ODE/PDE- eighenvalues+ eigenfunctions

In summary, the conversation discusses a Sturm-Liouville eigenvalue problem involving a separable ODE function. The speaker is unsure about the case where λ=0 and asks for clarification. The expert responds by explaining the solution process and pointing out an error in the speaker's solution. They also clarify that there is no non-trivial solution when λ=0.
  • #1
Roni1985
201
0

Homework Statement


it's already separable, so it's an ODE function.
X''+[tex]\lambda[/tex]*X=0 0<x<1
X(0)=-2X(1)+X'(1)=0


Homework Equations





The Attempt at a Solution



this is a Sturm-Liouville eigenvalue problem.
Now, I know how to solve it and everything, but I'm not sure with one thing.

when I check the case where [tex]\lambda[/tex]=0,
I get C2(-2x+1)=0
so C2 can be anything, correct ?
now what's my eigenfunction ?
X(x)=x is the eigenfunction ?

do I use the x=1/2 somewhere ?

Thanks.
 
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  • #2
Roni1985 said:

Homework Statement


it's already separable, so it's an ODE function.
X''+[tex]\lambda[/tex]*X=0 0<x<1
X(0)=-2X(1)+X'(1)=0


Homework Equations





The Attempt at a Solution



this is a Sturm-Liouville eigenvalue problem.
Now, I know how to solve it and everything, but I'm not sure with one thing.

when I check the case where [tex]\lambda[/tex]=0,
I get C2(-2x+1)=0
How did you get that?
so C2 can be anything, correct ?
now what's my eigenfunction ?
X(x)=x is the eigenfunction ?

do I use the x=1/2 somewhere ?

Thanks.
 
  • #3
vela said:
How did you get that?

well, when lamda is zero X''=0
so, X(x)=C1+C2*x
X(0)=C1=0
and by using the second BC, -2*C2*x+C2=0
so to get a nontrivial solution x=1/2, meaning C2 can be any number.

did I do something wrong ?
 
  • #4
The second BC is at x=1, so you get C2=0. So there's no non-trivial solution that satisfies the boundary conditions when λ=0.
 
  • #5
vela said:
The second BC is at x=1, so you get C2=0. So there's no non-trivial solution that satisfies the boundary conditions when λ=0.

shoot, you are right :\

forgot to plug in the 1.

Thanks for your help.
 

1. What are the differences between eigenvalues and eigenfunctions?

Eigenvalues and eigenfunctions are both important concepts in solving ODE/PDE problems. Eigenvalues are the constants that satisfy the corresponding homogeneous equation, while eigenfunctions are the corresponding solutions to the homogeneous equation. Eigenvalues represent the scaling factor for the eigenfunction, which is a mathematical function that remains unchanged when multiplied by the eigenvalue.

2. How do I find the eigenvalues and eigenfunctions for a given ODE/PDE?

To find the eigenvalues and eigenfunctions for a given ODE/PDE, you need to first set up the corresponding homogeneous equation. Then, you can use methods such as substitution, separation of variables, or the characteristic equation to solve for the eigenvalues. Once you have the eigenvalues, you can plug them back into the homogeneous equation to solve for the corresponding eigenfunctions.

3. Can I have multiple eigenvalues and eigenfunctions for a single ODE/PDE?

Yes, it is possible to have multiple eigenvalues and eigenfunctions for a single ODE/PDE. In fact, most ODE/PDE problems have an infinite number of eigenvalues and corresponding eigenfunctions. This is because the eigenvalues and eigenfunctions can be scaled by any constant and still satisfy the homogeneous equation.

4. How are eigenvalues and eigenfunctions used in practical applications?

Eigenvalues and eigenfunctions have a wide range of applications in various fields of science and engineering. For example, they are used in quantum mechanics to describe the energy levels of particles, in signal processing to decompose signals into basic components, and in structural engineering to determine the natural frequencies of structures. They are also used in image and data compression, and in solving boundary value problems in fluid dynamics, among others.

5. Can I use eigenvalues and eigenfunctions to solve non-linear ODE/PDE problems?

No, eigenvalues and eigenfunctions can only be used to solve linear ODE/PDE problems. Non-linear problems involve terms that are not proportional to the dependent variable, making it impossible to find eigenvalues and eigenfunctions. In these cases, other methods such as numerical approximation or perturbation theory may be used.

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