Evaluating the Gaussian integral

In summary, the standard method seems to be to evaluate the gaussian integral by first squaring it, then using Fubini's theorem to turn it into an area integral, and finally using Fubini's theorem again to turn it back into an iterated integral.
  • #1
loom91
404
0
Hi,

I'm trying to evaluate the standard Gaussian integral

[tex]\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}[/tex]

The standard method seems to be by i)squaring the integral, ii)then by setting the product of the two integrals equal to the iterated integral constructed by composing the two integrals, iii)using Fubini's theorem to turn this into an area integral and iv)then using Fubini's theorem again to turn this back into an iterated integral, this time in polar coordinates.

Of these, (ii) seems impossible to me. Why would the iterated integral be equal to the product of the two integrals taken separately? Even if this were the case, this does not seem like a result so trivial that you could use it without any justification. Are there other ways to evaluate the integral? Thanks.

Molu
 
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  • #2
ii) & not iii) uses Fubini's theorem.

Daniel.

BTW, it's "\infty" that gives the symbol [itex] \infty [/itex]
 
  • #3
dextercioby said:
ii) & not iii) uses Fubini's theorem.

Daniel.

BTW, it's "\infty" that gives the symbol [itex] \infty [/itex]

That's what I wrote, and thanks for the infinity.
 
  • #4
The fact that
[tex]\left(\int_{-\infty}^\infty f(x)dx\right)\left(\int_{-\infty}^\infty g(y)dy= \int_{-\infty}^\infty f(x)g(y)dxdy= \int\int_A f(x)g(y)dA[/tex]
where A is all of R2, is Fubini's theorem.
 
  • #5
HallsofIvy said:
The fact that
[tex]\left(\int_{-\infty}^\infty f(x)dx\right)\left(\int_{-\infty}^\infty g(y)dy= \int_{-\infty}^\infty f(x)g(y)dxdy= \int\int_A f(x)g(y)dA[/tex]
where A is all of R2, is Fubini's theorem.

Checking again, I see that there are two parts to Fubini's theorem of which (ii) uses one part (product of integrals=double integral) and (iii) and (iv) use the other (double integral=iterated integral). In any case, is this the only way to evaluate the gaussian integral?
 

1. What is the Gaussian integral?

The Gaussian integral, also known as the error function, is a mathematical function that describes the area under a bell-shaped curve. It is commonly used in statistics and physics to calculate probabilities and solve differential equations.

2. Why is evaluating the Gaussian integral important?

Evaluating the Gaussian integral is important because it allows us to solve a wide range of problems in mathematics, physics, and statistics. It is used to calculate the probability of events occurring in a normal distribution and to solve equations that involve the error function.

3. What is the formula for the Gaussian integral?

The formula for the Gaussian integral is:
∫e-x2 dx = √π

4. How is the Gaussian integral evaluated?

The Gaussian integral is evaluated using various methods such as integration by parts, substitution, and numerical approximations. The most commonly used method is integration by parts, which involves breaking down the integral into smaller, solvable parts.

5. What are the applications of the Gaussian integral?

The Gaussian integral has many applications in mathematics, physics, and statistics. It is used to solve differential equations, calculate probabilities and areas under curves, and in the study of heat transfer, diffusion, and quantum mechanics.

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