Crude Fourier Series approximation for PDEs.

In summary, the conversation discusses the use of Fourier series to approximate partial differential equations in a crude manner. The process involves projecting the function to the Fourier space and obtaining coefficients. The question is raised about how to obtain an appropriate function for projection when it is not explicitly given, but described through a system of differential equations.
  • #1
maistral
240
17
Is there a way to "crudely" approximate PDEs with Fourier series?

By saying crudely, I meant this way:

Assuming I want a crude value for a differential equation using Taylor series;

y' = x + y, y(0) = 1

i'd take a = 0 (since initially x = 0),

y(a) = 1,
y'(x) = x + y; y'(a) = 0 + 1 = 1
y"(x) = 1 + y'; y"(a) = 1 + 1 = 2
y'"(x) = 0 + y"(x); y"'(a) = 0 + 2 = 2

then y ~ 1 + x + 2/2! x^2 + 2/3! x^3.

Or something similar to that. Does this crude method have an analog to Fourier-PDE solutions?
 
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  • #2
Hey maistral.

With a Fourier series, you need to project your function to the Fourier space to get the co-effecients.

So the question is, how do you get an appropriate function to project to the trig basis if it's not explicit (i.e. you don't have f(x) but a DE system that describes it)?
 

1. What is a crude Fourier Series approximation for PDEs?

A crude Fourier Series approximation for PDEs is a method used to approximate solutions to partial differential equations (PDEs) by representing the solution as a sum of trigonometric functions. It is based on the concept that any periodic function can be represented as a sum of sine and cosine functions with different frequencies and amplitudes.

2. How does a crude Fourier Series approximation for PDEs work?

In a crude Fourier Series approximation for PDEs, the PDE is first transformed into an equivalent periodic PDE. The solution to this periodic PDE is then represented as a sum of trigonometric functions, with the coefficients of the functions determined by solving a system of linear equations. The resulting approximation is a periodic function which can then be extended to a solution for the original PDE.

3. What are the advantages of using a crude Fourier Series approximation for PDEs?

One advantage of using a crude Fourier Series approximation for PDEs is that it can yield a simple and explicit expression for the solution, which can be useful for gaining insights into the behavior of the PDE. It also allows for the use of standard Fourier Series techniques, making it a widely accessible method. Additionally, it can be easily extended to higher dimensions and more complex PDEs.

4. What are the limitations of a crude Fourier Series approximation for PDEs?

A crude Fourier Series approximation for PDEs may not always provide an accurate solution, especially for non-periodic boundary conditions or for discontinuous solutions. It also requires the PDE to be transformed into an equivalent periodic PDE, which may not always be possible or may lead to a more complex problem. Additionally, the convergence of the series may be slow, requiring a large number of terms to achieve a desired accuracy.

5. How is a crude Fourier Series approximation for PDEs different from other numerical methods?

Unlike other numerical methods for solving PDEs, such as finite difference or finite element methods, a crude Fourier Series approximation does not require the discretization of the domain. It also provides an exact solution, rather than an approximate one. However, it is limited to problems with periodic boundary conditions and may not be suitable for all types of PDEs. It can also be more computationally expensive compared to other methods.

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