Practical characterization of quantum devices without tomography

TL;DR

This paper introduces resource-efficient methods for characterizing quantum devices by estimating fidelity and identifying best-matching descriptions without full tomography, enabling scalable assessment of larger quantum systems.

Contribution

The authors develop targeted schemes for fidelity estimation and model selection that significantly reduce experimental and computational resources compared to traditional quantum tomography.

Findings

Fidelity can be estimated with a number of settings independent of system size.

The methods outperform full tomography in resource efficiency.

The approach enables scalable characterization of larger quantum devices.

Abstract

Quantum tomography is the main method used to assess the quality of quantum information processing devices, but its complexity presents a major obstacle for the characterization of even moderately large systems. The number of experimental settings required to extract complete information about a device grows exponentially with its size, and so does the running time for processing the data generated by these experiments. Part of the problem is that tomography generates much more information than is usually sought. Taking a more targeted approach, we develop schemes that enable (i) estimating the fidelity of an experiment to a theoretical ideal description, (ii) learning which description within a reduced subset best matches the experimental data. Both these approaches yield a significant reduction in resources compared to tomography. In particular, we demonstrate that fidelity can be estimated from a number of simple experimental settings that is independent of the system size, removing an important roadblock for the experimental study of larger quantum information processing units.