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)