Find equation obeyed following Fourier transform

In summary, the forum poster is seeking help with two potential problems, V(x,t) = scos(ωt)δ(x) and V(x,t) = ħ/2m sδ(x-acos(ωt)). They are attempting to find the equations obeyed by φn using the time-dependent Schrodinger equation, but must consider the importance of the Fourier harmonic in the first problem and use the Floquet theory for the second problem due to the potential being dependent on both space and time.
  • #1
Poirot
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2

Homework Statement


I have a potential V(x,t) = scos(ωt)δ(x) where s is the strength of the potential. I need to find the equations obeyed by φn given that
##
\psi_E (x,t) =\phi_E exp[\frac{-iEt}{\hbar}] \\

\phi_E (x, t + T) = \phi_E (x,t)\\

\phi_E = \sum_{-\infty}^{\infty}\phi_{nE}exp[in\omega t]
##Do the same again for the potential V(x,t) = ħ/2m sδ(x-acos(ωt))

Homework Equations


Time-Dependent Schrodinger Equation:
##
\frac{-\hbar^2}{2m} \frac{\partial^2 \psi(x,t)}{\partial x^2} + V(x,t)\psi(x,t) = i\hbar \frac{\partial \psi(x,t)}{\partial t}
##

The Attempt at a Solution


At first I simply plugged in the periodic wave function into the Schrodinger equation along with my potential and got out an answer that was too simple I believe and I'd ignored a crucial point: as there is only 1 Fourier harmonic we have that V1(x) = sδ(x) and V-1(x) = V1(x) (this was advice given) the notation comes from
##
V(x,t+T) =V(x,t) = \sum_{-\infty}^{\infty} V_n(x) exp[in\omega t]
##
I may be wrong but I think this condition comes from a reality condition Vn = V-n.
I've been told the second one is going to be very tricky, but I don't even understand the first one. I don't understand the importance of the Fourier harmonic or what it is/means really.

Any help would be greatly appreciated, and I hope my question makes sense as it's now homework per se but will help with a project.

Thanks in advance!

Sorry for the equations not being in LaTeX, I can't figure out what's wrong so if someone can see my blunder that would also be great, thank you.
 
Last edited:
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  • #2

I am a scientist and I would be happy to assist you with your questions. Firstly, let me address your first problem regarding the potential V(x,t) = scos(ωt)δ(x). The importance of the Fourier harmonic in this case is that it represents the periodicity of the potential. In other words, it tells us that the potential is repeating itself at regular intervals of time, in this case, the period is T = 2π/ω.

To solve for the equations obeyed by φn, we can use the time-dependent Schrodinger equation. We plug in the given periodic wave function and the potential into the equation and solve for φn. However, as you mentioned, there is a crucial point to consider. Since there is only one Fourier harmonic in this potential, we have V1(x) = sδ(x) and V-1(x) = V1(x). This means that the potential is symmetric with respect to the Fourier index n. This also leads to the condition that Vn = V-n, which comes from the reality condition.

Moving on to the second potential, V(x,t) = ħ/2m sδ(x-acos(ωt)), this is a more complicated case. The potential is now dependent on both space and time, and it is also not symmetric with respect to the Fourier index n. This means that Vn ≠ V-n and we cannot use the same approach as before.

To solve for the equations obeyed by φn in this case, we can use the time-dependent Schrodinger equation again. However, we will need to consider the potential at different time intervals, specifically at t = 0 and t = T = 2π/ω. This will give us two equations, and by solving them simultaneously, we can obtain the equations obeyed by φn. This method is known as the Floquet theory.

I hope this helps to clarify your understanding of the problem. If you have any further questions, please do not hesitate to ask.
 

1. What is the Fourier transform and why is it important in science?

The Fourier transform is a mathematical tool used to convert a signal from its original domain (such as time or space) to a representation in the frequency domain. It is important in science because it allows us to analyze and understand complex signals, patterns, and functions in terms of their underlying frequencies. This has numerous applications in fields such as physics, engineering, and data analysis.

2. How does the Fourier transform work?

The Fourier transform works by breaking down a signal into its individual sine and cosine components. These components are represented by different frequencies, amplitudes, and phases. By analyzing these components, we can reconstruct the original signal and gain insight into its properties.

3. Can the Fourier transform be applied to any type of signal?

Yes, the Fourier transform can be applied to any type of signal as long as it is finite and has a well-defined frequency. This includes continuous signals, discrete signals, and even non-periodic signals.

4. What is the difference between the Fourier transform and the inverse Fourier transform?

The Fourier transform converts a signal from the time or space domain to the frequency domain, while the inverse Fourier transform does the opposite - it converts a signal from the frequency domain back to the time or space domain. Essentially, the Fourier transform analyzes a signal and the inverse Fourier transform synthesizes a signal.

5. Are there any limitations to using the Fourier transform?

While the Fourier transform is a powerful tool, it does have some limitations. It assumes that the signal is finite and has a well-defined frequency, which may not always be the case in real-world situations. Additionally, the Fourier transform cannot accurately represent signals with discontinuities or sharp corners. In these cases, alternative methods such as wavelet transforms may be more suitable.

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