Characterizing the Reproducibility of Noisy Quantum Circuits

TL;DR

This paper investigates the reproducibility of noisy quantum circuits by quantifying outcome variability with the Hellinger distance and relating it to device noise characterization, providing an efficient predictive method validated on superconducting qubits.

Contribution

It introduces a method to assess quantum circuit reproducibility using Hellinger distance and links it to device noise metrics, offering an analytic bound and validation on real hardware.

Findings

Device characterization bounds outcome variability.

Reproducibility correlates with device noise parameters.

Method validated on superconducting transmon processor.

Abstract

The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.