What is the role of Fourier transform in solving PDEs?

In summary, the problem asks to solve for u(x,t) using the Fourier transform, resulting in the equation u(x,t) = \int_{-inf}^{inf} [ \frac{1}{2*pi} \int _{-inf}^{inf} f(x) e^{iwx} dx ] e^{(-w^{2}k-G)t} e^{-iwx} dw. Part (b) asks if this solution suggests a simplifying transformation, and the answer is yes - by substituting a = t(K-G) and evaluating the resultant Gaussian, the integral can be taken offline.
  • #1
paxprobellum
25
0

Homework Statement


(a) Solve [tex]\frac{\partial u}{\partial t}=k\frac{\partial ^{2} u}{\partial x^{2}} - Gu[/tex]

where -inf < x < inf
and u(x,0) = f(x)

(b) Does your solution suggest a simplifying transformation?

Homework Equations



I used the Fourier transform as:
F[f(x)] = F(w) = [tex] \frac{1}{2*pi} \int_{-inf}^{inf} f(x) e^{iwx} dx [/tex]

The Attempt at a Solution



I solved part a using Fourier transform. Although I'm not 100% certain, I think my answer is pretty plausible. I'm happy to elaborate on how I solved this, but I didn't want to type it all out for naught, because that's not really my question. Anyway, I got:

[tex] u(x,t) = \int_{-inf}^{inf} [ \frac{1}{2*pi} \int _{-inf}^{inf} f(x) e^{iwx} dx ] e^{(-w^{2}k-G)t} e^{-iwx} dw [/tex]

I'm not sure how to answer part b. Any ideas?
 
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  • #2
paxprobellum said:
(b) Does your solution suggest a simplifying transformation?

I'm not sure how to answer part b. Any ideas?

So I think maybe the problem statement is asking me to change the order of integration and take the middle integral "offline" by substituting for x (as x - xbar, for example). Or maybe this is expected in part A...
 
  • #3
paxprobellum said:
So I think maybe the problem statement is asking me to change the order of integration and take the middle integral "offline" by substituting for x (as x - xbar, for example). Or maybe this is expected in part A...

following my own logic, I find:

[tex]
u(x,t) = \frac{1}{2 \pi} \int_{-inf}^{inf} f(X) ( \int_{-inf}^{inf} e^{-iw(x-X)} e^{-(w^{2}k-G)t}dw)dX
[/tex]

and I need to find a function g(x-X) such that the Fourier transform is:

[tex] G(w) = e^{(-w^{2}k-G)t} [/tex]


So the substitution must simplify G(w) such that i can get an analytical form of the inverse Fourier transform... Any idears?
 
  • #4
So it turns out that the substitution is a = t(K-G). Thus you can take the integral offline by evaluating the resultant Gaussian.

Thanks! At least PF let's me talk to myself better :P
 
  • #5
paxprobellum said:
So it turns out that the substitution is a = t(K-G). Thus you can take the integral offline by evaluating the resultant Gaussian.

Thanks! At least PF let's me talk to myself better :P

Well, I don't know if this qualifies as a "transformation" -- again, welcoming comments.
 

1. What is a PDE (partial differential equation)?

A PDE is a mathematical equation that involves multiple independent variables and their partial derivatives. It is used to describe physical phenomena such as heat transfer, fluid dynamics, and electromagnetism.

2. What is the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It is commonly used in signal processing and differential equations to solve problems involving periodic or oscillatory behavior.

3. How does the Fourier transform help solve PDEs?

The Fourier transform allows us to convert a PDE into an ordinary differential equation (ODE), which is often easier to solve. By transforming the PDE into the frequency domain, we can use known solutions of ODEs to find solutions for the original PDE.

4. Are there any limitations to using the Fourier transform for solving PDEs?

Yes, the Fourier transform is most effective for linear PDEs and may not work for all types of boundary conditions. Also, the Fourier transform assumes that the function being transformed is integrable, which may not always be the case.

5. Can the Fourier transform be used for time-dependent PDEs?

Yes, the Fourier transform can be extended to solve time-dependent PDEs by using the Laplace transform. This allows us to transform the time variable into a complex frequency variable, making it easier to solve the PDE in the frequency domain.

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