Barber, B., Barnes, K.M., Bialas, T. et al. (10 more authors) (2025) A real-time, scalable, fast and resource-efficient decoder for a quantum computer. Nature Electronics, 8 (1). pp. 84-91. ISSN 2520-1131
Abstract
The development of quantum computers will require the careful management of the noise effects associated with qubit performance. However, the decoders responsible for diagnosing noise-induced computational errors must use resources efficiently to enable scaling to large qubit counts and cryogenic operation. They must also operate at speed, to avoid an exponential slowdown in the logical clock rate of the quantum computer. To overcome these challenges, we introduce the Collision Clustering decoder and demonstrate its implementation on field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) hardware. We simulate logical memory experiments using the leading quantum error correction scheme (the surface code) and demonstrate megahertz decoding speed—matching the requirements of fast-operating modalities such as superconducting qubits—up to an 881 qubit surface code with the FPGA and 1,057 qubit surface code with the ASIC. The ASIC design occupies 0.06 mm2 and consumes only 8 mW of power.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Nature Electronics is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Electrical and electronic engineering; 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 Jan 2025 12:42 |
Last Modified: | 12 Mar 2025 12:41 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1038/s41928-024-01319-5 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:221655 |