Quantum tomography benchmarking

TL;DR

This paper introduces a general methodology and software tools for benchmarking quantum tomography methods, enabling systematic comparison based on resource efficiency and accuracy in quantum computing research.

Contribution

It develops a comprehensive comparison framework and software for evaluating quantum tomography methods, addressing the lack of standardized benchmarking approaches.

Findings

Identified method-specific features in QT techniques.

Provided estimates of relative efficiency among tested QT methods.

Validated the benchmarking methodology with numerical experiments.

Abstract

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.