Fourier transform with Mathematica (Dirac mean position eigenfunction)

In summary, the conversation discusses the difficulty of calculating the Fourier transform of a mean-position eigenfunction of the Dirac equation using Mathematica. The function in question is not square integrable and is approximately equal to k. However, the exact spatial extent is important and the function is a Dirac delta in the untransformed representation.
  • #1
Jacob
5
0
Mathematica can't calculate Fourier transform (Dirac mean position eigenfunction)

Hi, I'm attempting to use Mathematica to calculate a mean-position eigenfunction of the Dirac equation. To do so I need to evaluate Fourier transforms (from p-space to r-space) of wavefunctions dependent on:

[tex]

\frac1{{\sqrt{{({1+{k^2}+{\sqrt{1+{k^2}}}})}}}}

[/tex]

where k is in units of the Compton wavevector.

Mathematica is unable to evaluate the FT of the above (either Fourier sine transform or normal FT). Can anyone give any suggestions as to how I could evaluate it?

More specifically, I am making a reverse Foldy-Wouthuysen transformation of a mean-position eigenfunction in p-space, then transforming the result into r-space assuming spherical symmetry. The first component of the r-space eigenfunction is given by the Fourier sine transform of:

[tex] k\,{\sqrt{1+{\frac1{\sqrt{1+{k^2}}}}}} [/tex]

Thanks for any help.
 
Last edited:
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  • #2
Hi again, have I posted this in the right forum? If not please suggest where I'm most likely to get an answer!

Otherwise I would be very grateful if anyone could tell me either how to Fourier transform:

[tex] k\,{\sqrt{1+{\frac1{\sqrt{1+{k^2}}}}}} [/tex]

or that it is not possible to do so.
 
  • #3
I sure can't, but the function isn't square integrable over k-space in any case.

Also, it is in very good approximation equal to k.
 
  • #4
Thanks :).

Unfortunately it's the difference from k that's important as it is the exact spatial extent of the wavefunction which is of interest (it is a Dirac delta in the untransformed Foldy-Wouthuysen representation since it's a mean position eigenfunction and mean position = r in that representation).
 
Last edited:

Related to Fourier transform with Mathematica (Dirac mean position eigenfunction)

1. What is the Fourier transform?

The Fourier transform is a mathematical tool used to decompose a function into its constituent frequencies. It converts a function from the time or spatial domain to the frequency domain, allowing for analysis and manipulation of the function in terms of its frequency components.

2. How does Mathematica compute the Fourier transform?

Mathematica uses the Fast Fourier Transform (FFT) algorithm to efficiently compute the Fourier transform. This algorithm uses mathematical shortcuts to calculate the transform much faster than traditional methods.

3. What is the Dirac mean position eigenfunction in relation to the Fourier transform?

The Dirac mean position eigenfunction is a function used to represent a single point in the frequency domain. It is used in the Fourier transform to represent the amplitude and phase of a single frequency component in a function.

4. How can I use the Fourier transform with Mathematica to analyze my data?

You can use the Fourier transform function in Mathematica to convert your data from the time or spatial domain to the frequency domain. This will allow you to identify and manipulate specific frequency components in your data, which can be useful for signal processing and data analysis.

5. Are there any limitations to using Mathematica for Fourier transform calculations?

While Mathematica is a powerful tool for computing the Fourier transform, it is limited by the size of the data that can be processed. For very large datasets, other tools or specialized hardware may be more efficient for computing the transform.

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