Eigenvectors of symmetric matrices

In summary, the eigenvectors of symmetric matrices are orthogonal if all the eigenvalues are different. This is because if the eigenvalues are different, the space associated with each eigenvector is one dimensional, making the vectors orthogonal.
  • #1
Curl
758
0
Can anyone prove that the eigenvectors of symmetric matrices are orthogonal?
 
Mathematics news on Phys.org
  • #2
Let v be a eigenvector with eigenvalue [itex]\lambda_1[/itex] and u an eigenvector with eigenvalue \(\displaystyle \lambda_2\), both with length 1.

[itex]\lambda_1<v, u>= <\lambda_1v, u>[/itex]
(<u, v> is the innerproduct)
[itex]= < Av, u>= \overline{<v, Au>}[/itex]
(because A is symmetric)
("self adjoint" in general)
[itex]= \overline{<v, \lambda_2u>}= \lambda<v, u>[/itex]
so that
[itex]\lambda_1<v, u>= \lambda_2<v, u>[/itex]
[itex](\lambda_1- \lambda_2)<v, u>= 0[/itex]
Since [itex]\lambda_1[/itex] and [itex]\lambda_2[/itex] are not equal,
[itex]\lambda_1- \lambda_2[/itex] is not 0, <v, u> is.
 
Last edited by a moderator:
  • #3
The important criterion is not symmetry, but whether the eigenvalues are all different (i.e. all the roots of the characteristic equation are different). If an eigenvalue is repeated, then the space associated with the eigenvector is not one dimensional, so that the vectors are not necessarily orthogonal.
 

1. What is an eigenvector of a symmetric matrix?

An eigenvector of a symmetric matrix is a vector that, when multiplied by the matrix, results in a scalar multiple of itself. In other words, the direction of the eigenvector remains unchanged, but its magnitude is scaled by a factor known as the eigenvalue.

2. How are eigenvectors and eigenvalues related in a symmetric matrix?

Eigenvectors and eigenvalues are closely related in a symmetric matrix. The eigenvalues represent the scaling factor for each eigenvector, and the set of all eigenvectors and their corresponding eigenvalues form a basis for the matrix.

3. What are the applications of eigenvectors of symmetric matrices?

Eigenvectors of symmetric matrices have numerous applications in mathematics, physics, and engineering. They are used in solving systems of linear equations, diagonalizing matrices, and in various machine learning algorithms.

4. How can you find the eigenvectors of a symmetric matrix?

The most common method for finding the eigenvectors of a symmetric matrix is by using the eigenvalue decomposition (EVD) method. This involves finding the eigenvalues and corresponding eigenvectors through a series of calculations.

5. Can a symmetric matrix have complex eigenvectors?

Yes, a symmetric matrix can have complex eigenvectors. However, for a symmetric matrix, the eigenvalues are always real numbers. This means that if a complex eigenvector exists, its complex conjugate must also be an eigenvector.

Similar threads

  • General Math
Replies
4
Views
963
Replies
7
Views
1K
  • Introductory Physics Homework Help
Replies
1
Views
693
  • Linear and Abstract Algebra
Replies
14
Views
1K
  • Calculus and Beyond Homework Help
Replies
8
Views
696
Replies
3
Views
1K
  • General Math
Replies
5
Views
1K
  • Linear and Abstract Algebra
Replies
24
Views
622
Replies
1
Views
1K
Replies
2
Views
1K
Back
Top