Characterizing large-scale quantum computers via cycle benchmarking

authored by: Alexander Erhard, Joel J. Wallman, Lukas Postler, Michael Meth, Roman Stricker, Esteban A. Martinez, Philipp Schindler, Thomas Monz, Joseph Emerson, Rainer Blatt
Abstract: Quantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits, and total process fidelities for multi-qubit entangling gates ranging from 99.6 (1) % for 2 qubits to 86 (2) % for 10 qubits. Furthermore, cycle benchmarking data validates that the error rate per single-qubit gate and per two-qubit coupling does not increase with increasing system size.
External Organisation(s): University of Innsbruck
University of Waterloo
Quantum Benchmark Inc.
University of Copenhagen
Alpine Quantum Technologies GmbH
Austrian Academy of Sciences
Type: Article
Journal: Nature Communications
Volume: 10
ISSN: 2041-1723
Publication date: 01.12.2019
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Chemistry(all), Biochemistry, Genetics and Molecular Biology(all), Physics and Astronomy(all)
Electronic version(s): https://doi.org/10.1038/s41467-019-13068-7 (Access: Open)

BibTeX

@article{50240ae80fee4a0d8b475235dd865dca,
title = "Characterizing large-scale quantum computers via cycle benchmarking",
abstract = "Quantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits, and total process fidelities for multi-qubit entangling gates ranging from 99.6 (1) % for 2 qubits to 86 (2) % for 10 qubits. Furthermore, cycle benchmarking data validates that the error rate per single-qubit gate and per two-qubit coupling does not increase with increasing system size.",
author = "Alexander Erhard and Wallman, {Joel J.} and Lukas Postler and Michael Meth and Roman Stricker and Martinez, {Esteban A.} and Philipp Schindler and Thomas Monz and Joseph Emerson and Rainer Blatt",
note = "Funding information: We gratefully acknowledge support by the Austrian Science Fund (FWF), through the SFB Fo-QuS (FWF Project No. F4002-N16), as well as the Institut f{\"u}r Quante-ninformation GmbH. In addition, we acknowledge support from the Austrian Research Promotion Agency (FFG) contract 872766. This research was funded by the Office of the Director of National Intelligence (ODNI) and Intelligence Advanced Research Projects Activity (IARPA) through the Army Research Office grant W911NF-16-1-0070. All statements of fact, opinions, or conclusions contained herein are those of the authors and should not be construed as representing the official views or policies of IARPA, the ODNI, or the U.S. Government. We also acknowledge support by U.S. A.R.O. through grant W911NF-14-1-0103. This research was undertaken thanks in part to funding from TQT, CIFAR, the Government of Ontario, and the Government of Canada through CFREF, NSERC, and Industry Canada. We want to thank the anonymous referees for their valuable remarks.",
year = "2019",
month = dec,
day = "1",
doi = "10.1038/s41467-019-13068-7",
language = "English",
volume = "10",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}