Fourier transform from k-space to x

In summary, the conversation discusses the process of finding the Fourier transform of a k-space function and using the residue theorem for the integral. The issue with the calculation is determined to be the use of a contour that does not encircle the pole at k=0. The solution is to use a closed contour with a small semi-circular arc and a large arc, the direction of which depends on the value of x. The conversation ends with a suggestion to try computing the integral with this new approach.
  • #1
jmm5872
43
0
I have calculated a k-space function to be f(k) = [itex]\frac{1}{2k}[/itex]

I want to Fourier transform this to find f(x), I have found many different Fourier transform equations...can I use this one?

f(x) = [itex]\frac{1}{\sqrt{2π}}[/itex][itex]\int[/itex][itex]\frac{1}{2k}[/itex]e-ikxdk Limits fo integration -Infinity to Infinity

I'm also having trouble remembering my complex analysis, would I use residue theorem for this integral? I don't quite remember exactly how that goes...

∫f(z) = 2πiRes(f,z0) Correct?

The residue for f(k) is 1/2, so I am not sure excatly what the answer means? Or if I am using residue theorem correctly?

Final answer: f(x) = [itex]\frac{1}{\sqrt{2π}}[/itex]2πi(1/2) = [itex]\sqrt{\frac{π}{2}}[/itex]i
This doesn't make sense as an answer.

Thanks,
Jason
 
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  • #2
jmm5872 said:
I have calculated a k-space function to be f(k) = [itex]\frac{1}{2k}[/itex]

I want to Fourier transform this to find f(x), I have found many different Fourier transform equations...can I use this one?

f(x) = [itex]\frac{1}{\sqrt{2π}}[/itex][itex]\int[/itex][itex]\frac{1}{2k}[/itex]e-ikxdk Limits fo integration -Infinity to Infinity

I'm also having trouble remembering my complex analysis, would I use residue theorem for this integral? I don't quite remember exactly how that goes...

∫f(z) = 2πiRes(f,z0) Correct?

The residue for f(k) is 1/2, so I am not sure excatly what the answer means? Or if I am using residue theorem correctly?

Final answer: f(x) = [itex]\frac{1}{\sqrt{2π}}[/itex]2πi(1/2) = [itex]\sqrt{\frac{π}{2}}[/itex]i
This doesn't make sense as an answer.

Thanks,
Jason

The issue with your calculation is that you seem to have forgotten that the residue theorem applies when the contour you are integrating over completely encircles a pole in the complex plane. What you calculated is the integral over a contour around the point k = 0. The integral you want to calculate is

$$\frac{1}{\sqrt{2\pi}} \int_{-\infty}^\infty dk~\frac{e^{-ikx}}{k},$$
so you need a closed contour, at least one piece of which runs along the real axis while avoiding the pole at k = 0. One typically skirts around the pole with a semi-circular arc of small radius ##\epsilon##, and then closes the contour with an arc of radius R, either in the upper half plane or the lower half plane. One takes ##R \rightarrow \infty## and ##\epsilon \rightarrow 0## at the end of the calculation.

There are a number of important things to note about such a contour: 1) the pole is not enclosed by it, so the full contour integral is zero; the integrals along the segments of the contour thus sum to zero. 2) Which half-plane (negative or positive) you close the large arc in will depend on whether or not x is positive or negative.

Have you computed a contour integral like this before? Give it a shot and see what you find.
 

FAQ: Fourier transform from k-space to x

What is a Fourier transform from k-space to x?

A Fourier transform from k-space to x is a mathematical operation that converts data from the k-space domain to the x-space domain. It is used in various fields of science and engineering to analyze signals and images.

Why is a Fourier transform from k-space to x important?

A Fourier transform from k-space to x is important because it allows us to understand the frequency components of a signal or image. This allows us to analyze and manipulate the data in a more meaningful way.

How does a Fourier transform from k-space to x work?

A Fourier transform from k-space to x works by decomposing a signal or image into its constituent frequencies. This is done by representing the data as a sum of sine and cosine waves, each with a different magnitude and phase. The Fourier transform then converts this representation from the k-space domain to the x-space domain.

What are some applications of a Fourier transform from k-space to x?

A Fourier transform from k-space to x has many applications in science and engineering. It is commonly used in signal processing, image processing, and data analysis. It is also used in fields such as physics, chemistry, and biology to analyze and interpret experimental data.

Are there any limitations to a Fourier transform from k-space to x?

While a Fourier transform from k-space to x is a powerful tool, it does have some limitations. For example, it assumes that the data is continuous and infinite, which is not always the case in real-world applications. Additionally, it may not be suitable for analyzing non-stationary or non-periodic signals.

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