Benchmarking noise extrapolation with the OpenPulse control framework

J. W.O. Garmon, R. C. Pooser, E. F. Dumitrescu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Distilling precise estimates from noisy intermediate scale quantum (NISQ) data has recently attracted considerable attention Kandala, Nature (London) 567, 491 (2019)NATUAS0028-083610.1038/s41586-019-1040-7. In order to augment digital qubit metrics, such as gate fidelity, we discuss analog error mitigability, i.e., the ability to accurately distill precise observable estimates, as a hybrid quantum classical computing benchmarking task. Specifically, using Rabi oscillations as a test program, we characterize single qubit error rates on IBM's Poughkeepsie superconducting quantum hardware, incorporate control-mediated noise dependence into a generalized rescaling protocol, and analyze how noise characteristics influence Richardson extrapolation-based error mitigation. Our results identify regions in the space of Hamiltonian control fields and circuit depth which are most amenable to reliable noise extrapolation, as well as shed light on how low-level hardware characterization can be used as a predictive tool for uncertainty quantification in error-mitigated NISQ computations.

Original languageEnglish
Article number042308
JournalPhysical Review A
Volume101
Issue number4
DOIs
StatePublished - Apr 2020

Funding

E.F.D. and R.C.P. acknowledge U.S. Department of Energy ASCR funding under the Quantum Testbed Pathfinder program, FWP Grant No. ERKJ332. J.W.O.G. was supported by the U.S. Department of Energy Science Undergraduate Laboratory Internship (SULI) program. This research used resources of the Oak Ridge Leadership Computing Facility, which is a U.S. Department of Energy Office of Science User Facility supported under Contract No. DE-AC05-00OR22725. Oak Ridge National Laboratory manages access to the IBM Q System as part of the IBM Q Network. The views expressed are those of the authors and do not reflect the official policy or position of IBM or the IBM Q team.

FundersFunder number
FWPERKJ332
SULI
U.S. Department of Energy Science Undergraduate Laboratory Internship
U.S. Department of EnergyDE-AC05-00OR22725

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