  Recent advances in quantum computers and simulators are steadily leading us
towards full-scale quantum computing devices. Due to the fact that debugging is
necessary to create any computing device, quantum tomography (QT) is a critical
milestone on this path. In practice, the choice between different QT methods
faces the lack of comparison methodology. Modern research provides a wide range
of QT methods, which differ in their application areas, as well as experimental
and computational complexity. Testing such methods is also being made under
different conditions, and various efficiency measures are being applied.
Moreover, many methods have complex programming implementations; thus,
comparison becomes extremely difficult. In this study, we have developed a
general methodology for comparing quantum state tomography methods. The
methodology is based on an estimate of the resources needed to achieve the
required accuracy. We have developed a software library (in MATLAB and Python)
that makes it easy to analyze any QT method implementation through a series of
numerical experiments. The conditions for such a simulation are set by the
number of tests corresponding to real physical experiments. As a validation of
the proposed methodology and software, we analyzed and compared a set of QT
methods. The analysis revealed some method-specific features and provided
estimates of the relative efficiency of the methods.
