Gaussian Summation - Find Out the Result!

In summary, the conversation discusses the result of a discrete Gaussian function in x, which is found to be \frac{1 + \vartheta_3(0,e^{-1/a})}{2} where \vartheta_b(x,q) is a theta function. The theta function is defined as \vartheta_3(z,q) = \sum_{n=-\infty}^\infty q^{n^2} e^{2\pi i z}. It is mentioned that this result may be available in Mathematica and Matlab, but there may not be a way to compute it without referencing the theta function.
  • #1
mfengwang
2
0
Hi,
We know that the Gaussian integral is
[tex]\int_{-\infty}^{+\infty}e^{-\frac{x^2}{a^2}}dx=a\sqrt{\pi}[/tex]
However, if the gaussian function is discrete in x, what is the result of
[tex]\sum_{n=0}^{+\infty}e^{-\frac{n^2}{a}} = \\?[/tex]
where n is natural number, that is n=0,1,2,3....
 
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  • #2
I checked Wolfram alpha; it gives the result as

[tex]\frac{1 + \vartheta_3(0,e^{-1/a})}{2},[/tex]

where [itex]\vartheta_b(x,q)[/itex] is a theta function. Looking up the definition of the theta function on mathworld reveals that the result is pretty much by definition:

[tex]\vartheta_3(z,q) = \sum_{n=-\infty}^\infty q^{n^2} e^{2\pi i z}[/tex]

Rearrangement and plugging in z = 0, q = e^(-1/a) gives the result, although it's not very enlightening. The theta function is a special function that should be available in mathematica and perhaps matlab.

I'm not sure if, setting a = 1 for example, there is a way to compute the resulting value without reference to the theta function.
 
  • #3
Thanks a lot! It's really a great help to me. :smile::smile::smile:
 

FAQ: Gaussian Summation - Find Out the Result!

What is Gaussian summation?

Gaussian summation is a mathematical method used to find the sum of a series of numbers that follow the Gaussian (normal) distribution. This method is commonly used in statistics and probability to calculate the total area under the curve of a normal distribution.

How do you calculate the result of a Gaussian summation?

To calculate the result of a Gaussian summation, you first need to determine the mean and standard deviation of the given data set. Then, you use a formula called the Gaussian integral to find the area under the curve. This integral involves solving an indefinite integral, which can be done through various methods such as substitution or integration by parts.

When is Gaussian summation used?

Gaussian summation is commonly used in statistics and probability, particularly in situations where the data follows a normal distribution. This distribution is often observed in natural phenomena such as human height, IQ scores, and measurement errors.

What is the significance of Gaussian summation?

Gaussian summation is significant because it allows us to calculate the area under a normal distribution curve, which is crucial in various statistical analyses. It also helps us understand the behavior and characteristics of a data set by providing insights into its central tendency and variability.

Can Gaussian summation be used for non-normal distributions?

While Gaussian summation is specifically designed for normal distributions, it can also be used for non-normal distributions that are approximately normal. This is because the normal distribution is a commonly observed pattern in nature, and many data sets exhibit characteristics of normality.

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