Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ##

In summary: I'm sorry, I don't understand what you mean by "2D Green's function."In summary, the attempted solution for Poisson's equation using spherical coordinates converges for n>2, but the last two integrals don't seem to be going to converge nicely.
  • #1
MisterX
764
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Homework Statement


This comes up in the context of Poisson's equation
Solve for ##\mathbf{x} \in \mathbb{R}^n ## $$ \nabla^2 G(\mathbf{x}) = \delta(\mathbf{x})$$

Homework Equations


$$\int_0^\pi \sin\theta e^{ikr \cos\theta}\mathop{dk} = \int_{-1}^1 e^{ikr \cos\theta}\mathop{d\cos \theta
}$$

The Attempt at a Solution


Attempt by using Fourier Transforms
$$ \nabla^2 G(\mathbf{x}) = \delta(\mathbf{x}) \Rightarrow -\lVert k\rVert^2 \tilde{G}(\mathbf{k}) = 1$$
$$ G(\mathbf{x}) = -\mathcal{F}^{-1}\left[ \lVert k\rVert^{-2} \right]$$
I reasoned that we could use N-dimensional spherical coordinates and be left with an integral integral over one angle in the plane between ##\mathbf{k}## and ##\mathbf{x}## and a radial integral which would have an element ##k^{n-1}\,dk ## where ##n## is the number of dimensions.
$$G\left(\mathbf{x}\right) = \frac{-1}{(2\pi)^n}\int k^{n-1}F(\phi_1,\dots,\phi_{n-3})\sin(\phi_{n-2})\mathop{dk d\phi_1 \dots d\phi_{n-2}d\phi_{n-1}} \frac{e^{ikr\cos \phi_{n-2}}}{k^2} $$
with ##u = \cos \phi_{n-2}##
$$G\left(\mathbf{x}\right) = \frac{-1}{(2\pi)^n}\int F(\phi_1,\dots,\phi_{n-3})\mathop{d\phi_1 \dots d\phi_{n-3}d\phi_{n-1} }\int_{-1}^{1} du\int_0^\infty\mathop{dk} k^{n-3} e^{ikru}$$
Maybe I'm not thinking clearly but the last two integrals don't seem like they are going to converge to anything nice. I don't know if I've made a mistake or I need to take these integrals in a particular order. I know I can show the Green's function is proportional to ##|| r||^\alpha ## for ##n>2## by using a test function, but the the idea here is to calculate it directly without assuming that much about its form.
 
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  • #2
MisterX said:

Homework Statement


This comes up in the context of Poisson's equation
Solve for ##\mathbf{x} \in \mathbb{R}^n ## $$ \nabla^2 G(\mathbf{x}) = \delta(\mathbf{x})$$

Homework Equations


$$\int_0^\pi \sin\theta e^{ikr \cos\theta}\mathop{dk} = \int_{-1}^1 e^{ikr \cos\theta}\mathop{d\cos \theta
}$$

The Attempt at a Solution


Attempt by using Fourier Transforms
$$ \nabla^2 G(\mathbf{x}) = \delta(\mathbf{x}) \Rightarrow -\lVert k\rVert^2 \tilde{G}(\mathbf{k}) = 1$$
$$ G(\mathbf{x}) = -\mathcal{F}^{-1}\left[ \lVert k\rVert^{-2} \right]$$
I reasoned that we could use N-dimensional spherical coordinates and be left with an integral integral over one angle in the plane between ##\mathbf{k}## and ##\mathbf{x}## and a radial integral which would have an element ##k^{n-1}\,dk ## where ##n## is the number of dimensions.
$$G\left(\mathbf{x}\right) = \frac{-1}{(2\pi)^n}\int k^{n-1}F(\phi_1,\dots,\phi_{n-3})\sin(\phi_{n-2})\mathop{dk d\phi_1 \dots d\phi_{n-2}d\phi_{n-1}} \frac{e^{ikr\cos \phi_{n-2}}}{k^2} $$
with ##u = \cos \phi_{n-2}##
$$G\left(\mathbf{x}\right) = \frac{-1}{(2\pi)^n}\int F(\phi_1,\dots,\phi_{n-3})\mathop{d\phi_1 \dots d\phi_{n-3}d\phi_{n-1} }\int_{-1}^{1} du\int_0^\infty\mathop{dk} k^{n-3} e^{ikru}$$
Maybe I'm not thinking clearly but the last two integrals don't seem like they are going to converge to anything nice. I don't know if I've made a mistake or I need to take these integrals in a particular order. I know I can show the Green's function is proportional to ##|| r||^\alpha ## for ##n>2## by using a test function, but the the idea here is to calculate it directly without assuming that much about its form.

