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

In summary, if AA^T = A^TA, then it can be proven that A and A^T have the same eigenvectors. The next steps would involve showing that if x is an eigenvector of A, then x, not A^Tx, is also an eigenvector of A^T. However, it cannot be assumed that 0 is not an eigenvalue of A.
  • #1
arpon
235
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?
 
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  • #2
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?
 
  • #3
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:
  • #4
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:
  • #5
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.
 
  • #6
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 [itex]A[/itex].
 

What is an eigenvector?

An eigenvector is a vector that does not change direction when multiplied by a particular transformation. It only changes in magnitude by a scalar value, known as the eigenvalue.

Why are eigenvectors important?

Eigenvectors are important in many fields of science, such as physics, engineering, and data analysis. They are used to understand the behavior of complex systems and to identify patterns and trends in data.

How are eigenvectors calculated?

Eigenvectors can be calculated through a process called eigenvalue decomposition, which involves finding the eigenvalues and corresponding eigenvectors of a matrix. This can be done using various mathematical techniques, such as Gaussian elimination or the power method.

What is the significance of the eigenvalue in an eigenvector?

The eigenvalue of an eigenvector represents the amount by which the vector is scaled when multiplied by a specific transformation. It can also provide information about the stability and behavior of a system.

What are some real-world applications of eigenvectors?

Eigenvectors have many practical applications, such as in image and signal processing, machine learning, and quantum mechanics. They are also commonly used in solving systems of differential equations and in understanding the properties of physical systems.

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