Minimizing effects of the Kalman gain on Posterior covariance Eigenvalues, the characteristic polynomial and symmetric polynomials of Eigenvalues

The Kalman gain is commonly derived as the minimizer of the trace of theposterior covariance. It is known that it also minimizes the determinant of the posterior covariance. I will show that it also minimizes the smallest Eigenvalue ${\lambda }_1$ and the chracteristic polynomial on $(-\mathrm{\infty },{\lambda }_1)$ and is critical point to all symmetric polynomials of the Eigenvalues, minimizing some. This expands the range of uncertainty measures for which the Kalman Filter is optimal.