Eigenvalue problem with operators as matrix elements

In summary, the conversation discusses solving an eigenvalue problem involving a matrix with x-dependencies and a given function u(x). The question asks for the solution to the eigenfrequency and eigenvectors, specifically for the function omega of x. The use of del is clarified to indicate a partial derivative, and the typo in the equation is pointed out. The possibility of obtaining all three variables (omega, a, and b) through solving for omega is also mentioned.
  • #1
wil3
179
1
Hello, I have a feeling that the solution to this question is going to be incredibly obvious, so my apologies if this turns out to be really dumb. How do I solve the following eigenvalue problem:

[tex]

\begin{bmatrix}
\partial_x^2 + \mu + u(x) & u(x)^2 \\
\bar{u(x)}^2 & \partial_x^2 + \mu + u(x)
\end{bmatrix}
\begin{bmatrix}
a(x)\\
b(x)
\end{bmatrix}
=
\omega(x)
\begin{bmatrix}
a(x)\\
b(x)
\end{bmatrix}
[/tex]

where all x dependencies have been declared. I know the definition of the function [itex] u(x)[/itex], but I need to solve for the eigenfrequency and eigenvectors.
 
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  • #2
wil3 said:
Hello, I have a feeling that the solution to this question is going to be incredibly obvious, so my apologies if this turns out to be really dumb. How do I solve the following eigenvalue problem:

[tex]

\begin{bmatrix}
\partial_x^2 + \mu + u(x) & u(x)^2 \\
\bar{u(x)}^2 & \partial_x^2 + \mu + u(x)
\end{bmatrix}
\begin{bmatrix}
a(x)\\
b(x)
\end{bmatrix}
=
\omega(x)
\begin{bmatrix}
a(x)\\
b(x)
\end{bmatrix}
[/tex]

where all x dependencies have been declared. I know the definition of the function [itex] u(x)[/itex], but I need to solve for the eigenfrequency and eigenvectors.
I assume that you mean to find the function omega of x? You need to specify, because it's unclear what you want. Is your use of del indicating a partial derivative or a directional derivative. Be specific.
 
  • #3
Typo in question: [itex] \omega [/itex] should not depend on x. I want to solve for [itex] \omega [/itex], hence why I am calling this an eigenvalue problem. I'm not sure if getting w will also give a and b, like in a standard linear system.

[itex] \partial_x [/itex] indicates a partial derivative, which is standard notation in physics for this sort of problem. But the problem would be identical if you wanted to interpret that as a directional derivative (both because the problem is one dimensional and because the subscript x would suggest a derivative in the x direction).
 

1. What is an eigenvalue problem with operators as matrix elements?

An eigenvalue problem with operators as matrix elements is a mathematical problem that involves finding the eigenvalues and corresponding eigenvectors of a matrix where the elements are operators instead of numbers. In other words, it is a way of solving for the eigenvalues and eigenvectors of a matrix that represents a linear transformation.

2. How is an eigenvalue problem with operators as matrix elements different from a traditional eigenvalue problem?

The main difference between an eigenvalue problem with operators as matrix elements and a traditional eigenvalue problem is that the elements of the matrix are operators instead of numbers. This means that the eigenvectors are not just vectors, but also represent some kind of transformation.

3. What are some real-world applications of solving eigenvalue problems with operators as matrix elements?

Eigenvalue problems with operators as matrix elements have many applications in physics, engineering, and other fields where linear transformations are important. They are used to study quantum mechanics, electromagnetism, and other physical phenomena, as well as in data analysis and signal processing.

4. How are eigenvalue problems with operators as matrix elements solved?

Solving an eigenvalue problem with operators as matrix elements typically involves finding the eigenvalues and eigenvectors of the matrix using techniques such as diagonalization, similarity transformations, or numerical methods. The resulting eigenvalues and eigenvectors can then be used to understand the linear transformation represented by the matrix.

5. What is the significance of solving eigenvalue problems with operators as matrix elements?

Eigenvalue problems with operators as matrix elements are important because they provide a way to understand and analyze linear transformations in a wide range of applications. They also have connections to other areas of mathematics, such as differential equations and functional analysis, making them a powerful tool for solving complex problems.

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