Let $A$ be a nonzero symmetric $3\times3$ matrix. Consider the function $f(\textbf x)=\frac{1}{2}(A \textbf x)\cdot \textbf x$.
(a) What is $\nabla f$?
Here's what I did:
Let $A= \left[ \begin{array}{ccc} a & b & c \\ b & e & d \\ c & d & g \end{array} \right]$ and $\textbf x = \left[ \begin{array}{c} x \\ y \\ z \end{array} \right]$.
$ f(\textbf x)=\frac{1}{2}(A \textbf x)\cdot \textbf x = \frac{1}{2}(\left[ \begin{array}{ccc} a & b & c \\ b & e & d \\ c & d & g \end{array} \right] \left[ \begin{array}{c} x \\ y \\ z \end{array} \right])\cdot \textbf[x \space y \space z \textbf] \\= \frac{1}{2}ax^2+\frac{1}{2}ey^2+\frac{1}{2}gz^2+bxy+cxz+dyz=f(x,y,z).$
I basically converted the vectors' dot products into defined matrix multiplication. Then I took the partial derivatives to form $\nabla f=(ax+by+cz,bx+ey+dz,cx+dy+gz)$. In matrix form this reduces to $A \textbf x$. Can someone tell me if I did this correctly?
Here is where I am stuck:
(b) Consider the restriction of $f$ to the unit sphere $S$ in $\mathbb R^3$. We know that $f$ must have a maximum and minimum on $S$. Show that there must be an $\textbf x \in S$ and a $\lambda \neq 0$ such that $A \textbf x = \lambda \textbf x$. (The vector $\textbf x$ is called an eigenvector, while the scalar $\lambda$ is called an eigenvalue.)
I'm not sure how to show this, and I am taking Linear Algebra as well but we haven't covered eigenvectors yet. My instructor says that knowledge of eigenvectors is not necessary to solve this. It is not clear to me what the question is asking, and I don't know where to begin.