Fourier transform of a differential equation

In summary, for the given partial differential equation with a spatial Fourier transform, the solution involves taking the transform of both sides and using the rule for transforming second order derivatives. This leads to a differential equation involving the transformed function \phi and a troublesome term involving the transformed product of p and x.
  • #1
AxiomOfChoice
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Homework Statement


I'm supposed to take the "spatial Fourier transform" of the partial differential equation

[tex]
p_t = \frac{a^2}{2\tau}p_{xx} + 2g(p + xp_x)
[/tex]

for [itex]p = p(x,t)[/itex].

Homework Equations


Well, I guess I eventually need something like

[tex]
\phi(k,t) = \mathbb F(p(x,t)) = \frac{1}{\sqrt{2\pi}} \int_{-\infty}^{\infty} p(x,t) e^{-ikx}\ dx.
[/tex]

The Attempt at a Solution


I've never done anything like this before, so I'm really not sure what to do. I think if I get a few hints or a gentle nudge in the right direction, I'll be good to go, though.

I'm guessing that I should take the spatial Fourier transform [itex]\mathbb F[/itex] of both sides. So the LHS would become

[tex]
\mathbb F(p_t) = \frac{1}{\sqrt{2 \pi}} \int \frac{\partial p}{\partial t}e^{-ikx}dx = \frac{1}{\sqrt{2 \pi}} \frac{\partial}{\partial t} \int p(x,t) e^{-ikx}dx = \phi_t.
[/tex]

Is this right?
 
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  • #2
And then I guess we can use the rule that

[tex]
\mathbb F(p_{xx}) = -k^2 \mathbb F(p)
[/tex]

to conclude that the transform of the first term on the RHS is just

[tex]
-\frac{a^2k^2}{2\tau} \phi.
[/tex]

So, at the end of the day, our differential equation becomes

[tex]
\phi_t = -\frac{a^2k^2}{2\tau} \phi + 2g(\phi + \mathbb F(xp_x)).
[/tex]

That last term on the right is giving me fits!
 

1. What is the Fourier transform of a differential equation?

The Fourier transform of a differential equation is a mathematical operation that converts a differential equation from the time domain to the frequency domain. It allows us to analyze the frequency components of a function or signal, making it easier to solve and understand the behavior of the system.

2. How is the Fourier transform of a differential equation different from the regular Fourier transform?

The regular Fourier transform operates on continuous signals, while the Fourier transform of a differential equation is specifically designed for transforming differential equations. It also involves complex numbers and is typically more complex to calculate.

3. What is the importance of using Fourier transform in solving differential equations?

Fourier transform is important in solving differential equations because it allows us to find the solution in the frequency domain, which can then be transformed back to the time domain to get the solution of the original differential equation. This approach is often more efficient and accurate than traditional methods of solving differential equations.

4. Can Fourier transform be applied to all types of differential equations?

Yes, Fourier transform can be applied to all types of differential equations, including ordinary differential equations and partial differential equations. However, the complexity and difficulty of the transform may vary depending on the type of differential equation being solved.

5. Are there any limitations or assumptions when using Fourier transform to solve differential equations?

One limitation of using Fourier transform is that it can only be applied to linear differential equations. Non-linear differential equations require other methods of solving. Additionally, the Fourier transform assumes that the differential equation is time-invariant, meaning that the system's behavior does not change over time. This may not always be the case in real-world systems.

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