Fractional Fourier Transform in a QM Oscillator

In summary, the conversation discusses a modern version of a quantum mechanics simulation that creates movies of time evolutions of wave functions in a harmonical oscillator. The method used is a Fractional Fourier Transform, which is based on the eigenfunctions of the oscillator, the Gaussian Hermite functions. The time evolution of the oscillator is shown through a series of movies, demonstrating the relationship between the original function and its Fourier Transform. The conversation also mentions the use of the Schrodinger Equation and the observation of momentum and energy in the derivatives.
  • #1
Hans de Vries
Science Advisor
Gold Member
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Last year I made a more modern version of a QM simulation
I did a long long time ago, It makes movies of time evolutions
of arbitrary wave functions in a QM harmonical oscillator.
(You can see the movies via the links below)


http://www.chip-architect.com/physics/gaussian.avi

http://www.chip-architect.com/physics/narrow_gaussian.avi

http://www.chip-architect.com/physics/square.avi



Interesting is the used method with a Fractional Fourier Transform.
The eigenfunctions of the QM oscillator are Gaussian Hermite
functions which are also eigenfunctions of the Fourier Transform.

They stay unchanged under the Fourier Transform up to a constant
value. If we decompose an arbitrary function with the Gaussian
Hermite functions as the orthogonal base then we get the
Fourier Transform by simply multiplying the components with ein
(were n is for the nth Gaussian Hermite function) and adding
them back together again.

Now the time evolution for the Harmonical Oscillator is eint
so after time '1' we get the Fourier Transform. At time is '2' we get
the original function back again but mirrored. At t=3 we get the mirrored
transform and finally at t=4 we're back where we started.

In the mean time we have Fractional Fourier Transforms. There are 3
movies. One of a Gaussian Pulse equal to the 0th eigen function but
displaced from the center so it oscillates back and forward. Two is
a narrow Gaussian pulse that spreads into a sine wave and back.
Third movie is a square wave that oscillates back and forward
between it's Fourier Transform which is sin(x)/x.

You may want to set your player in a repeat mode for continuous playing.
It's all based on the good old Schrodinger Equation. So OK, non-relativistic
and zero rest mass but still interesting. You can see the momentum
and energy if you look at the derivatives.


Regards, Hans
 
Last edited:
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  • #2
Hans de Vries said:
Now the time evolution for the Harmonical Oscillator is eint
so after time '1' we get the Fourier Transform. At time is '2' we get
the original function back again but mirrored. At t=3 we get the mirrored
transform and finally at t=4 we're back where we started.

This is very similar to what happens in (classical) Fourier optics, when evolving from the "image" to the "focal plane", where you have the spatial Fourier transform of the image amplitude !

cheers,
patrick.
 
  • #3
.


Thank you for sharing your work on the Fractional Fourier Transform in a QM oscillator. It is fascinating to see the time evolution of arbitrary wave functions in a harmonic oscillator through your simulation. The use of Gaussian Hermite functions as eigenfunctions of both the QM oscillator and the Fourier Transform is a clever approach. It allows for a simple decomposition and reconstruction of an arbitrary function using the Fourier Transform, and the time evolution of the harmonic oscillator can be easily visualized by applying the Fractional Fourier Transform.

I am also intrigued by the three movies that you have shared. The first one, with a Gaussian pulse oscillating back and forth, demonstrates the periodicity of the Fourier Transform and the time evolution of the harmonic oscillator. The second one, with a narrow Gaussian pulse spreading into a sine wave and back, shows the effect of the Fourier Transform on different types of functions. And the third one, with a square wave oscillating between its Fourier Transform and back, highlights the connection between the QM oscillator and the Fourier Transform.

Your work is a great example of the power and versatility of the Fractional Fourier Transform in quantum mechanics. It is impressive to see how the Schrodinger Equation, although non-relativistic and with zero rest mass, can still provide such interesting insights into the behavior of quantum systems. Thank you for sharing your simulation and providing a deeper understanding of the Fractional Fourier Transform in a QM oscillator.
 

1. What is the Fractional Fourier Transform (FrFT) in a QM Oscillator?

The Fractional Fourier Transform (FrFT) is a mathematical operation that describes the transformation of a function from the time domain to the frequency domain. In a quantum mechanical (QM) oscillator, the FrFT is used to analyze the wavefunction of the oscillator and understand its behavior in both time and frequency domains.

2. How is the FrFT related to the Quantum Harmonic Oscillator?

The Quantum Harmonic Oscillator is a fundamental model in quantum mechanics that describes the behavior of a particle confined in a potential well. The FrFT is used in the analysis of the oscillator's wavefunction, which is a solution to the Schrödinger equation.

3. What is the significance of the FrFT in QM oscillator analysis?

The FrFT is significant in QM oscillator analysis because it allows for a more comprehensive understanding of the behavior of the oscillator in both time and frequency domains. It also provides a way to relate the classical and quantum mechanical descriptions of the oscillator.

4. How is the FrFT calculated in a QM oscillator?

The FrFT in a QM oscillator is calculated using the FrFT operator, which is a unitary operator that acts on the wavefunction of the oscillator. The FrFT operator is a function of the oscillator's Hamiltonian and the desired fractional Fourier order.

5. What are the applications of the FrFT in QM oscillator analysis?

The FrFT has various applications in QM oscillator analysis, such as studying the time-frequency properties of the oscillator's wavefunction, analyzing the uncertainty principle, and understanding the behavior of non-stationary states. It also has applications in signal processing, image processing, and optics.

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