Robust Extraction of Tomographic Information via Randomized Benchmarking

TL;DR

This paper introduces a robust method using randomized benchmarking to accurately reconstruct and verify the unital part of quantum maps, enabling efficient characterization of quantum circuits and components.

Contribution

It extends randomized benchmarking techniques to reconstruct unital quantum maps and estimate fidelities outside the Clifford group, improving quantum circuit verification.

Findings

Robust reconstruction of unital quantum maps using randomized benchmarking.

Efficient estimation of average fidelity for non-Clifford unitaries.

Rigorous bounds on the complexity of the benchmarking procedures.

Abstract

We describe how randomized benchmarking can be used to reconstruct the unital part of any trace-preserving quantum map, which in turn is sufficient for the full characterization of any unitary evolution, or more generally, any unital trace-preserving evolution. This approach inherits randomized benchmarking's robustness to preparation, measurement, and gate imperfections, therefore avoiding systematic errors caused by these imperfections. We also extend these techniques to efficiently estimate the average fidelity of a quantum map to unitary maps outside of the Clifford group. The unitaries we consider correspond to large circuits commonly used as building blocks to achieve scalable, universal, and fault-tolerant quantum computation. Hence, we can efficiently verify all such subcomponents of a circuit-based universal quantum computer. In addition, we rigorously bound the time and sampling complexities of randomized benchmarking procedures, proving that the required non-linear estimation problem can be solved efficiently.