[step:Compute the pullback of the standard volume form via the Jacobian determinant]We claim that for $f: U \to V$ a $C^1$ map with Jacobian matrix $Jf_x \in \mathbb{R}^{n \times n}$ (entries $(Jf_x)_{ij} = \partial_{x_j}f_i(x)$),
\begin{align*}
f^*(dy_1 \wedge \cdots \wedge dy_n) = \det(Jf_x)\, dx_1 \wedge \cdots \wedge dx_n.
\end{align*}
[claim:Pullback of the top volume form equals the Jacobian determinant times the standard volume form on $U$]
For every $C^1$ map $f: U \to V$, one has
\begin{align*}
f^*(dy_1 \wedge \cdots \wedge dy_n) = \det(Jf_x)\, dx_1 \wedge \cdots \wedge dx_n.
\end{align*}
[/claim]
[proof]
For each $x \in U$ and vectors $v_1, \dots, v_n \in T_xU = \mathbb{R}^n$,
\begin{align*}
\bigl(f^*(dy_1 \wedge \cdots \wedge dy_n)\bigr)_x(v_1, \dots, v_n) &= (dy_1 \wedge \cdots \wedge dy_n)_{f(x)}\bigl(df_x(v_1), \dots, df_x(v_n)\bigr) \\
&= \det\bigl[(dy_i)_{f(x)}(df_x(v_j))\bigr]_{i,j=1}^n.
\end{align*}
The second equality uses the standard determinantal formula for the action of a wedge product of $1$-forms on a tuple of vectors:
\begin{align*}
(\alpha_1 \wedge \cdots \wedge \alpha_n)(w_1, \dots, w_n) = \det\bigl[\alpha_i(w_j)\bigr]_{i,j=1}^n,
\end{align*}
which is the defining property of the wedge product of $1$-forms — equivalently, it follows from the antisymmetric multilinear extension of the [tensor product](/page/Tensor%20Product) $\alpha_1 \otimes \cdots \otimes \alpha_n$. Now $(dy_i)_{f(x)}(df_x(v_j)) = (df_x(v_j))_i$, the $i$-th component of $df_x(v_j) \in \mathbb{R}^n$. By the definition of the [total derivative](/theorems/320) and the Jacobian matrix (see notation standards §0), $df_x: \mathbb{R}^n \to \mathbb{R}^n$ is the [linear map](/page/Linear%20Map) whose matrix in the standard basis is the Jacobian $Jf_x$, with entries $(Jf_x)_{ij} = \partial_{x_j}f_i(x)$. Hence $df_x(v_j) = Jf_x \, v_j$, so
\begin{align*}
\bigl(df_x(v_j)\bigr)_i = (Jf_x \, v_j)_i = \sum_{k=1}^n (Jf_x)_{ik}\, (v_j)_k.
\end{align*}
Therefore the matrix in the determinant equals $Jf_x \cdot V$, where $V$ is the $n \times n$ matrix with columns $v_1, \dots, v_n$. By multiplicativity of the determinant,
\begin{align*}
\det\bigl[(df_x(v_j))_i\bigr] = \det(Jf_x \, V) = \det(Jf_x) \cdot \det(V).
\end{align*}
On the other hand,
\begin{align*}
\bigl(\det(Jf_x)\, dx_1 \wedge \cdots \wedge dx_n\bigr)_x(v_1, \dots, v_n) = \det(Jf_x) \cdot \det(V),
\end{align*}
by the same determinantal formula $(\alpha_1 \wedge \cdots \wedge \alpha_n)(w_1, \dots, w_n) = \det[\alpha_i(w_j)]$ applied with $\alpha_i = dx_i$ and $w_j = v_j$, so that $dx_i(v_j) = (v_j)_i = V_{ij}$. The two expressions agree pointwise, proving the claim.
[/proof]
Multiplying by the scalar $a(f(x))$ and using $\mathbb{R}$-linearity of pullback,
\begin{align*}
f^*\omega = f^*\bigl(a(y)\, dy_1 \wedge \cdots \wedge dy_n\bigr) = (a \circ f)(x) \cdot \det(Jf_x) \, dx_1 \wedge \cdots \wedge dx_n.
\end{align*}[/step]