Ali, H. orcid.org/0000-0002-7454-0910, Marques, J. orcid.org/0000-0001-9939-051X, Crawford, O. et al. (7 more authors) (2024) Reducing the error rate of a superconducting logical qubit using analog readout information. Physical Review Applied, 22 (4). 044031. ISSN 2331-7043
Abstract
Quantum error correction enables the preservation of logical qubits with a lower logical error rate than the physical error rate, with performance depending on the decoding method. Traditional decoding approaches rely on the binarization (“hardening”) of readout data, thereby ignoring valuable information embedded in the analog (“soft”) readout signal. We present experimental results showcasing the advantages of incorporating soft information into the decoding process of a distance-3 (d = 3) bit-flip surface code with flux-tunable transmons. We encode each of the 16 computational states that make up the logical state |0L , and protect them against bit-flip errors by performing repeated Z-basis stabilizer measurements. To infer the logical fidelity for the |0L state, we average across the 16 computational states and employ two decoding strategies: minimum-weight perfect matching and a recurrent neural network. Our results show a reduction of up to 6.8% in the extracted logical error rate with the use of soft information. Decoding with soft information is widely applicable, independent of the physical qubit platform, and could allow for shorter readout durations, further minimizing logical error rates. <jats:sec> <jats:title/> <jats:supplementary-material> <jats:permissions> <jats:copyright-statement>Published by the American Physical Society</jats:copyright-statement> <jats:copyright-year>2024</jats:copyright-year> </jats:permissions> </jats:supplementary-material> </jats:sec>
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024. Published by the American Physical Society under the terms of the Creative CommonsAttribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. https://creativecommons.org/licenses/by/4.0/ |
Keywords: | Artificial neural networks; Optoelectronics; Quantum circuits; Quantum error correction; Quantum information with solid state qubits |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Nov 2024 14:44 |
Last Modified: | 13 Nov 2024 14:44 |
Status: | Published |
Publisher: | American Physical Society (APS) |
Refereed: | Yes |
Identification Number: | 10.1103/physrevapplied.22.044031 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219554 |