14. Directional Derivatives and Gradients
d. Properties of the Gradient
- \(\vec\nabla f\) points perpendicular to each level set of \(f\).
- \(|\vec\nabla f|\) is inversely proportional to the spacing between level sets. (Qualitative)
3. Applications of Gradient Properties 3 & 4
Find a normal vector to the ellipse \(\dfrac{x^2}{8}+\dfrac{y^2}{18}=1\) at the point \((x,y)=(2,3)\).
The ellipse is the level set of \(f=\dfrac{x^2}{8}+\dfrac{y^2}{18}\) with value \(1\). Its gradient will be perpendicular to the level set. The gradient is: \[ \vec\nabla f=\left\langle \dfrac{x}{4},\dfrac{y}{9}\right\rangle \] At \((x,y)=(2,3)\), the normal is: \[ \vec N=\left.\vec\nabla f\right|_{(2,3)} =\left\langle \dfrac{1}{2},\dfrac{1}{3}\right\rangle \] Any multiple of this is acceptable.
The plot at the right is a contour plot of \(f(x,y)\). At which point is \(|\vec\nabla f|\) the largest?
Point \(P\)
Point \(Q\)
Point \(R\)
Point \(S\)
\(P\). Incorrect. At this point the countours are far apart. What does that say about \(|\vec\nabla f|\)? Try again.
\(Q\). Sorry. At this point the countours are farther apart than at \(R\) but closer than at \(P\). What does that say about \(|\vec\nabla f|\)? Try again.
\(R\). Sorry. At this point the countours are farther apart than at \(S\) but closer than at \(Q\). What does that say about \(|\vec\nabla f|\)? Try again.
\(S\). Correct. At this point the countours are close together. So \(|\vec\nabla f|\) is largest.
Find the points on the hyperboloid \(2x^2-y^2+2z^2=1\) where the normal line is parallel to the line that joins the points \(P=(2,-1,3)\) and \(Q=(6,-4,1)\).
The points are: \[ (x,y,z)=(2,3,-1) \qquad \text{and} \qquad (x,y,z)=(-2,-3,1) \]
The hyperboloid is a level set of the function \(f(x,y,z)=2x^2-y^2+2z^2\). The direction of the normal line is its gradient: \[ \vec\nabla f=\langle 4x,-2y,4z\rangle \] We want this to be parallel to the vector from \(P\) to \(Q\): \[ \overrightarrow{PQ}=Q-P=\langle 4,-3,-2\rangle \] To say they are parallel means one vector is a multiple of the other, i.e. \[ \vec\nabla f=\lambda\overrightarrow{PQ} \qquad \text{or} \qquad \langle 4x,-2y,4z\rangle =\lambda\langle 4,-3,-2\rangle \] where \(\lambda\) (the Greek letter lambda) is the proportionality factor. This gives \(3\) equations, \[ 4x=4\lambda \qquad -2y=-3\lambda \qquad 4z=-2\lambda, \] but there are \(4\) unknowns: \(x\), \(y\), \(z\) and \(\lambda\). We need a \(4^\text{th}\) equation. It is the equation of the hyperboloid: \[ 2x^2-y^2+2z^2=1 \] To solve these equations, we use the first three equations to express \(x\), \(y\) and \(z\) in terms of \(\lambda\) and substitute these into the equation of the hyperbola: \[ x=\lambda \qquad y=\dfrac{3}{2}\lambda \qquad z=-\,\dfrac{1}{2}\lambda \] \[ 2(\lambda)^2-\left(\dfrac{3}{2}\lambda\right)^2 +2\left(-\,\dfrac{1}{2}\lambda\right)^2=1 \] This says \((2-\,\dfrac{9}{4}+\dfrac{1}{2})\lambda^2=1\) or \(\dfrac{\lambda^2}{4}=1\) or \(\lambda=\pm2\). So the points are: \[ (x,y,z)=(2,3,-1) \qquad \text{and} \qquad (x,y,z)=(-2,-3,1) \]
The method used to solve this problem is similar to one that will be used later to solve Max-Min problems using Lagrange multipliers.
There are more significant applications of Property 3 on the next three pages.
Heading
Placeholder text: Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum Lorem ipsum