Analytic form of eigenpairs for a special matrix

In summary, the conversation discusses a physically-motivated algorithm and a matrix with a specific form that the speaker is trying to analyze. They are able to compute the fundamental mode, but are seeking suggestions on how to generate higher order modes, specifically the eigenvalues. They mention using Laplace's formula to calculate the determinant for the eigenvalue polynomial and achieving a recursion quickly.
  • #1
robertsj
7
1
Hi all,

I have a physically-motivated algorithm for which I'm trying to flesh out some basic properties analytically. In one case, I end up with a matrix of the following form:

[tex]
\left [\begin{array}{ccccccccc}
0 & & & & & & & & \\
& 0 & R & T & & & & & \\
T & R & 0 & & & & & & \\
& & & 0 & R & T & & & \\
& & T & R & 0 & & & & \\
& & & & & \ddots & & & \\
& & & & & & 0 & R & T \\
& & & & & T & R & 0 & \\
& & & & & & & & 0 \\
\end{array} \right ]
[/tex]

I can compute the the fundamental mode analytically based on the physics of the problem, but I haven't been able to generate higher order modes. I'm most interested in the eigenvalues. Any suggestions? Has someone done this?
 
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FAQ: Analytic form of eigenpairs for a special matrix

What is an analytic form of eigenpairs for a special matrix?

The analytic form of eigenpairs for a special matrix is a way of representing the eigenvalues and eigenvectors of a special type of matrix. It involves expressing the eigenvalues and eigenvectors in terms of known mathematical functions, such as polynomials or trigonometric functions.

What makes a matrix "special" for the analytic form of eigenpairs?

A matrix is considered special for the analytic form of eigenpairs if it meets certain criteria, such as being diagonalizable, symmetric, or having repeated eigenvalues. These special properties allow for a simpler and more elegant representation of the eigenvalues and eigenvectors.

Why is the analytic form of eigenpairs important in mathematics and science?

The analytic form of eigenpairs is important because it provides a more efficient and structured way of representing eigenvalues and eigenvectors, which are crucial for understanding the behavior of linear systems in mathematics and science. This form also allows for easier calculation and manipulation of these values.

Can the analytic form of eigenpairs be used for any type of matrix?

No, the analytic form of eigenpairs is only applicable to certain types of matrices that have specific properties. For example, it cannot be used for matrices that are not diagonalizable or have complex eigenvalues.

How is the analytic form of eigenpairs calculated?

The analytic form of eigenpairs is calculated using various methods, such as diagonalization, Sylvester's law of inertia, or the characteristic polynomial. These methods involve finding the eigenvalues and eigenvectors of the matrix and then expressing them in terms of known mathematical functions.

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