Feed-Forward Probabilistic Error Cancellation with Noisy Recovery Gates

TL;DR

This paper introduces Feed-Forward PEC, an improved probabilistic error cancellation method that cancels noise from recovery gates, resulting in more accurate expectation value estimates in quantum computing.

Contribution

The paper proposes FFPEC, a novel PEC variant that accounts for noise in recovery gates, providing unbiased and more precise expectation value estimations.

Findings

FFPEC yields more accurate expectation values than conventional PEC.

Analytical evaluations confirm unbiasedness of FFPEC.

Numerical experiments support improved performance of FFPEC.

Abstract

Probabilistic Error Cancellation (PEC) aims to improve the accuracy of expectation values for observables. This is accomplished using the probabilistic insertion of recovery gates, which correspond to the inverse of errors. However, the inserted recovery gates also induce errors. Thus, it is difficult to obtain accurate expectation values with PEC since the estimator of PEC has a bias due to noise induced by recovery gates. To address this challenge, we propose an improved version of PEC that considers the noise resulting from gate insertion, called Feed-Forward PEC (FFPEC). FFPEC provides an unbiased estimator of expectation values by cancelling out the noise induced by recovery gates. We demonstrate that FFPEC yields more accurate expectation values compared to the conventional PEC method through analytical evaluations. Numerical experiments are used to evaluate analytical results.