[proofplan]
We compare the [bilinear form](/page/Bilinear%20Form) with its associated [linear map](/page/Linear%20Map) $\Psi_B:W\to V^*$. In the chosen basis of $W$ and the [dual basis](/theorems/414) of $V^*$, the coordinate matrix of $\Psi_B$ is exactly the matrix $A$ whose entries are $B(v_i,w_j)$. Therefore the rank of the bilinear form, defined as the dimension of the image of $\Psi_B$, is the same as the column rank of $A$.
[/proofplan]
custom_env
admin
[step:Pass from the bilinear form to its associated linear map]
Define the map
\begin{align*}
\Psi_B: W \to V^*
\end{align*}
by declaring that, for each $w \in W$, the functional $\Psi_B(w):V\to k$ is
\begin{align*}
\Psi_B(w)(v)=B(v,w).
\end{align*}
For fixed $w \in W$, the map $v \mapsto B(v,w)$ is linear because $B$ is linear in its first variable, so $\Psi_B(w)\in V^*$. For $w,w' \in W$ and $\lambda \in k$, bilinearity in the second variable gives
\begin{align*}
\Psi_B(w+\lambda w')(v)=B(v,w+\lambda w')=B(v,w)+\lambda B(v,w')=(\Psi_B(w)+\lambda\Psi_B(w'))(v)
\end{align*}
for every $v\in V$. Hence $\Psi_B$ is a linear map $W\to V^*$.
By definition of the [rank of a bilinear form](/page/Rank%20of%20a%20Bilinear%20Form),
\begin{align*}
\operatorname{rank}(B)=\operatorname{rank}(\Psi_B)=\dim_k \operatorname{im}(\Psi_B).
\end{align*}
[/step]
custom_env
admin
[step:Identify the coordinate matrix of $\Psi_B$]Let $(v_1^*,\dots,v_m^*)$ denote the dual basis of $V^*$, so $v_i^*:V\to k$ is the linear functional satisfying $v_i^*(v_\ell)=1$ if $i=\ell$ and $v_i^*(v_\ell)=0$ otherwise.
For each $j\in\{1,\dots,n\}$, write $\Psi_B(w_j)$ in the dual basis:
\begin{align*}
\Psi_B(w_j)=\sum_{i=1}^m c_{ij}v_i^*
\end{align*}
for uniquely determined scalars $c_{ij}\in k$. Evaluating both sides at $v_\ell$ gives
\begin{align*}
c_{\ell j}=\Psi_B(w_j)(v_\ell)=B(v_\ell,w_j)=A_{\ell j}.
\end{align*}
Thus
\begin{align*}
\Psi_B(w_j)=\sum_{i=1}^m A_{ij}v_i^*.
\end{align*}
Therefore the matrix of the linear map $\Psi_B:W\to V^*$ with respect to the basis $(w_1,\dots,w_n)$ of $W$ and the dual basis $(v_1^*,\dots,v_m^*)$ of $V^*$ is precisely $A$.[/step]
custom_env
admin
[guided]The point of introducing $\Psi_B$ is that a bilinear form has two inputs, while matrix rank is naturally attached to a linear map. We freeze the first input as the variable of a functional and send each $w\in W$ to the functional $v\mapsto B(v,w)$.
Let $(v_1^*,\dots,v_m^*)$ be the dual basis of $V^*$. To find the coordinate matrix of $\Psi_B$, we must compute the coordinates of each image vector $\Psi_B(w_j)$ in this dual basis. So write
\begin{align*}
\Psi_B(w_j)=\sum_{i=1}^m c_{ij}v_i^*.
\end{align*}
The coefficient $c_{\ell j}$ is recovered by evaluating at $v_\ell$, because the dual basis satisfies $v_i^*(v_\ell)=0$ unless $i=\ell$, and $v_\ell^*(v_\ell)=1$. Hence
\begin{align*}
c_{\ell j}=\Psi_B(w_j)(v_\ell).
\end{align*}
By the definition of $\Psi_B$, this is
\begin{align*}
\Psi_B(w_j)(v_\ell)=B(v_\ell,w_j).
\end{align*}
By the definition of the matrix $A$ of the bilinear form in the bases $(v_1,\dots,v_m)$ and $(w_1,\dots,w_n)$, we have
\begin{align*}
B(v_\ell,w_j)=A_{\ell j}.
\end{align*}
Therefore every column of the coordinate matrix of $\Psi_B$ is exactly the corresponding column of $A$. This verifies that the coordinate matrix of $\Psi_B$ is $A$ itself.[/guided]
custom_env
admin
[step:Compare the rank of the map with the rank of its coordinate matrix]
The rank of a matrix is the dimension of the span of its columns. Since the columns of $A$ are exactly the coordinate vectors of
\begin{align*}
\Psi_B(w_1),\dots,\Psi_B(w_n)
\end{align*}
in the basis $(v_1^*,\dots,v_m^*)$ of $V^*$, the column span of $A$ is the coordinate representation of the subspace
\begin{align*}
\operatorname{span}_k\{\Psi_B(w_1),\dots,\Psi_B(w_n)\}\subseteq V^*.
\end{align*}
Because $(w_1,\dots,w_n)$ is a basis of $W$, every $w\in W$ is a $k$-linear combination of $w_1,\dots,w_n$, and linearity of $\Psi_B$ gives
\begin{align*}
\operatorname{im}(\Psi_B)=\operatorname{span}_k\{\Psi_B(w_1),\dots,\Psi_B(w_n)\}.
\end{align*}
Passing to coordinates in a basis preserves [dimension of subspaces](/theorems/375). Therefore
\begin{align*}
\operatorname{rank}(A)=\dim_k\operatorname{im}(\Psi_B)=\operatorname{rank}(\Psi_B)=\operatorname{rank}(B).
\end{align*}
This proves the claimed equality.
[/step]