Eigenvalues of the power of a matrix

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Homework Help Overview

The discussion revolves around the relationship between the eigenvalues of a symmetric matrix A and the eigenvalues of its square, A^2. The original poster seeks to understand the implications of the eigenvalues of A^2 on those of A, particularly focusing on proving the converse of a known result.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore the relationship between eigenvalues of A and A^2, questioning how to prove that if λ is an eigenvalue of A^2, then either √λ or -√λ is an eigenvalue of A. There is also discussion about the implications of A being symmetric on the nature of its eigenvalues.

Discussion Status

The discussion includes attempts to clarify the conditions under which eigenvalues of A^2 relate to those of A. Some participants suggest that both √λ and -√λ could be eigenvalues of A, while others emphasize that the symmetry of A implies real eigenvalues. The conversation reflects a productive exploration of these concepts without reaching a definitive conclusion.

Contextual Notes

Participants note that A is symmetric, which raises questions about the nature of its eigenvalues, particularly regarding their positivity and reality. There is also mention of the potential for complex eigenvalues in the context of the discussion.

IniquiTrance
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Homework Statement



If [itex]\lambda_i[/itex] are the eigenvalues of a matrix [itex]A^2[/itex], and [itex]A[/itex] is symmetric, then what can you say about the eigenvalues of A?

Homework Equations


The Attempt at a Solution



I know how to prove that if [itex]\sqrt(\lambda_i)[/itex] is an eigenvalue of A, then [itex]\lambda_i[/itex] is an eigenvalue of [itex]A^2[/itex].

I don't know how to prove the converse though.

Thanks!
 
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Let [itex]\lambda[/itex] be an eigenvalue of [itex]A^2[/itex]. What can you say about [itex]A^2-\lambda I[/itex]?

Now, use that

[tex]A^2-\lambda I=(A-\sqrt{\lambda}I)(A+\sqrt{\lambda} I)[/tex]
 
micromass said:
Let [itex]\lambda[/itex] be an eigenvalue of [itex]A^2[/itex]. What can you say about [itex]A^2-\lambda I[/itex]?

Now, use that

[tex]A^2-\lambda I=(A-\sqrt{\lambda}I)(A+\sqrt{\lambda} I)[/tex]

Then:

[tex]det(A-\sqrt{\lambda}I)*det(A+\sqrt{\lambda} I) = 0[/tex]

Not sure how to proceed...
 
If xy=0, then what can you say about x or y?
 
micromass said:
If xy=0, then what can you say about x or y?

Oh so all we can say is that either [itex]\sqrt{\lambda}[/itex] or [itex]-\sqrt{\lambda}[/itex] is an eigenvalue of A, but not both?
 
IniquiTrance said:
Oh so all we can say is that either [itex]\sqrt{\lambda}[/itex] or [itex]-\sqrt{\lambda}[/itex] is an eigenvalue of A, but not both?

Right.
 
Thank you.
 
One more question, how do we know that all the eigenvalues of [itex]A^2[/itex] are positive? Since A is symmetric, if [itex]\lambda < 0[/itex] were an eigenevalue of [itex]A^2[/itex] we'd run into a problem...
 
We can do the same with [itex]\sqrt{\lambda}[/itex] complex numbers, no?
 
  • #10
micromass said:
We can do the same with [itex]\sqrt{\lambda}[/itex] complex numbers, no?

But since A is symmetric, it must have real eigenvalues, no?
 
  • #11
IniquiTrance said:
But since A is symmetric, it must have real eigenvalues, no?

Yes, sure. So what we do is we argue the same argument where [itex]\lambda[/itex] might be negative and where [itex]\sqrt{\lambda}[/itex] might be complex. Then we can deduce that either [itex]\sqrt{\lambda}[/itex] or [itex]-\sqrt{\lambda}[/itex] are eigenvalues of A. Since A is symmetric, we have that [itex]\sqrt{\lambda}[/itex] must be real, so [itex]\lambda[/itex] was positive to begin with.
 
  • #12
micromass said:
Yes, sure. So what we do is we argue the same argument where [itex]\lambda[/itex] might be negative and where [itex]\sqrt{\lambda}[/itex] might be complex. Then we can deduce that either [itex]\sqrt{\lambda}[/itex] or [itex]-\sqrt{\lambda}[/itex] are eigenvalues of A. Since A is symmetric, we have that [itex]\sqrt{\lambda}[/itex] must be real, so [itex]\lambda[/itex] was positive to begin with.

Ah ok, thanks again!
 
  • #13
IniquiTrance said:
Ah ok, thanks again!

No, you can have both. The matrix
[tex]A = \pmatrix{2 & 0 \\0 & -2}[/tex] has
[tex]B = A^2 = \pmatrix{4 & 0 \\0 & 4},[/tex]
and so both [itex]\sqrt{4}[/itex] and [itex]-\sqrt{4}[/itex] are eigenvalues of [itex]A.[/itex]

RGV
 

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