21. Multiple Integrals in Curvilinear Coordinates
d. Integrating in 2D Curvilinear Coordinates
3. The Jacobian
On the previous page we found that a double integral may be computed in a curvilinear coordinate system, \((u,v)\), as: \[ \iint_R f\,dA=\iint_R f(u,v)\,J\,du\,dv \] where the differential of area is \[ dA=J\,du\,dv \] and where \(J\) is the Jacobian factor: \[ J=|\vec{e}_u\times\vec{e}_v| \] However, there is a problem with this formula for the Jacobian, namely the cross product is only defined in \(3\) dimensions, but \(\vec{e}_u\) and \(\vec{e}_v\) are \(2\) dimensional vectors. To fix this, we simply let \(\vec{e}_u\) and \(\vec{e}_v\) have a third component of \(0\). Then: \[ \vec{e}_u\times\vec{e}_v =\begin{vmatrix} \hat{\imath} & \hat{\jmath} & \hat k \\[4pt] \dfrac{\partial x}{\partial u} & \dfrac{\partial y}{\partial u} & 0 \\[8pt] \dfrac{\partial x}{\partial v} & \dfrac{\partial y}{\partial v} & 0 \end{vmatrix} =\hat{\imath}(0)-\hat{\jmath}(0)+\hat{k} \left(\dfrac{\partial x}{\partial u}\dfrac{\partial y}{\partial v} -\,\dfrac{\partial y}{\partial u}\dfrac{\partial x}{\partial v}\right) \] and: \[ J=|\vec{e}_u\times\vec{e}_v| =\sqrt{0^2+0^2 +\left(\dfrac{\partial x}{\partial u}\dfrac{\partial y}{\partial v} -\,\dfrac{\partial y}{\partial u}\dfrac{\partial x}{\partial v}\right)^2} =\left|\dfrac{\partial x}{\partial u}\dfrac{\partial y}{\partial v} -\,\dfrac{\partial y}{\partial u}\dfrac{\partial x}{\partial v}\right| \] Notice that this expression for the Jacobian factor is the absolute value of a determinant called the Jacobian determinant which is usually denoted by \[ \dfrac{\partial(x,y)}{\partial(u,v)}= \begin{vmatrix} \dfrac{\partial x}{\partial u} & \dfrac{\partial y}{\partial u} \\[6pt] \dfrac{\partial x}{\partial v} & \dfrac{\partial y}{\partial v} \end{vmatrix} =\det \begin{pmatrix} \dfrac{\partial x}{\partial u} & \dfrac{\partial y}{\partial u} \\[6pt] \dfrac{\partial x}{\partial v} & \dfrac{\partial y}{\partial v} \end{pmatrix} \qquad \text{(*)} \]
Notice that the rows of the Jacobian determinant are the tangent vectors \(\vec{e}_u\) and \(\vec{e}_v\). \[ \dfrac{\partial(x,y)}{\partial(u,v)}= \begin{vmatrix} \leftarrow & \vec e_u & \rightarrow \\ \leftarrow & \vec e_v & \rightarrow \end{vmatrix} \]
Recall that the area is always positive. Likewise the Jacobian factor is always positive and requires an absolute value.
In summary:
The Jacobian factor is the absolute value of the Jacobian determinant: \[ J=\left|\dfrac{\partial(x,y)}{\partial(u,v)}\right| \] and appears in the differential of area: \[ dA=J\,du\,dv \]
3 Meanings of Jacobian
Actually, there are three different quantities which are frequently called the Jacobian. They are:
-
The Jacobian Matrix:
\(
\begin{pmatrix}
\dfrac{\partial x}{\partial u} & \dfrac{\partial x}{\partial v} \\
\dfrac{\partial y}{\partial u} & \dfrac{\partial y}{\partial v}
\end{pmatrix}
\)
Note: This is actually the transpose of the matrix displayed in (*). This transpose has no affect on the determinant. -
The Jacobian Determinant:
\(
\dfrac{\partial(x,y)}{\partial(u,v)}
=\begin{vmatrix}
\dfrac{\partial x}{\partial u} & \dfrac{\partial x}{\partial v} \\
\dfrac{\partial y}{\partial u} & \dfrac{\partial y}{\partial v}
\end{vmatrix}
\)
Note: This defines the symbol \(\dfrac{\partial(x,y)}{\partial(u,v)}\) as the Jacobian determinant. -
The Jacobian Factor:
\(
J=\left|\dfrac{\partial(x,y)}{\partial(u,v)}\right|
=\left|
\begin{vmatrix}
\dfrac{\partial x}{\partial u} & \dfrac{\partial x}{\partial v} \\
\dfrac{\partial y}{\partial u} & \dfrac{\partial y}{\partial v}
\end{vmatrix}
\right|
\)
Note:The double bars around the matrix indicate that we first take a determinant and then an absolute value.
The Jacobian factor is what appears in an integral.
Thus the area element is \(dA=J\,du\,dv\).
The Jacobian determinant is useful in surface
integtrals, which we study in the
next chapter.
The Jacobian matrix is used frequently in linear
algebra, but not in this course.
So, if someone refers to the Jacobian, you need to ask which one. However, in
this book, if we just say Jacobian, we will mean the Jacobian factor.
As you may have noticed in the previous formulas, multiple vertical bars can
be quite confusing. A pair of vertical bars can have one of three meanings:
1) Absolute value
2) Length
3) Determinant
The meaning of the vertical bars is determined by the quantity inside them.
1) Vertical bars around a scalar mean the
absolute value of that scalar.
2) Vertical bars around a vector mean the
length of that vector.
3) Vertical bars around a matrix mean the
determinant of that matrix.
Notice that in formula for the Jacobian factor there are two pairs of vertical bars. The inner pair encloses a matrix. So this is a determinant which produces a scalar. So the outer pair of vertical bars is an absolute value.
The Jacobian for Polar Coordinates
Recompute the Jacobian factor for polar coordinates (again).
Recall that in polar coordinates, \(\vec{R}(r,\theta)=\left\langle r\cos\theta,r\sin\theta\right\rangle\). So the tangent vectors are: \[ \vec{e}_r=\left\langle \cos\theta,\sin\theta\right\rangle \qquad \text{and} \qquad \vec{e}_\theta=\left\langle -r\sin\theta,r\cos\theta\right\rangle \] So \[\begin{aligned} J&=\left|\dfrac{\partial(x,y)}{\partial(r,\theta)}\right| =\left| \begin{vmatrix} \dfrac{\partial x}{\partial r} & \dfrac{\partial y}{\partial r} \\[6pt] \dfrac{\partial x}{\partial \theta} & \dfrac{\partial y}{\partial \theta} \end{vmatrix} \right| =\left| \begin{vmatrix} \leftarrow & \vec e_r & \rightarrow \\ \leftarrow & \vec e_\theta & \rightarrow \end{vmatrix} \right| \\ &=\left| \begin{vmatrix} \cos\theta & \sin\theta \\ -r\sin\theta & r\cos\theta \end{vmatrix} \right| =|r\cos^2\theta-(-r\sin^2\theta)| =r \end{aligned}\] Using the general formulas for the Jacobian, we have just derived the Jacobian for polar coordinates, \(J=r\). Consequently, \(dA=r\,dr\,d\theta\).
Notice that this requires us to take \(r\) positive when we compute integrals.
On the next two pages we look at elliptic, and “ diamond shaped” coordinate systems and use them to compute integrals.
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