Is the Convolution of Two Gaussians Always a Gaussian?

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Homework Help Overview

The discussion revolves around the convolution of two Gaussian functions and whether this operation always results in another Gaussian. The original poster expresses a desire to see the integration worked out, indicating a need for clarification on this topic.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the explicit form of the convolution integral and question whether it can be derived. Some suggest writing out the convolution explicitly for two standard Gaussians. Others provide a method to simplify the expression and reference properties of Fourier transforms related to Gaussian functions.

Discussion Status

There are multiple lines of reasoning being explored, including direct computation and properties of Fourier transforms. Some participants have provided helpful insights into the mathematical properties of Gaussians, but no consensus has been reached on the original question.

Contextual Notes

The original poster is seeking resources or direct assistance with the integration, indicating a possible constraint in their current understanding or access to materials. The discussion includes references to specific mathematical properties and methods without resolving the initial inquiry.

nshiell
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I've read on a bunch of websites that the convolution of two gaussians produces another gaussian however I have not seen this integration worked out. I am working on an integral which has a similar form as this convolution so it would be a great help too see. Does anyone know a book or website or wants to type out the answer for me? Thanks a lot.

Nicholi.
 
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nshiell said:
Does anyone know a book or website or wants to type out the answer for me?
Nicholi.

Could you not write out the convolution explicitly (even for two standard gaussians) ?
 
int(exp(-x^2)*exp(-(r-x)^2))dx

there is the limits are +/- infinity
 
You can use another method for this:

\exp\left[ -x^2 \right] \exp\left[ -(r-x)^2 \right] = <br /> \exp\left[ -2 x^2 + 2 r x - r^2 \right] = <br /> \exp\left[ -2 (x + r/2)^2 \right] \exp\left[ - r^2 / 2 \right]<br />
where the last term does not depend on x and the first one is just another Gaussian, but centered around a different point.
 
Thanks!
 
CompuChip said:
You can use another method for this:

\exp\left[ -x^2 \right] \exp\left[ -(r-x)^2 \right] = <br /> \exp\left[ -2 x^2 + 2 r x - r^2 \right] = <br /> \exp\left[ -2 (x + r/2)^2 \right] \exp\left[ - r^2 / 2 \right]<br />
where the last term does not depend on x and the first one is just another Gaussian, but centered around a different point.

This only shows c) here below.

Another argument, besides direct computation, is by standard properties of Fourier transform:
a) Fourier transform of a gaussian is a gaussian
b) Fourier transform of convolution product = pointwise product of Fourier transforms (up to choice of normalisation)
c) pointwise product of gaussians is gaussian.
d) inverse Fourier transform of a gaussian is gaussian.
 

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