Solving Polynomial Eigenvalue Problem

In summary, solving polynomial eigenvalue problems involves finding the roots or eigenvalues of a polynomial equation. This can be done through various methods, such as using the characteristic polynomial or computing the determinant of a matrix. The eigenvalues represent the values at which the polynomial equation equals zero, and they are important in many applications, including physics, engineering, and computer graphics. The process of solving these problems can be complex, but there are algorithms and techniques that can be used to efficiently find the solutions.
  • #1
member 428835
Hi PF!

I'm trying to solve the polynomial eigenvalue problem ##M \lambda^2 + \Phi \lambda + K## such that
Code:
K = [5.92 -.9837;-0.3381 109.94];
I*[14.3 24.04;24.04 40.4];
M = [1 0;0 1];
[f lambda cond] = polyeig(M,Phi,K)
I verify the output of the first eigenvalue via
Code:
(M*lambda(1)^2 + Phi*lambda(1) + K)*f(:,1)
and the output has zero real component but non-zero imaginary: ##[44i,88i]##. Any ideas what's happening? Condition number is 5, which is evidently sufficiently low to output accurate answers?
 
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  • #2
I think you are giving polyeig the arguments in the wrong order.

Jason
 
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Likes member 428835
  • #3
jasonRF said:
I think you are giving polyeig the arguments in the wrong order.

Jason
Thanks!
:doh:
 

1. What is a polynomial eigenvalue problem?

A polynomial eigenvalue problem is a mathematical problem that involves finding the values of a variable, called eigenvalues, that satisfy a given polynomial equation. This problem is commonly encountered in many fields of science and engineering, such as physics, chemistry, and computer science.

2. How is a polynomial eigenvalue problem solved?

There are several methods for solving a polynomial eigenvalue problem, including direct methods, iterative methods, and perturbation methods. Direct methods involve solving a system of linear equations, while iterative methods involve repeatedly improving an initial estimate of the eigenvalues. Perturbation methods involve making small changes to the coefficients of the polynomial equation to obtain approximate solutions.

3. What are the applications of solving a polynomial eigenvalue problem?

The solutions of a polynomial eigenvalue problem are used to solve a variety of problems in science and engineering, such as finding the natural frequencies of a vibrating system, determining the stability of a dynamical system, and analyzing the behavior of quantum mechanical systems.

4. What are the challenges of solving a polynomial eigenvalue problem?

One of the main challenges of solving a polynomial eigenvalue problem is the potential for the problem to have multiple solutions or complex solutions. This can make it difficult to find an accurate solution and may require the use of advanced numerical methods. Additionally, the size of the problem can also be a challenge, as larger systems may require more computing power and time to solve.

5. Are there any real-world examples of polynomial eigenvalue problems?

Yes, polynomial eigenvalue problems have many real-world applications. For example, in structural engineering, the natural frequencies of a building or bridge can be found by solving a polynomial eigenvalue problem. In chemistry, the vibrational modes of molecules can be determined by solving a polynomial eigenvalue problem. In finance, polynomial eigenvalue problems can be used to analyze stock market trends and make predictions.

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