POTW Is the Rank of AB Related to the Ranks of A and B?

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Let ##F## be a field. If ##A \in M_{n\times k}(F)## and ##B\in M_{k\times n}(F)##, show that $$\operatorname{rank}(A) + \operatorname{rank}(B) - k \le \operatorname{rank}(AB) \le \min\{\operatorname{rank}(A), \operatorname{rank}(B)\}$$
 
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First some preliminaries. The column space of a matrix ##M##, denoted ##\mathcal{C} (M)##, is the span of the columns of ##M## and the row space of a matrix ##M##, denoted ##\mathcal{R} (M)##, is the span of the rows of ##M##. The column rank of a matrix ##M## is the dimension of the column space of ##M##, while the row rank of ##M## is the dimension of the row space of ##M##. It can be shown that the column rank is equal to the row rank, which is denoted ##\text{rank} (M)##. Note ##\mathcal{C} (M)## is the ##\text{range} (M)##.

For ##M \in M_{k \times n} (F)## we have by the rank-nullity theorem:

\begin{align*}
\dim \ker (M) + \dim \text{range} (M) = n .
\end{align*}

But ##\dim \text{range} (M) = \dim \mathcal{C} (M) = \text{rank} (M)##. Therefore,

\begin{align*}
\dim \ker (M) + \text{rank} (M) = n \qquad (*)
\end{align*}

We have the inequality

\begin{align*}
\dim \ker (AB) \leq \dim \ker (A) + \dim \ker (B) \qquad (**)
\end{align*}

as

\begin{align*}
\dim \ker (AB) =\dim [\ker (A) \cap \text{range} (B)] + \dim \ker (B) .
\end{align*}

Using ##(*)## in ##(**)##,

\begin{align*}
[n - \text{rank} (AB)] \leq [k - \text{rank} (A)] + [n - \text{rank} (B)]
\end{align*}

or

\begin{align*}
\text{rank} (A) + \text{rank} (B) - k \leq \text{rank} (AB)
\end{align*}

Next, the columns of ##AB## are linear combinations of columns of ##A## and are hence in its span so ##\text{rank} (AB)## is less than or equal to ##\text{rank} (A)##. The rows of ##AB## are linear combinations of rows of ##B## and are hence in its span so ##\text{rank} (AB)## is less than or equal to ##\text{rank} (B)##. Therefore,

\begin{align*}
\text{rank} (AB) \leq \min \{ \text{rank} (A) , \text{rank} (B) \} .
\end{align*}
 
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Supplementary

We elaborate on the proof of:

\begin{align*}
\dim \ker (AB) \leq \dim \ker (A) + \dim \ker (B) .
\end{align*}First, we have by the rank-nullity theorem:

\begin{align*}
\dim \ker (AB) = n - \dim \text{range} (AB) \qquad (*)
\end{align*}

Now, consider the linear transformation ##A_{| \text{range} (B)} : \text{range} (B) \rightarrow F^n## defined by ##A_{| \text{range} (B)} x = A x## for all ##x \in \text{range} (B) \subseteq F^k##. Note ##\text{range} (A_{| \text{range} (B)}) = \text{range} (AB)##. By the rank-nullity theorem applied to ##A_{| \text{range} (B)}##:

\begin{align*}
\dim \text{range} (AB) = \dim \text{range} (A_{| \text{range} (B)}) = \dim \text{range} (B) - \dim \ker (A_{| \text{range} (B)})
\end{align*}

Note, by the rank-nullity theorem, ##\dim \text{range} (B) = n - \dim \ker (B)##, therefore by the previous result

\begin{align*}
\dim \text{range} (AB) = n - \dim \ker (B) - \dim \ker (A_{| \text{range} (B)}) \quad (**)
\end{align*}

Using ##(**)## in ##(*)## we have

\begin{align*}
\dim \ker (AB) = \dim \ker (A_{| \text{range} (B)}) + \dim \ker (B)
\end{align*}

As ##\ker (A_{| \text{range} (B)}) = \ker (A) \cap \text{range} (B)##,

\begin{align*}
\dim \ker (AB) = \dim [\ker (A) \cap \text{range} (B)] + \dim \ker (B) .
\end{align*}

Finally, as ##\ker (A) \cap \text{range} (B) \subseteq \ker (A)##, we have ##\dim [\ker (A) \cap \text{range} (B)] \leq \dim \ker (A)##, and thus

\begin{align*}
\dim \ker (AB) \leq \dim \ker (A) + \dim \ker (B) .
\end{align*}
 

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