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I wanted to prove/disprove whether for every matrix $A\in \operatorname{Mat}_{n \times n}$

$\operatorname{rank} (A^2) = \operatorname{rank}(A)$ for any matrix $A\in \operatorname{Mat}_{n \times n}$

I know that for two matrices $A, B$ (it actually doesn't matters what is the size of $B$ as long as $AB$ is defined)

$$\operatorname{rank}(AB) \leq \min \{ \operatorname{rank}(A), \operatorname{rank}(B)\}$$

Therefore, $$\operatorname{rank}(A^2) \leq \operatorname{rank} (A)$$

In order to prove that:

$$\operatorname{rank}(A^2) = \operatorname{rank}(A)$$

you'd have to prove that: $$\operatorname{rank}(A^2) \geq \operatorname{rank}(A)$$ which I don't know how to prove, or finding a different way to prove directly both directions (meaning; one direction is $\leq$ and the other is $\geq$)

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  • $\begingroup$ What about nilpotent matrices? $\endgroup$
    – Quiver
    Aug 5, 2018 at 15:16
  • $\begingroup$ If $A \in \operatorname{Mat}_{m\times n}$ then $A^2$ exists only if $n=m. \qquad$ $\endgroup$
    – Michael Hardy
    Aug 5, 2018 at 15:22
  • $\begingroup$ In general, for a square matrix $A$, $\text{rank}(A^2)=\text{rank}(A)$ if and only if the column space of $A$ intersects the nullspace of $A$ trivially. $\endgroup$
    – Batominovski
    Aug 5, 2018 at 16:50

2 Answers 2

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It is not true that the square of a matrix has the same rank as the matrix itself. For instance, the $2\times 2$ matrix $A= \left[ {\begin{array}{cc} 0 & 1 \\ 0 & 0 \\ \end{array} } \right]$ has rank $1$ and satisfies $A^2=0$.

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  • $\begingroup$ but here's what I'm confused about - for a squared matrix, $\text rank (A) = \text rank (A^T)$, so $\text rank (AA^T) = \text rank (A^2)$ $\endgroup$
    – Jneven
    Aug 5, 2018 at 15:20
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    $\begingroup$ @Jneven This is a totally separate problem, in general $A^T$ has nothing to do with powers of $A$. I suggest you look at this then: math.stackexchange.com/questions/2315/… $\endgroup$
    – Suzet
    Aug 5, 2018 at 15:21
  • $\begingroup$ but $\text rank (A) \leq \text {min}$ {${sp\{R(A)\}}, {sp\{C(A)\}}$ $\endgroup$
    – Jneven
    Aug 5, 2018 at 15:32
  • $\begingroup$ @Jneven The rank is not multiplicative. It is not true that $\operatorname{rank}(AB)=\operatorname{rank}(A)\operatorname{rank}(B)$ as you seem to suggest. The quantities $\operatorname{rank}(AA^T)$ and $\operatorname{rank}(A^2)$ are not equal. The matrix $A$ I exhibed in my answer is a counter example for it. I let you compute $AA^T$ and see that it is not zero, whereas $A^2=0$ ! $\endgroup$
    – Suzet
    Aug 5, 2018 at 15:38
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    $\begingroup$ Yes, and this is true. However, $\operatorname{rank}(AA^T)=\operatorname{rank}(A^2)$ is not true. All you can say, using your inequality, is $\operatorname{rank}(AA^T)\leq \operatorname{rank}(A)$ (and also $\operatorname{rank}(A^2)\leq \operatorname{rank}(A)$). $\endgroup$
    – Suzet
    Aug 5, 2018 at 15:46
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First, it makes no sense to write $A^2$ if $A$ is not a square matrix. So you need $m=n$.

This being said, there is a class of matrices called nilpotent, from which it is trivial to build counterexamples:

$$\operatorname{rk}\left(\matrix{0&1\\0&0}\right)=1$$$$\operatorname{rk}\left(\matrix{0&1\\0&0}\right)^2=0$$

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  • $\begingroup$ I would have to disagree about the statement that "it would make no sense". in fact, I think writing $AA$ would just be weird. $\endgroup$
    – Jneven
    Aug 5, 2018 at 15:18
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    $\begingroup$ @Jneven No, seriously, it would make no mathematical sense. A product of matrices is defined when the number of columns of the left factor is the number of rows of the right factor. $\endgroup$
    – Arnaud Mortier
    Aug 5, 2018 at 15:19
  • $\begingroup$ you're right, I understood my confusion. $\endgroup$
    – Jneven
    Aug 5, 2018 at 15:22

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