Convolution of exp(-a*norm(x)^2) and exp(-b*norm(x)^2) ?

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The convolution of the functions exp(-a*norm(x)^2) and exp(-b*norm(x)^2) can be computed efficiently using the Fourier transform. Both functions are Gaussian, and their Fourier transforms remain Gaussian functions. The multiplication of these transforms simplifies the convolution process, allowing for straightforward computation using the properties of Gaussian transforms. The key to this method lies in applying the correct formula for Gaussian transforms.

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How do I compute convolution of exp(-a*norm(x)^2) and exp(-b*norm(x)^2) where a,b > 0 and x belongs to Rn?

I wonder if there is an easy way to compute this convolution using Fourier transform.
 
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The convolution becomes simple multiplication after Fourier transforming. The two functions you have are gaussian functions, their FT is still a gaussian function, so is the product, and finally so is the antitransform. All you need is the formula for gaussian transforms.
 

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