I have the following problem:
Define $H$ and $R_k$ for $k=1\dots N$, to be $M\times M$ positive definite matrices.
The problem is to find optimal weights $p_k$that solves the following problem
\begin{equation*} \begin{aligned} & \underset{p}{\text{minimize}} & & tr\left(\sum_{k=1}^N p_k^2 H^{-1}R_k\right) \\ & \text{subject to} & & \sum_{k=1}^Np_k = 1, \;\;\; p_k>0 \;\;\;\forall \; k \end{aligned} \end{equation*}
I know that the solution is given by the following
\begin{equation*} p^0_k = \frac{1}{tr\left(H^{-1}R_k\right)} \left( \sum_{l=1}^N\frac{1}{tr\left(H^{-1}R_l\right)}\right)^{-1}. \end{equation*}
It is obvious that $\sum_{k=1}^Np^0_k = 1$ and that $p^0_k>0 \;\;\;\forall \; k$, so the given solution satisfies the constraint. But how to show that it minimizes the trace?