Singular Values and Eigenvalues

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    Eigenvalues
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Discussion Overview

The discussion revolves around the relationship between eigenvalues and singular values of a matrix, specifically under the condition that the matrix is symmetric positive definite. Participants are exploring the proof of this relationship and the implications of symmetry and positive definiteness.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant seeks to prove that a matrix A has eigenvalues equal to its singular values if and only if it is symmetric positive definite, expressing uncertainty about the symmetry aspect.
  • Another participant suggests that posting existing work would be beneficial for further discussion.
  • A participant notes that if a singular value is an eigenvalue of \( A^TA \), then A must be positive semi-definite, questioning the starting point regarding symmetry.
  • One participant references the Spectral Theorem, stating that every real symmetric matrix is diagonalizable and thus has real eigenvalues and corresponding eigenvectors.
  • Another participant challenges the problem statement, suggesting that the assumption of positive definiteness typically includes symmetry and points out that singular values can be zero, which complicates the claim about eigenvalues being positive.
  • This participant agrees that if A is symmetric positive definite, then its eigenvalues are positive and relates the eigenvalues of A to the singular values through the relationship with \( A^TA \).

Areas of Agreement / Disagreement

Participants express differing views on the necessity of symmetry in the context of positive definiteness and the implications of singular values being zero. There is no consensus on the correctness of the initial claim regarding eigenvalues and singular values.

Contextual Notes

Participants have not fully resolved the assumptions regarding the definitions of positive definiteness and symmetry, nor have they clarified the implications of singular values being zero on the eigenvalues of A.

linearishard
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Hi, one more question!

How do I prove that A has eigenvalues equal to its singular values iff it is symmetric positive definite? I think I have the positive definite down but I can't figure out the symmetric part. Thanks!
 
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It will help if you post the work you already have.
 
All I have is that if a singular value is the eigenvalue of ATA, then A must be positive semi definite or the signs will be different on at least one eigenvalue. I don't know where to start with symmetry or if my assumption is correct.
 
Are you familiar with the Spectral Theorem?
That is that every real symmetric matrix is diagonalizable?

So if the matrix is symmetric and has real numbers as its elements, it is diagonalizable, which means that it has a full set of real eigenvalues and corresponding eigenvectors that span the vector space.
 
Hello again, linearishard,

Usually, positive definite matrices are assumed to be symmetric (or Hermitian for complex matrices). Does your teacher's definition of positive definite exclude the symmetry assumption? In any case, the problem statement is not true. For since singular values of a matrix can be zero, having eigenvalues of $A$ equal to the singular values of $A$ does not necessarily result in every eigenvalue being positive (which is what you need to claim positive definiteness).

The forward conditional is true, however. if $A$ is symmetric positive definite, the eigenvalues of $A$ are positive. The eigenvalues of $A$ are square roots of the eigenvalues of $A^2 = A^TA$, so the singular values of $A$ are the eigenvalues of $A$.
 

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