Proving 1. $\leftrightarrow$ 2.: A Matrix Invertibility Challenge

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Discussion Overview

The discussion revolves around proving the equivalence between two statements regarding matrix invertibility: that a matrix A is left invertible and that the equation Ax=0 has only the trivial solution x=0. The scope includes theoretical aspects of linear algebra, particularly focusing on properties of matrices, ranks, and determinants.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants assert that if A is left invertible, then Ax=0 implies x=0, using the definition of left invertibility.
  • Others propose that if the only solution to Ax=0 is the trivial solution, then the reduced row echelon form (RREF) of A must be the identity matrix, suggesting A is invertible.
  • Some participants mention that if Ax=0 has only the trivial solution, then the determinant of A is non-zero, indicating invertibility.
  • There is a contention regarding the applicability of these statements to non-square matrices, with some arguing that only square matrices can be inverted.
  • One participant references the rank-nullity theorem to support claims about the relationship between the rank of A and the kernel of A.
  • Another participant challenges the assertion that the kernel of A can be empty, noting that the zero vector is always in the kernel.
  • Some participants express uncertainty about how to apply certain theorems to non-square matrices and the implications of having a left inverse.
  • One participant suggests that the relationship between rank and dimensions of the kernel leads to a conclusion about the dimensions of A but admits to needing further thought.
  • Another participant introduces the concept of the matrix product ATA and its invertibility as a potential pathway to understanding the problem.

Areas of Agreement / Disagreement

Participants express differing views on the applicability of certain properties to non-square matrices, and there is no consensus on how to prove the equivalence between the two statements. The discussion remains unresolved with multiple competing perspectives presented.

Contextual Notes

Limitations include the dependence on definitions of invertibility and the rank-nullity theorem, as well as the unresolved status of how these concepts apply to non-square matrices.

ImAnEngineer
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I found on wikipedia that the following statements are equivalant:
1. Matrix A is left invertible
2. Ax=0 => x=0

I couldn't find the proof so I try to do it myself.

From 1. to 2. is easy. Assume A is left invertible. If Ax=0, then x=Ix=A-1Ax=A-10 = 0 .

I can't figure out how to do 2=>1. Any help is appreciated.

Things that might prove useful:
- A is injective
- dim(ker(A))=0
- rank(A)=n (if A is an m x n matrix)
- [tex]n\leq m[/tex]
 
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If the solutions to [tex]Ax=0[/tex] are only the trivial one, then its RREF is the identity matrix, thus it is invertible.

And another:
[tex]Ax=0[/tex] are only the trivial solution, then [tex]\textrm{det}A\ne 0[/tex] thus it is invertible.
 
Zorba said:
If the solutions to [tex]Ax=0[/tex] are only the trivial one, then its RREF is the identity matrix, thus it is invertible.

And another:
[tex]Ax=0[/tex] are only the trivial solution, then [tex]\textrm{det}A\ne 0[/tex] thus it is invertible.

Why and why?

Note that A is not (necessarily) a square matrix
 
Only square matrices can be inverted, thus the statements only make sense for them.

All of the statements above I used can be shown to be equivalent, but I need to know what level you are at so I can know which equivalent statements to use.

[tex]Ax=0 \Rightarrow \textrm{RREF}(A)=I[/tex] follows from the rank-nullity theorem, have you seen this theorem?

[tex]Ax=0 \Rightarrow \textrm{det}A\ne0[/tex] follows from properties of the determinant and also properties of elementary matrices, are you familiar with these?
 
Zorba said:
Only square matrices can be inverted, thus the statements only make sense for them.

All of the statements above I used can be shown to be equivalent, but I need to know what level you are at so I can know which equivalent statements to use.

[tex]Ax=0 \Rightarrow \textrm{RREF}(A)=I[/tex] follows from the rank-nullity theorem, have you seen this theorem?

[tex]Ax=0 \Rightarrow \textrm{det}A\ne0[/tex] follows from properties of the determinant and also properties of elementary matrices, are you familiar with these?
This is simply not true. I have a better source ("Linear algebra done wrong"), but I'll use wikipedia to quote:
Non-square matrices (m-by-n matrices for which m ≠ n) do not have an inverse. However, in some cases such a matrix may have a left inverse or right inverse. If A is m-by-n and the rank of A is equal to n, then A has a left inverse: an n-by-m matrix B such that BA = I. If A has rank m, then it has a right inverse: an n-by-m matrix B such that AB = I.

I underlined what I'm trying to proof.

I know the theorems but I don't see how they are applicable to a non-square matrix.
 
ImAnEngineer said:
This is simply not true. I have a better source (Linear algebra done wrong), but I'll use wikipedia to quote:I underlined what I'm trying to proof.

Ah I see, just a left-inverse, in that case then you must avoid mentioning determinants although my first statement still holds.
 
Zorba said:
Ah I see, just a left-inverse, in that case then you must avoid mentioning determinants although my first statement still holds.

That statement does hold indeed, and helped me to get:
rank(A) + dim(ker(A)) = rank(A) = n
rank(At) + dim(ker(At))= rank(A) + dim(ker(At)) = n + dim(ker(At)) = m
Hence: [tex]m\geq n[/tex]

But it doesn't get me any further.
 
ImAnEngineer said:
That statement does hold indeed, and helped me to get:
rank(A) + dim(ker(A)) = rank(A) = n
rank(At) + dim(ker(At))= rank(A) + dim(ker(At)) = n + dim(ker(At)) = m
Hence: [tex]m\geq n[/tex]

But it doesn't get me any further.

But [tex]Ax=0[/tex] having only the trivial solution [tex]\Rightarrow \textrm{ker}A={ \emptyset }[/tex] which again seems to imply that its square... I don't know, I'll have to have a think about it.
 
Zorba said:
But [tex]Ax=0[/tex] having only the trivial solution [tex]\Rightarrow \textrm{ker}A={ \emptyset }[/tex] which again seems to imply that its square... I don't know, I'll have to have a think about it.

It's not true that Ker(A)= empty set, because [tex]0 \in \textrm{ker}(A)[/tex] . And why do you think it implies that it's square?
 
  • #10
Ax = 0 => x = 0
==> rank(A) = n = rank(ATA)
==> ATA is invertible.

Using this you should get the ball rolling... Or I may be wrong.
 
  • #11
(ATA)-1ATA = I

That's it, thanks :)
 

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