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I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

Clarification: I am not asking about the fact the'the convolution of independent GaussianGaussians is GaussianGaussian'.

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

Clarification: I am not asking about the fact the convolution of independent Gaussian is Gaussian.

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

Clarification: I am not asking about the fact 'the convolution of independent Gaussians is Gaussian'.

clarified
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I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

Clarification: I am not asking about the fact the convolution of independent Gaussian is Gaussian.

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

Clarification: I am not asking about the fact the convolution of independent Gaussian is Gaussian.

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I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for tesethese ideas?

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for tese ideas?

I'm taking a course on topology and probabily. Today, the professor remarked something along the lines of:

If you look at the space of probability distributions with $0$ mean and variance $1$, equipped with convolution, then the Gaussian distribution is characterized as the fixed point of each orbit."

He also said this was a nice way to appreciate the importance of the gaussian distribution, and to gain insight for the central limit theorem.

I asked for references on this point of view, but he said it's not standard and recalled only hearing about it in some seminar forty years ago.

Where can I find a (preferably grad-level) reference for these ideas?

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  • 935
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