Eigenvectors of commuting matrices

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Discussion Overview

The discussion revolves around the properties of eigenvectors of commuting matrices, specifically addressing a claim made in Horn and Johnson's Matrix Analysis regarding the behavior of eigenvectors when one matrix commutes with another. The focus is on the implications of this claim when one of the matrices has distinct eigenvalues.

Discussion Character

  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the assumption that Ax cannot be the zero vector when A and B are commuting matrices, given that B has distinct eigenvalues.
  • Another participant provides a counterexample by suggesting that if A is the zero matrix, then Ax would indeed be zero, challenging the original claim.
  • A clarification is made regarding the terminology, distinguishing between eigenvalue 0 and eigenvector 0, emphasizing that the zero vector is part of the eigen space for any eigenvalue.
  • One participant expresses confusion about the claim that Ax is an eigenvector of B, specifically questioning the condition under which Ax could be zero.
  • A later reply agrees that if Ax is the zero vector, it cannot be considered an eigenvector, suggesting that the original text may have overlooked this possibility.

Areas of Agreement / Disagreement

Participants express disagreement regarding the assumption that Ax cannot be the zero vector, with some arguing that this is not necessarily true. The discussion remains unresolved as to whether the original claim adequately addresses this possibility.

Contextual Notes

The discussion highlights a potential oversight in the original argument regarding the conditions under which Ax can be an eigenvector, particularly in relation to the zero vector. There are also nuances in the definitions of eigenvalues and eigenvectors that are not fully explored.

acarchau
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I can't follow an argument in Horn and Johnson's Matrix analysis in a suggestion (actually an outline of a proof) that follows problem 8 following section 1.3 (pg 55 in my copy).

They argue that if A and B are complex square matrices of order n which commute, and if all eigenvalues of B are distinct, then given any eigenvector of B, say x, corresponding to an eigenvalue u, Ax is also an eigenvector of B. This apparently simply follows from the fact that B(Ax)=A(Bx) = u (Ax).

However they skip mentioning why Ax cannot be the zero vector. Is this obvious? I am clearly missing something.
 
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There's no reason why Ax can't be zero: if you pick A = 0, then clearly A and B commute, but Ax is zero.
 
Right. That is a simple counterexample.
 
Are you talking about eigenvalue 0 or eigenvector 0?

Typically, we say that an "eigenvalue" is a NON-ZERO vector such that Ax= \lambda x simply because A0= \lambda 0 for any linear transformation A and any number \lambda. Of course, the 0 vector is in the "eigen space" for any eigenvalue.
 
I meant an eigenvector. My problem was with the claim Ax was an eigenvector of B when x was an eigenvector of B, even though it was not obvious to me why Ax was not the zero vector.
 
Well if Ax is the 0 vector then it cannot be an eigenvector. I think they did forget to mention that possibility, but you managed to figure it out anyway.
 

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