4.7 Article

Quantum tomography benchmarking

期刊

QUANTUM INFORMATION PROCESSING
卷 20, 期 10, 页码 -

出版社

SPRINGER
DOI: 10.1007/s11128-021-03285-9

关键词

Quantum tomography; Quantum computing; Benchmarking

资金

  1. Ministry of Science and Higher Education of Russia [0066-2019-0005]
  2. Theoretical Physics and Mathematics Advancement Foundation BASIS [20-1-1-34-1]

向作者/读者索取更多资源

Recent advances in quantum computers and simulators are leading to the development of full-scale quantum computing devices. Quantum tomography is a critical milestone in debugging and assessing the efficiency of different methods in various conditions. Developing a general methodology and software for comparing quantum-state tomography methods provides estimates of relative efficiency and method-specific features.
Recent advances in quantum computers and simulators are steadily leading us toward 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.

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