Linear Algebra: Eigenvectors and Orthonormal Bases

Click For Summary

Homework Help Overview

The discussion revolves around the properties of eigenvectors of a symmetric matrix in linear algebra, specifically focusing on their linear independence and the formation of an orthonormal basis. The original poster poses questions regarding the spanning of vector spaces by eigenvectors and the relationship between linear independence and orthogonality.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the conditions under which a set of vectors spans a vector space and whether the eigenvectors of a symmetric matrix meet these conditions. They also examine the relationship between linear independence and orthogonality through examples.

Discussion Status

The discussion includes attempts to clarify the implications of linear independence for spanning a space, with some participants recognizing that a basis spans the space. There is also acknowledgment of a counter-example regarding linear independence and orthogonality, indicating a productive exploration of the concepts.

Contextual Notes

Participants are considering the properties of symmetric matrices and their eigenvectors, as well as the definitions of linear independence and orthogonality in the context of vector spaces.

Niles
Messages
1,834
Reaction score
0

Homework Statement


Consider a symmetric (and hence diagonalizable) n x n matrix A. The eigenvectors of A are all linearly independent, and hence they span the eigenspace Rn.

Since the matrix A is symmetric, there exists an orthonormal basis consisting of eigenvectors.

My questions are:

1) Will this orthonormal basis of eigenvectors also span the same space Rn?

2) If two vectors are linearly independent, will they also be orthogornal?
 
Physics news on Phys.org
For 1): when does a set of vectors span the vector space? Do the eigenvectors satisfy these conditions? [Actually, you already gave the answer yourself... do you see where? ]

For 2): Consider (1, 0) and (1, 1) in R2.
 
1) They ar elinearly dependent, so yes - I guess I answered my own question there!

2) Great, a counter-example, so no. Thanks!
 
1) Yep, it follows from the fact that "the eigenvectors are linearly independent" and that there are n of them. That is, they form a basis, as you said in the question. And of course a basis always spans the space (even a non-orthogonal and/or not normalized one).
 

Similar threads

Replies
15
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 15 ·
Replies
15
Views
3K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
5
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K