Cited by 156Quantum Computing Algorithms and ArchitectureQuantum Information and CryptographyQuantum many-body systems

Three-Qubit Randomized Benchmarking

Open access
McKay, David C., Sheldon, Sarah, Smolin, John A., Chow, Jerry M., Gambetta, Jay M.·2019·Physical Review Letters

Abstract

As quantum circuits increase in size, it is critical to establish scalable multiqubit fidelity metrics. Here we investigate, for the first time, three-qubit randomized benchmarking (RB) on a quantum device consisting of three fixed-frequency transmon qubits with pairwise microwave-activated interactions (cross-resonance). We measure a three-qubit error per Clifford of 0.106 for all-to-all gate connectivity and 0.207 for linear gate connectivity. Furthermore, by introducing mixed dimensionality simultaneous RB-simultaneous one- and two-qubit RB-we show that the three-qubit errors can be predicted from the one- and two-qubit errors. However, by introducing certain coherent errors to the gates, we can increase the three-qubit error to 0.302, an increase that is not predicted by a proportionate increase in the one- and two-qubit errors from simultaneous RB. This demonstrates the importance of multiqubit metrics, such as three-qubit RB, on evaluating overall device performance.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1103/physrevlett.122.200502

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Randomized benchmarking, state and process tomography, and gateset tomography fail to account for errors arising from interactions with spectator qubits.

    “Methods such as randomized benchmarking [5], state and process tomography [6], and gateset tomography [7] are valued for measuring the performance of operations on a few qubits, yet they fail to account for errors arising from interactions with spectator qubits [8, 9].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [36]Joel J. Wallman, 'Randomized benchmarking with gatedependent noise,' (2017), arxiv:1703.09835. · arXiv

Cited by

Sorted by citations

Authors
McKay, D. C., Sheldon, S., Smolin, J. A., Chow, J. M., & Gambetta, J. M.
Affiliations
IBM Research - Thomas J. Watson Research Center (US)
Venue
Physical Review Letters
Published
2019-05-23
Volume
122
Issue
20
Pages
200502-200502
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W2776564547
Cited by
156
References
41
Citations by year
2026: 12 · 2025: 17 · 2024: 13 · 2023: 22 · 2022: 23 · 2021: 37 · 2020: 20 · 2019: 12
FWCI
10.61
Type
journal article
Language
en
Open access
Locations
  • Physical Review Letters (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
Army Research Office (W911NF-14-1-0124)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
Keywords
transmon qubits, cross-resonance gate, coherent errors

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review