Fourier transform of function which has only radial dependence

In summary, the author discusses why the angle ## \theta ## is chosen in the equation for the 3d Fourier transform of a function which has only radial dependence, and explains that this choice makes the resulting integrals easier to evaluate.
  • #1
LagrangeEuler
717
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3d Fourier transform of function which has only radial dependence ##f(r)##. Many authors in that case define
[tex]\vec{k} \cdot \vec{r}=|\vec{k}||\vec{r}|\cos\theta[/tex]
where ##\theta## is angle in spherical polar coordinates.
So
[tex]\frac{1}{(2\pi)^3}\int\int_{V}\int e^{-i \vec{k} \cdot \vec{r}}f(r)=\frac{1}{(2\pi)^3}\int^{\infty}_0r^2f(r)dr\int^{\pi}_0\sin \theta d\theta \int^{2 \pi}_0 d\varphi e^{-ikr\cos \theta}[/tex]
Ok function ##f(r)## does not depend on angles, but why here we have specially angle ## \theta##?
 
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  • #2
You are missing a factor of ## f(r) ## in your radial integral, and the exponential factor belongs inside the ##\theta## integral, which is important to note (see below). Also, the ##\theta## integral itself goes inside the radial integral.

The reason the angle ## \theta ## is chosen is that we can always choose the coordinate system so that the wave vector ## \mathbf{k} ## is aligned with the ## z ## axis. That is what enables us to write ## \mathbf{k}\cdot\mathbf{r} = kr\cos\theta ##. Then the integral ##\int_0^\pi \sin\theta e^{-ikr\cos\theta} d\theta ## is easy to evaluate via substitution.

If we had instead chosen for ## \mathbf{k} ## to be along, say, the ##x## axis, then we would have had ## \mathbf{k}\cdot\mathbf{r} = kr\cos\phi ##. We would now have to evaluate the integral ## \int_0^{2\pi} e^{-ikr\cos\phi} d\phi ##, which is not so easy!
 
  • #3
Thank you very match. And when I may use that is not so important which coordinate system I will use? Only in the case when ##f(\vec{r})=f(r)##?
 
  • #4
If ## f ## dependent on, say, both ##r## and ##\theta##, that trick might still help. The ##\theta ## integral would become ## \int_0^{\pi} f(r,\theta) e^{-ikr\cos\theta}d\theta##. Depending on the form of ## f(r,\theta) ##, you might still be able to either evaluate the integral exactly or, failing that, do an asymptotic approximation via, e.g., the method of steepest descent or the method of stationary phase.
 
  • #5
Yes but my real question here about this is

if ##F[f(\vec{r})]=\tilde{f}(\vec{k})## why should I put in general case that direction of ##\vec{k}## is z axis?
 
  • #6
Because, as a rule of thumb, it makes the resulting integrals easier to evaluate. I can't see any reason why it would have to, though (in the general case).
 
  • #7
Yes but it is just when function is isotropic I think. I think that this relation is wrong for example

[tex]\frac{1}{(2\pi)^3}\int\int_{V}\int e^{-i \vec{k} \cdot \vec{r}}f(\vec{r})=\frac{1}{(2\pi)^3}\int^{\infty}_0r^2dr\int^{\pi}_0\sin \theta e^{-ikr\cos \theta} d\theta \int^{2 \pi}_0 d\varphi f(\vec{r})[/tex]
is wrong because if argument of function ##f(\vec{r})## depends on two angles, then

[tex]\frac{1}{(2\pi)^3}\int^{\infty}_0r^2dr\int^{\pi}_0\sin \theta e^{-ikr\cos \theta} d\theta \int^{2 \pi}_0 d\varphi f(\vec{r}) \neq \frac{1}{(2\pi)^3}\int^{\infty}_0r^2dr\int^{\pi}_0\sin \theta d\theta \int^{2 \pi}_0 d\varphi e^{-ikr\cos \varphi}f(\vec{r}) [/tex]
will be different (if I calculate both somehow) for some general form of ##f(\vec{r})##. This will be always the same to my mind only in case

[tex]\frac{1}{(2\pi)^3}\int^{\infty}_0r^2dr\int^{\pi}_0\sin \theta e^{-ikr\cos \theta} d\theta \int^{2 \pi}_0 d\varphi f(r) = \frac{1}{(2\pi)^3}\int^{\infty}_0r^2dr\int^{\pi}_0\sin \theta d\theta \int^{2 \pi}_0 d\varphi e^{-ikr\cos \varphi}f(r) [/tex]
 
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  • #8
I'm not sure I understand your placement of the integrands. For example, if ## f ## depends only on ## r ##, I would write something like

## \frac{1}{(2\pi)^3} \int_0^{2\pi} d\phi \int_0^{\infty} f(r) r^2 \left[ \int_0^{\pi} \sin\theta e^{-ikr\cos\theta} d\theta \right] dr ##

because the integral in square brackets will end up depending on ## r ##. Also, note that if ## \theta ## is the polar angle, then it's ## \theta ## that appears in the exponential, not ## \phi ##.

I know that sometimes in physics we just pile everything in front of the integral signs; at the same time, that can be confusing if what variables to integrate over are at issue. If ## f ## depends on both ## r ## and ## \theta ##, then we would instead have, e.g.,

## \frac{1}{(2\pi)^3} \int_0^{2\pi} d\phi \int_0^{\infty} r^2 \left[ \int_0^{\pi} f(r,\theta) \sin\theta e^{-ikr\cos\theta} \right] dr ##

Depending on the specific form that ## f(r,\theta) ## takes, the integral may or may not be tractable using this "## \mathbf{k} ## along the ## z ## axis" technique.

(sorry for the profuse editing)
 
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Related to Fourier transform of function which has only radial dependence

What is a Fourier transform?

A Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It is used to analyze signals and can also be used to solve differential equations.

What is the radial dependence of a function?

Radial dependence refers to the dependence of a function on the distance from a central point. In other words, how the function changes as you move further away from the center.

How is the Fourier transform of a function with only radial dependence different from a general Fourier transform?

The Fourier transform of a function with only radial dependence is a one-dimensional transform, while a general Fourier transform is typically a multi-dimensional transform. This is because the function only varies with distance from a central point, rather than varying with multiple independent variables.

What is the significance of a function having only radial dependence in the Fourier transform?

A function with only radial dependence in the Fourier transform has rotational symmetry, meaning it looks the same when rotated around the central point. This can be useful in analyzing and solving problems involving circular or spherical shapes.

What applications does a Fourier transform of a function with only radial dependence have?

The Fourier transform of a function with only radial dependence has many applications in physics, engineering, and other fields. It can be used to analyze signals in circular or spherical systems, solve differential equations with rotational symmetry, and more.

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