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I have to prove this lemma without using the concept of rank neither the concept of determinant:

$A$ is a singular matrix iff $A^T$ is singular

Unfortunately i've only found proofs that contains rank and determinant. Can you help me ?

Parcly Taxel
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Koinos
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3 Answers3

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Assume for contradiction that $A^T$ was invertible, then there would be a matrix $B$ with $BA^T=I$. But that means $I=I^T=(BA^T)^T=AB^T$, so $B^T$ would be an inverse for $A$, which is impossible.

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Formally, a singular matrix $A$ is one for which there does not exist another matrix $B$ with $AB=BA=I$.

The statement here can be proven through the contrapositive: if $A$ is not singular, there exists some $B$ with $AB=I$. Transposing this gives $B^TA^T=I$, so $A^T$ is not singular. Thus if $A^T$ is singular, $A$ is singular. Replacing $A$ with $A^T$ in the last sentence gives the other direction, so the original statement is established.

Parcly Taxel
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If $A$ were singular, then the kernel (null space) of $A$ has nonzero vectors in it. That is, $Ax = 0$ admits nontrivial (nonzero) solutions. Now take the transpose on each side. Then if $x$ is nonzero, so is $x^T$ (clearly), and so $x^T A^T = 0^T$ also admits nonzero solutions, so $A^T$ is singular.

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    How do you know that $x^TA^T=0$, $x\ne0$ implies that there exists $y\ne0$ with $A^Ty=0$? – David C. Ullrich Jul 24 '18 at 16:46
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    @DavidC.Ullrich Sean Roberson did not directly claim that. If $x^TA^T=0^T$ has a nontrivial solution, then clearly its rows are not linearly independent, so it is singular. – Acccumulation Jul 24 '18 at 21:48
  • @Acccumulation We need a definition. His definition of singular seems to be non-zero kernel. Which says exactly that the columns are dependent. Now saying rows dependent implies singular is just assuming what we 're supposedly proving, that the transpose of a singular matrix is singular. – David C. Ullrich Jul 25 '18 at 12:30