Show the Fourier transformation of a Gaussian is a Gaussian.

In summary, the conversation is about using the Fourier transformation to find the Gaussian wavepacket of a given width and center frequency. The attempt at solution involves completing the square and integrating the resulting expression, but the poster is unsure if their solution is correct as it does not match the given formula. They provide their work but do not receive any feedback on where they may have gone wrong.
  • #1
thomas19981

Homework Statement


Show, by completing the square in the exponent, that the Fourier transform of a Gaussian wavepacket ##a(t)## of width ##\tau## and centre (angular) frequency ##\omega_0##:
##a(t)=a_0e^{-i\omega_0t}e^{-(t/\tau)^2}##
is a Gaussian of width ##2/\tau##, centred on ##\omega_0##, given by:
##a(\omega)=\frac{a_0\tau}{2\sqrt \pi}e^{-(\frac{\omega-\omega_0}{2/\tau})^2}##

Homework Equations


I just used the Fourier transformation:
##\frac{1}{ \sqrt{2\pi}}\int \psi(t)e^{-i\omega t} \, dt## the limits of integration is all ##\Bbb{R}##

The Attempt at a Solution


Well I subbed in ##a(t)## for ##\psi(t)## and then carried the integral through and I got:
##\frac{a_0\tau}{\sqrt2}e^{-(\frac{\omega+\omega_0}{2/\tau})^2}##. As you can see the exponent should be ##\omega- \omega_0## and there is a missing factor of ##\frac{1}{\sqrt{2\pi}}##. I have looked through my work endlessly and can't find any mistakes so is that the right formula that I am using above or is there an alternative? If that is the right formula above then does that mean the solution is wrong?

So I completed the square of a(t) which gave me:
##a_0e^{-(t/\tau+(1/2)\tau i\omega_0)^2}e^{-\tau^2 \omega_0^2 /4}##
I then plugged this into the integral which gave me:
##\frac{1}{ \sqrt{2\pi}}\int a_0e^{-(t/\tau+(1/2)\tau i\omega_0)^2}e^{-\tau^2 \omega_0^2 /4}e^{-i\omega t} \, dt##

I completed the square of this which gave me:
##\frac{1}{ \sqrt{2\pi}}e^{-\tau^2 \omega_0^2 /4}\int a_0e^{-(t/\tau+(\omega+\omega_0)i\tau/2)^2}e^{-\omega^2 \tau^2 /4}e^{-\omega_0 \omega \tau^2 /2} \, dt##.
Then I simplified this down to:
##\frac{a_0\tau}{\sqrt2}e^{-\frac{\tau^2}{4}(\omega+\omega_0)^2}##.
I then simplified this down further to give me my incorrect answer at the top of the page.
 
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  • #2
How are we going to find out where you have gone wrong in your work if you do not post your work?
 

Related to Show the Fourier transformation of a Gaussian is a Gaussian.

1. What is a Fourier transformation?

A Fourier transformation is a mathematical operation that converts a function in the time or spatial domain into a function in the frequency domain. It is used to analyze the frequency components of a signal or function.

2. What is a Gaussian function?

A Gaussian function is a bell-shaped curve that represents a normal distribution of data. It is characterized by a peak at the mean value, with symmetrical tails on either side.

3. How is a Gaussian transformed into a Gaussian using Fourier transformation?

The Gaussian function in the time domain is multiplied by a complex exponential function in the frequency domain, resulting in a Gaussian function in the frequency domain. This is known as the Fourier transformation of a Gaussian.

4. Why is it important for a Gaussian to remain a Gaussian after Fourier transformation?

The Gaussian function is a common and important distribution in many fields of science, and it is often used to model real-world data. Its properties, such as symmetry and the Central Limit Theorem, make it easier to analyze and interpret. Therefore, it is important for a Gaussian to remain a Gaussian after Fourier transformation to preserve these properties.

5. What are the applications of the Fourier transformation of a Gaussian?

The Fourier transformation of a Gaussian has many applications in signal processing, image processing, and data analysis. It is used to filter and remove noise from signals, as well as to extract frequency components and analyze data. It is also used in fields such as optics, acoustics, and quantum mechanics to study the properties of waves and fields.

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