Fourier Transform of Distribution

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SUMMARY

The discussion focuses on computing the Fourier Transform of the distribution \(x-a\). The Fourier Transform of a distribution is evaluated using the Fourier Transform of a test function. A suggested approach involves regularizing the distribution with the function \(\tilde{f}_{\epsilon}(k)=\int_{\mathbb{R}} \mathrm{d} x \exp(-\mathrm{i} k x) (x-a) \exp(-\epsilon x^2)\). The smoothed delta distribution \(\delta_{\epsilon}(k)=\frac{1}{2 \sqrt{\pi \epsilon}} \exp \left (-\frac{k^2}{4 \epsilon} \right )\) is introduced, highlighting its limit as \(\epsilon\) approaches zero.

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  • Understanding of Fourier Transforms in the context of distributions
  • Familiarity with integration techniques, particularly integration by parts
  • Knowledge of regularization methods in mathematical analysis
  • Basic concepts of delta distributions and their properties
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  • Explore the concept of delta distributions and their applications
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VVS
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Hi,

I hope somebody can help me with this one.

Homework Statement


Compute the Fourier Transform of the distribution x-a

Homework Equations


The Fourier Transform of a distribution is just the distribution evaluated with the Fourier Transform of a test function.

The Attempt at a Solution


See this pdf View attachment Übung 27.pdf
I used integration by parts but now I am stuck, because I have to evaluate the integral of the Foureir Transform of the test function.Thanks
VVS
 
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I'd rather regularize the distribution, e.g., defining
[tex]\tilde{f}_{\epsilon}(k)=\int_{\mathbb{R}} \mathrm{d} x \exp(-\mathrm{i} k x) (x-a) \exp(-\epsilon x^2).[/tex]
Then you only need to know that
[tex]\delta_{\epsilon}(k)=\frac{1}{2 \sqrt{\pi \epsilon}} \exp \left (-\frac{k^2}{4 \epsilon} \right )[/tex]
is a smoothed [itex]\delta[/itex] distribution, i.e.,
[tex]\lim_{\epsilon \rightarrow 0^+} \delta_{\epsilon}(k)=\delta(k).[/tex]
 

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