Matrix/vector : (A-B)s = 0 does not imply A=B

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Discussion Overview

The discussion revolves around the mathematical implications of the equation (A-B)s = 0, specifically exploring the conditions under which this does not imply A = B. The focus includes linear operators, matrix properties, and the concept of null spaces in linear algebra.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant presents an equation involving a column vector and a diagonal matrix, questioning the validity of an equality derived from it.
  • Another participant discusses the scenario where a non-zero linear operator A can lead to Ax=0 without x being zero, highlighting the existence of a null space.
  • A third participant notes that the equality involving the scalar α and the matrix L leads to a situation where the derived expression does not imply the original equality holds.
  • Further clarification is provided that if the operator s^T L s L - L s s^T L were invertible, it would lead to the conclusion that s must be zero, but the possibility of s being non-zero indicates the operator is non-invertible.

Areas of Agreement / Disagreement

Participants express varying perspectives on the implications of the mathematical properties discussed, with no consensus reached on the interpretations of the equations or their implications.

Contextual Notes

The discussion highlights the limitations of certain mathematical assumptions, particularly regarding invertibility and the implications of null spaces, without resolving these issues.

Who May Find This Useful

Readers interested in linear algebra, matrix theory, and the properties of linear operators may find this discussion relevant.

elgen
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Let s be a column vector and L be a diagonal matrix. Then

[tex]s^T L s L s = L s s^T L s[/tex]

by noticing that [tex]s^TLs[/tex] is a scalar.

However,

[tex]s^T L s L \neq L s s^T L[/tex].

Is there some mathematical explanation behind this? Thank you.

elgen
 
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Are you looking for a reason why Ax=0 doesn't imply x=0, when A is a non-zero linear operator and x a vector (or equivalently, when A is a m×n matrix and x an n×1 matrix)? One way of looking at it is that there are non-zero linear operators that aren't invertible. This is different from how real numbers behave, since every non-zero real number r has the multiplicative inverse 1/r. If A is invertible, we clearly have x=0. But we can easily find examples of non-invertible, non-zero A such that Ax=0 with x≠0.

[tex]\begin{pmatrix}0 & 0 & 0\\ 0 & 1 & 0\\ 0 & 0 & 1\end{pmatrix}\begin{pmatrix}1 \\ 0\\ 0\end{pmatrix}=0[/tex]

Here A projects onto the 23 plane, and x is in the 1 direction.
 
Thank you for replying my message, Fredrik. Even though it is not the expected answer, it does explain well the presence of the NULL space of the matrix A.

What has surprised me is that, let [tex]\alpha=s^TL s[/tex], the equality is really
[tex]\alpha Ls = L s \alpha[/tex].

Since
[tex]s^T L s Ls = L s s^T L s[/tex]
we have
[tex](s^T Ls L - L s s^T L)s = 0[/tex]

This does not imply that [tex]s^T L s L = L s s^T L[/tex].
 
Right. I answered the question in the title (or rather, one that's easily seen to be completely equivalent to it), and the answer should explain the issue you brought up in the post (the one you're repeating now). If sTLsL-LssTL had been invertible, we would obviously have had s=0. The fact s≠0 is a possibility means that we have found an example (sTLsL-LssTL) of a non-zero, non-invertible linear operator.
 
Thank you for the discussion.
 

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