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Homework Statement


How would one show that dirac delta is the limit of the normal distribution?
http://en.wikipedia.org/wiki/Dirac_delta
using the definition [tex]\delta(k) = 1/(2\pi)\int_{-\infty}^{\infty}e^{ikx}dx[/tex]

Homework Equations


The Attempt at a Solution

 
Last edited:
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Equality for distributions is defined pointwise. You just have to prove you get the same value if you convolve either one with a test function. I.E. for any test function f, you have to prove

[tex] \int_{-\infty}^{+\infty} \delta(k) f(k) \, dk<br /> =<br /> \frac{1}{2\pi} \int_{-\infty}^{+\infty} \int_{-\infty}^{+\infty}<br /> e^{ikx} f(k) \, dk \, dx[/tex]
 
One way (not so rigorous mathematically) to define the delta function is that it is a function that satisfies [tex]\delta(x)=0[/tex] if [tex]x\ne 0[/tex], and [tex]\textstyle \int_{-\infty}^{+\infty}dx\;\delta(x)=1.[/tex] So you need to show (1) that the limit of the normal distribution has these properties, and (2) that [tex]\textstyle{1\over2\pi}\int_{-\infty}^{+\infty}dk\;e^{ikx}[/tex] has these properties. Part (1) is easy. Amusingly, the easiest way to do part (2) is to define it by inserting a convergence factor of [tex]\exp(-\epsilon^2 k^2/2)[/tex] into the integrand, which turns it into a normal distribution that becomes a delta function in the limit [tex]\epsilon\to 0.[/tex]
 
Oh, hah, I misread the problem. I thought the equation the OP posted was the equation he wanted to prove.

The idea is the same, though. For a distribution F(_) and a family of distributions G(_, y), to prove

[tex] F(x) = \lim_{y \rightarrow 0} G(x, y)[/tex]

you have to show

[tex] \int F(x) f(x) \, dx = \lim_{y \rightarrow 0} \int G(x, y) f(x) \, dx[/tex]
 
Can I choose any f(x)?
 
It has to be infinitely differentiable, or something like that (not up on my rigorous defs, sorry), but otherwise yes.
 

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