On the orthogonality of Sturm-Liouville eigenvectors

In summary: That is the simplest possible Sturm-Liouville differential equation.In summary, the solutions to the Sturm-Liouville differential equation (SLDE) are considered to be orthogonal due to the assumption that they satisfy homogeneous boundary conditions. This is a prerequisite of Sturm-Liouville's theorem, as making superpositions of solutions with inhomogeneous boundary conditions would not fulfill the same boundary conditions. Additionally, for each possible value of the eigenvalue, there will be two independent solutions, but the boundary conditions will determine whether or not a non-trivial solution is possible. Finally, working through the simplest case of the SL operator on the interval [0,1] can help understand how the boundary conditions determine the allowed eigenvalues and number of
  • #1
mjordan2nd
177
1
From what I understand, solutions to the Sturm-Liouville differential equation (SLDE) are considered to be orthogonal because of the following statement:

[tex] \left( \lambda_m-\lambda_n \right) \int_a^b w(x) y_m(x)y_n(x) dx = 0 [/tex]

My first question involves the assumptions that go into this equation. One of the assumptions that go into this equation is that the solutions to the SLDE satisfy the Dirichlet, Neumann, or mixed homogeneous boundary conditions, correct? If the boundary conditions were inhomogeneous then the above equation would not necessarily be true, correct? Is it then correct to say that solutions to the SLDE are only orthogonal if they satisfy homogeneous boundary conditions?

My second question involves the case when [itex]\lambda_m=\lambda_n[/itex]. Since the SLDE is a second order ordinary differential equation there should be two linearly independent solutions for each eigenvalue. So even if [itex]\lambda_m=\lambda_n[/itex], that doesn't necessarily mean [itex]y_m=y_n[/itex]. In this case, it is not clear that these two solutions are orthogonal. I can buy that every eigensubspace of the SLDE is orthogonal to the others, however what about two vectors belonging to the same subspace?

Thanks
 
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  • #2
mjordan2nd said:
If the boundary conditions were inhomogeneous then the above equation would not necessarily be true, correct? Is it then correct to say that solutions to the SLDE are only orthogonal if they satisfy homogeneous boundary conditions?

Having homogeneous boundary conditions are a prerequisite of Sturm-Liouville's theorem. You cannot make superpositions of solutions with inhomogeneous boundary conditions and get new solutions fulfilling the same boundary conditions.

mjordan2nd said:
Since the SLDE is a second order ordinary differential equation there should be two linearly independent solutions for each eigenvalue.

No, this is not true. For each possible value of the eigenvalue, there will be two independent solutions. However, the boundary conditions will take care of this and determine whether or not a non-trivial solution is possible for that eigenvalue.
 
  • #3
Thank you for your response!

Orodruin said:
However, the boundary conditions will take care of this and determine whether or not a non-trivial solution is possible for that eigenvalue.

I am unclear about what you mean. Do you mean to say that the boundary conditions will reduce the number of nontrivial solutions per eigenvalue to one? Because this is the only way I can see that the equation I posted above proves that all eigenvectors are mutually orthogonal.
 
  • #4
Yes. They will also tell you what eigenvalues are allowed. My suggestion is to work it out in the absolutely easiest case of the SL operator ##-d^2/dx^2## on the interval ##[0,1]##.
 

1. What is the significance of the orthogonality of Sturm-Liouville eigenvectors?

The orthogonality of Sturm-Liouville eigenvectors is a fundamental property that allows for the unique representation of a function as a linear combination of these eigenvectors. This property is essential in solving boundary value problems in mathematics and physics.

2. How is the orthogonality of Sturm-Liouville eigenvectors proven?

The proof of the orthogonality of Sturm-Liouville eigenvectors is based on the Sturm-Liouville theory, which involves using the Sturm-Liouville operator to transform the differential equation into a simpler form. This simplification allows for the use of standard techniques, such as the Gram-Schmidt process, to show the orthogonality of the eigenvectors.

3. Can the orthogonality of Sturm-Liouville eigenvectors be applied to any type of function?

The orthogonality of Sturm-Liouville eigenvectors applies to a specific class of functions called Sturm-Liouville functions. These are functions that satisfy a certain type of differential equation, known as the Sturm-Liouville equation. Many common functions, such as polynomials and trigonometric functions, can be represented as Sturm-Liouville functions.

4. What are some practical applications of the orthogonality of Sturm-Liouville eigenvectors?

The orthogonality of Sturm-Liouville eigenvectors has numerous applications in mathematics and physics, including solving differential equations, Fourier analysis, and signal processing. It is also used in the study of quantum mechanics, where the eigenvectors of the Hamiltonian operator are Sturm-Liouville functions.

5. Are there any limitations or exceptions to the orthogonality of Sturm-Liouville eigenvectors?

The orthogonality of Sturm-Liouville eigenvectors holds true for most cases; however, there are some exceptions. For example, when dealing with complex-valued functions, the concept of orthogonality must be extended to include the complex inner product. There are also some special cases where the Sturm-Liouville theory does not apply, such as when the differential equation is singular at certain points.

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