Lehmann bounds and eigenvalue error estimation The paper investigates the properties of Lehmann’s optimal bounds for eigenvalues of Hermitian problems in order to find a way to efficiently use them for eigenvalue error estimation. A practical error estimation scheme is described that can be employed in the framework of a subspace iteration algorithm and is actually implemented by the HSL-ea19 software package from the HSL Mathematical Software Library of Rutherford Appleton Laboratory.