Do Eigenvalues of A and A^T have the same Eigenvectors?

  • Thread starter Thread starter arpon
  • Start date Start date
  • Tags Tags
    Eigenvector
arpon
Messages
234
Reaction score
16

Homework Statement


If ##AA^T=A^TA##, then prove that ##A## and ##A^T## have the same eigenvectors.

Homework Equations

The Attempt at a Solution


##Ax=\lambda x##
##A^TAx=\lambda A^Tx##
##AA^Tx=\lambda A^Tx##
##A(A^Tx)=\lambda (A^Tx)##
So, ##A^Tx## is also an eigenvector of ##A##.
What should be the next steps?
 
Physics news on Phys.org
arpon said:

Homework Statement


If ##AA^T=A^TA##, then prove that ##A## and ##A^T## have the same eigenvectors.

Homework Equations

The Attempt at a Solution


##Ax=\lambda x##
##A^TAx=\lambda A^Tx##
##AA^Tx=\lambda A^Tx##
##A(A^Tx)=\lambda (A^Tx)##
So, ##A^Tx## is also an eigenvector of ##A##.
What you have to show is that if x is an eigenvector of A, then x, not ATx, is also an eigenvector of AT.
arpon said:
What should be the next steps?
 
A fact that might be pertinent here is that for square matrices A and B, if AB = BA, then each one is the inverse of the other.

Edit: As pointed out by Ray, this is not true. Mea culpa.
 
Last edited:
Mark44 said:
A fact that might be pertinent here is that for square matrices A and B, if AB = BA, then each one is the inverse of the other.

If
$$A = \pmatrix{0&1\\1&0} \; \text{and} \; B = \pmatrix{1&0\\0&1}$$
then ##AB = BA = A##, but ##B \neq A^{-1}## and ##A \neq B^{-1}##.

However, if you mean that ##AB = (BA)^{-1}##, etc., then that seems OK, in this example at least.
 
Last edited:
Ray Vickson said:
If
$$A = \pmatrix{0&1\\1&0} \; \text{and} \; B = \pmatrix{1&0\\0&1}$$
then ##AB = BA = A##, but ##B \neq A^{-1}## and ##A \neq B^{-1}##.

However, if you mean that ##AB = (BA)^{-1}##, etc., then that seems OK, in this example at least.
No, I meant the first, so my "fact" was incorrect. I guess I had that confused with if AB = I, then A and B are inverses.
 
Ray Vickson said:
However, if you mean that ##AB = (BA)^{-1}##, etc., then that seems OK, in this example at least.

I don't think we are entitled to assume that 0 is not an eigenvalue of A.
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
Back
Top