Scalable quantum processor noise characterization

Kathleen E. Hamilton, Tyler Kharazi, Titus Morris, Alexander J. McCaskey, Ryan S. Bennink, Raphael C. Pooser

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

Measurement fidelity matrices (MFMs) (also called error kernels) are a natural way to characterize state preparation and measurement errors in near-term quantum hardware. They can be employed in post processing to mitigate errors and substantially increase the effective accuracy of quantum hardware. However, the feasibility of using MFMs is currently limited as the experimental cost of determining the MFM for a device grows exponentially with the number of qubits. In this work we present a scalable way to construct approximate MFMs for many-qubit devices based on cumulant expansions. Our method can also be used to characterize various types of correlation error.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Quantum Computing and Engineering, QCE 2020
EditorsHausi A. Muller, Greg Byrd, Candace Culhane, Erik DeBenedictis, Travis Humble
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages430-440
Number of pages11
ISBN (Electronic)9781728189697
DOIs
StatePublished - Oct 2020
Event2020 IEEE International Conference on Quantum Computing and Engineering, QCE 2020 - Denver, United States
Duration: Oct 12 2020Oct 16 2020

Publication series

NameProceedings - IEEE International Conference on Quantum Computing and Engineering, QCE 2020

Conference

Conference2020 IEEE International Conference on Quantum Computing and Engineering, QCE 2020
Country/TerritoryUnited States
CityDenver
Period10/12/2010/16/20

Funding

This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. The authors would like to thank Vicente Leyton-Ortega for insightful discussions about noise characterization and error mitigation. The authors would like to thank IBM for providing information about the IBM Q system This work was supported as part of the ASCR Quantum Testbed Pathfinder Program at Oak Ridge National Laboratory under FWP #ERKJ332. This research used quantum computing system resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. Oak Ridge National Laboratory manages access to the IBM Q System as part of the IBM Q Network.

Keywords

  • NISQ computing
  • error mitigation
  • noise characterization
  • quantum computing

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