Solving an Eigenvalue Problem for Large n Matrix

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Discussion Overview

The discussion revolves around an eigenvalue problem involving a real symmetric n*n matrix, specifically the equation Ax = λx. Participants seek guidance on finding all eigenvalues and eigenvectors, particularly in the context of large n matrices.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related

Main Points Raised

  • One participant expresses difficulty with the eigenvalue problem and seeks guidance and recommended texts.
  • Another participant notes that the eigenvalues of A are equal to those of A^T, citing the determinant property det(A - λI) = det(A^T - λI), and mentions that the diagonal/trace remains the same.
  • Some participants speculate that since A is symmetric (A^T = A), the eigenvectors might also be equal, although they hedge this claim due to lack of coverage in their texts.
  • A later reply corrects an earlier assumption about the eigenvectors of A and A^T being the same, acknowledging uncertainty about the reasons behind this difference.
  • Participants share resources, including a link to a book by Gilbert Strang, which may provide additional insights into the topic.

Areas of Agreement / Disagreement

Participants generally agree on the symmetry of matrix A and the relationship between the eigenvalues of A and A^T. However, there is disagreement regarding the equality of eigenvectors, with some participants unsure and correcting earlier claims.

Contextual Notes

Some participants express limitations in their understanding and knowledge, indicating that their textbooks do not provide comprehensive explanations on the topic.

Who May Find This Useful

Students studying linear algebra, particularly those focusing on eigenvalue problems and symmetric matrices, may find this discussion relevant.

Pyrokenesis
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I am having trouble with the following question. (Just hoping to get some guidance, recommended texts etc.):

"Consider an eigenvalue problem Ax = λx, where A is a real symmetric n*n matrix, the transpose of the matrix coincides with the matrix, (A)^T = A. Find all the eigenvalues and all the eigenvectors. Assume that n is a large number."

Any help would be fantastic!
 
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Originally posted by Pyrokenesis

"Consider an eigenvalue problem Ax = λx, where A is a real symmetric n*n matrix, the transpose of the matrix coincides with the matrix, (A)^T = A. Find all the eigenvalues and all the eigenvectors. Assume that n is a large number."

Don't know how much help I can be, but since I am studying the same material at the moment, I will help with what I can.

The eigenvalues of A are equal to the eigenvalues of A^T because det(A-λI)=det(A^T-λI). The diagonal/trace stays the same here.

(I am guessing on the next part, as our book does not cover this)
Normally, for non-symmetric matrices the eigenvectors are not the same. However, in your case, since A^T=A then (and I am guessing here) I would tend to believe that Laplace expansions would end up yielding equal eigenvectors as well.
 


Originally posted by samoth
Don't know how much help I can be, but since I am studying the same material at the moment, I will help with what I can.

The eigenvalues of A are equal to the eigenvalues of A^T because det(A-λI)=det(A^T-λI). The diagonal/trace stays the same here.

(I am guessing on the next part, as our book does not cover this)
Normally, for non-symmetric matrices the eigenvectors are not the same. However, in your case, since A^T=A then (and I am guessing here) I would tend to believe that Laplace expansions would end up yielding equal eigenvectors as well.

If A^T = A then A is symmetric, no? Does this help?
 
Yes, A is symmetric when A^T=A.

First of all, I was wrong about the eigenvectors of A and A^T being the same. They are not. However, I cannot help as to why, as our text offers only two sentences in this matter. Further, I do not believe I am at a level of knowledge upon which speculation would prove fruitful. Hmm.. let's see. I can give you some links that will hopefully be of some help.

We are using a book by Gilbert Strang from MIT. He has quite a bit of information on his/the books website, as well as fully recorded lectures. Here is his site.


http://web.mit.edu/18.06/www/

I am sorry I can be of little help with this, but I hope this can help you shed some light on the problem.
 
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Thanx bro,

I know, its a tough subject, cheers for the link. Now that all other coursework is out of the way I will crack on with this and post my findings when I find something.

Good luck with your course as well,

cheers,

Dexter
 
Originally posted by Pyrokenesis

I will crack on with this and post my findings when I find something.


Please do, as I am quite curious now.
Good luck as well with your course!
 

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