Show that if the real symmetric matrix \(A\) has real eigenvalues \(\lambda _i\) and
orthogonal eigenvectors \(\mathbf {x}_i\), then for any vector \(\mathbf {y}=\sum _i c_i\mathbf {x}_i\), the smallest eigenvalue
satisfies \[ \lambda _0\le \frac {\mathbf {y}^TA\mathbf {y}}{\mathbf {y}^T\mathbf {y}}. \]
Show that the eigenfunctions \(\phi \) and eigenvalues \(-\lambda \) of the problem \[ \nabla ^2\phi +\lambda \phi =0\quad \text {in a region }D, \] with \[ \frac {\partial \phi }{\partial n}+\alpha \phi =0\quad \text {on }\partial D, \] where \(\partial /\partial n\)
is the outward normal derivative, satisfy \[ \lambda \int _D \phi ^2d x =\int _D \lvert \nabla \phi \rvert ^2d x+\alpha \int _{\partial D}\phi ^2d s. \] Assuming that the eigenfunctions
\(\phi \) form a complete orthonormal set, derive an upper bound for the smallest
eigenvalue in terms of an appropriate energy integral (Rayleigh quotient).