TITLE: Maximize $\int_\Gamma\,\langle{y,x}\rangle^2\, dx$
QUESTION [7 upvotes]: Given a bounded, compact, closed surface $\Gamma\subset\mathbb{R}^n$, I'm searching
$$
\max_{y\in\mathbb{R}^n, \|y\|=1} \int_\Gamma \langle y, x\rangle^2.
$$
Without the square, and with the enclosed volume $\Omega$,
$$
\max_{y\in\mathbb{R}^n, \|y\|=1} \int_\Omega \langle y, x\rangle,
$$
I'm guessing $y_\text{max}$ points towards the centroid of $\Omega$. Not sure how to prove that though.
Any hints?

REPLY [3 votes]: Let's do the second one first.  Let 
\begin{align*}
    f(y_1, \dots, y_n) &= \int_\Omega (y_1x_1 + \dots y_n x_n)\,dV \\
    g(y_1, \dots, y_n) &= y_1^2 + y_2^2 + \dots + y_n^2
\end{align*}
We want the critical values of $f$ subject to the constraint that $g=1$.
By the method of Lagrange multipliers, there is a constant $\lambda$ such that, for each $i$ from $1$ to $n$, $\frac{\partial f}{\partial y_i} = \lambda \frac{\partial g}{\partial y_i}$.  That is,
$$
   \int_\Omega x_i \,dV = 2\lambda y_i
$$
for each $i$.  By squaring and summing all $n$ of these equations, we get
$$
4\lambda^2 = \sum_{i=1}^n \left(\int_\Omega x_i \,dV\right)^2
$$
The only way the right-hand side is zero is if $\int_\Omega x_i \,dV = 0$ for each $i$.  In that case $f$ is identically zero and any $y$ will do.
Otherwise, $\lambda \neq 0$, so
$$
    y_i = \frac{1}{2\lambda} \int_\Omega x_i \,dV
$$
Since the $i$th coordinate of the centroid of $\Omega$ is $\bar x_i =\frac{1}{\operatorname{Vol}(\Omega)}\int_\Omega x_i \,dV$, I agree that $y$ is a multiple of $\bar x$.

The first one is trickier, at least, to me.  Let 
$$
   h(y_1,\dots,y_n) = \int_\Gamma (x_1y_1+\dots+x_ny_n)^2\,ds
$$ 
Again, we want to maximize $h$ subject to $g=1$.  We have
$$
    2\int_\Gamma (x_1y_1+\dots+x_ny_n)x_i\,ds = 2\lambda y_i \tag{$*$}
$$
for each $i$.  If we set
$$
    M_{ij} = \int_\Gamma x_i x_j \,ds
$$
then $(*)$ is equivalent to 
$$
    \sum_{j=1}^n M_{ij} y_j = \lambda y_i
$$
In other words, $y$ is an eigenvector of the matrix $M$, corresponding to the eigenvalue $\lambda$.  
The matrix $M$ is symmetric, and I think, positive definite.  I am guessing the latter can be shown by squaring each equation and adding them up like before.  So there is an orthonormal basis of eigenvectors.  Therefore the maximum value of $f$ is the maximum of the eigenvalues of $M$.
I'm not sure if we can say more than that.  This is a very interesting problem but I've already spent way too much time that I should be doing something else! \smiley