The last table in
http://en.wikipedia.org/wiki/Fourier_transform
seems to have this entry; it has a function whose transform is ##||k||^{-(n-\alpha)}, \; 0 < \alpha < n##, and yours is for ##\alpha = n-2##. Of course, the results are essentially stated without proof.
 
  • #3
Yes, I am seeking to prove that result.
 
  • #4
Perhaps you could introduce a convergence factor ##e^{-\lambda k}## and then take the limit as ##\lambda \to 0^+##.
 
  • #5
That will just be equivalent to ignoring the other endpoint which perhaps needs justification. If you proceed this way you should obtain$$ \int_0^\infty k^\eta e^{-ikru} = \frac{\Gamma(\eta + 1)}{(-iru)^{\eta+1}}\;, \eta >-1$$

$$\eta = n-3 > -1 \Rightarrow n>2 $$

So now we expect the integral of F() over the variables besides k and u to give us something like $$\frac{\text{Surface Area(k)}}{k^{n-1}}\frac{1}{2} $$
 
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  • #6
This should also be equivalent to considering the integral to be over a complex parameter k and closing the contour in the first octant (for positive u). This should reduce the integral to an integral along the positive imaginary axis, where the exponential is ##e^{-kru}##. For negative u you would have to close the contour in the fourth octant instead. Note that I did not try this explicitly, but I think it seems like a reasonable thing to do.

For ##n = 2##, the integral is not convergent for small k and you have to regulate it by adding something that evaluates to a (in principle infinite) constant. This is related to the 2D Green's function being of the form ##\ln(r/r_0)##, where ##r_0## will depend on your regularisation.
 
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  • #7
Orodruin said:
This should also be equivalent to considering the integral to be over a complex parameter k and closing the contour in the first octant (for positive u).
I am skeptical because the return path integral will have imaginary bounds. Using this equivalence does not seem to help. An imaginary number will appear either in your integration bounds or in the exponential.Something like
$$\int _0^\infty f(iz)dz = -i\int_{i\infty}^{i0} f(u) du $$
is not necessarily that useful.
Vela's suggestion may simply be the way forward or perhaps there is another approach.
 
  • #8
Exactly, you want an additional i to appear in the exponential so that you get rid of the i that is already there. The imaginary units that appear due to k^m are just constants multiplying the integral. In the end it is very similar to what vela is suggesting although fully taking the rotation in the complex plane rather than letting it go to zero.

The return path is from ##z = i\infty## to ##z = 0## along the imaginary axis. This can be parametrised in terms of the real number ##t## using ##z = it##, giving you a real integral multiplied by i to some power.

The total integral is
$$
0 = \int_C f(z) dz = \int_0^\infty f(z) dz + \int^0_{i\infty} f(z) dz \quad \Rightarrow \quad \int_0^\infty f(z) dz = - \int^0_{i\infty} f(z) dz,
$$
where ##C## is the full contour and I have assumed that you can show that the contribution from 0 and the closing contour at infinity go to zero. In the second integral you do the parametrisation ##z = it##, giving you
$$
\int_0^\infty f(z) dz = i \int_0^{\infty} f(it) dt.
$$
Inserting your ##f(z) = z^m \exp(izur)## should give ##f(it) = i^m t^m \exp(-tur)## upon which the right integral can be solved.
 

FAQ: Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ##

1. What is the Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ##?

The inverse Fourier transform of ##1/k^2## in ##\mathbb{R}^N ## is a mathematical operation that converts a function in the frequency domain to its corresponding function in the spatial or time domain. In simpler terms, it is a way to analyze a function by breaking it down into its individual frequency components.

2. What is the significance of ##1/k^2## in ##\mathbb{R}^N ##?

The function ##1/k^2## in ##\mathbb{R}^N ## is known as the "inverse square" function and is commonly used in physics and engineering to describe the relationship between two quantities that are inversely proportional to the square of the distance between them. It also appears in various mathematical models and equations, such as the inverse square law of gravitation.

3. How is the Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ## calculated?

The Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ## can be calculated using the formula: $$f(x) = \frac{1}{(2\pi)^N} \int_{-\infty}^{\infty} \hat{f}(k) e^{ikx} dk$$ where ##\hat{f}(k)## represents the Fourier transform of the function ##f(x)##.

4. What are some real-world applications of the Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ##?

The Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ## has numerous applications in physics, engineering, and signal processing. It is used to analyze and interpret signals, such as sound and image data, in the time domain. It is also useful in solving differential equations and in studying the behavior of physical systems.

5. What are some limitations of using the Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ##?

While the Inverse Fourier Transform of ##1/k^2## in ##\mathbb{R}^N ## is a powerful tool in signal analysis and mathematical modeling, it does have some limitations. For example, it can only be applied to functions that are integrable, and it may not be able to accurately represent functions that have sharp discontinuities or singularities. Additionally, it requires a good understanding of the underlying mathematics and may be computationally intensive for complex functions.

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