MUB tomography performance under influence of systematic errors

We propose a method for accounting the simplest type of systematic errors in the mutually unbiased bases (MUB) tomography, emerging due to an imperfect (non-orthogonal) preparation of measurement bases. The present approach allows to analyze analytically the performance of MUB tomography in finite systems of an arbitrary (prime) dimension. We compare the estimation error appearing in such an imperfect MUB-based tomography with those intrinsically present in the framework of the symmetric informationally complete positive operator value measure (SIC-POVM) reconstruction scheme and find that MUB tomography outperforms the perfect SIC-POVM tomography including the case of strong errors.