Efficient noise mitigation technique for quantum computing

Quantum computers have enabled solving problems beyond the current machines' capabilities. However, this requires handling noise arising from unwanted interactions in these systems. Several protocols have been proposed to address efficient and accurate quantum noise profiling and mitigation. In...

Full description

Saved in:
Bibliographic Details
Published inScientific reports Vol. 13; no. 1; p. 3912
Main Authors Shaib, Ali, Naim, Mohamad Hussein, Fouda, Mohammed E, Kanj, Rouwaida, Kurdahi, Fadi
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 08.03.2023
Nature Publishing Group UK
Nature Portfolio
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Quantum computers have enabled solving problems beyond the current machines' capabilities. However, this requires handling noise arising from unwanted interactions in these systems. Several protocols have been proposed to address efficient and accurate quantum noise profiling and mitigation. In this work, we propose a novel protocol that efficiently estimates the average output of a noisy quantum device to be used for quantum noise mitigation. The multi-qubit system average behavior is approximated as a special form of a Pauli Channel where Clifford gates are used to estimate the average output for circuits of different depths. The characterized Pauli channel error rates, and state preparation and measurement errors are then used to construct the outputs for different depths thereby eliminating the need for large simulations and enabling efficient mitigation. We demonstrate the efficiency of the proposed protocol on four IBM Q 5-qubit quantum devices. Our method demonstrates improved accuracy with efficient noise characterization. We report up to 88% and 69% improvement for the proposed approach compared to the unmitigated, and pure measurement error mitigation approaches, respectively.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-30510-5