Local clustering decoder as a fast and adaptive hardware decoder for the surface code

To avoid prohibitive overheads in performing fault-tolerant quantum computation, the decoding problem needs to be solved accurately and at speeds sufficient for fast feedback. Existing decoding systems fail to satisfy both of these requirements, meaning they either slow down the quantum computer or reduce the number of operations that can be performed before the quantum information is corrupted. We introduce the Local Clustering Decoder as a solution that simultaneously achieves the accuracy and speed requirements of a real-time decoding system. Our decoder is implemented on FPGAs and exploits hardware parallelism to keep pace with the fastest qubit types. Further, it comprises an adaptivity engine that allows the decoder to update itself in real-time in response to control signals, such as heralded leakage events. Under a realistic circuit-level noise model where leakage is a dominant error source, our decoder enables one million error-free quantum operations with 4x fewer physical qubits when compared to standard non-adaptive decoding. This is achieved whilst decoding in under 1 μs per round with modest FPGA resources, demonstrating that high-accuracy real-time decoding is possible, and reducing the qubit counts required for large-scale fault-tolerant quantum computation.

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Publication Details

Journal
Nature Communications
Published
2025-12-17
DOI
https://doi.org/10.1038/s41467-025-66773-x
Citations
3
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
7.44
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article

Local clustering decoder as a fast and adaptive hardware decoder for the surface code

György Pál Gehér, Matthew P. Stafford, Joan Camps, Canberk Topal et al.
3 citations
Nature Communications
Quantum Computing Algorithms and Architecture
7.44
article

Local clustering decoder as a fast and adaptive hardware decoder for the surface code

György Pál Gehér, Matthew P. Stafford, Joan Camps, Canberk Topal, Abbas B. Ziad, Mark L. Turner, Ankit Zalawadiya
article en
3 citations

Abstract

To avoid prohibitive overheads in performing fault-tolerant quantum computation, the decoding problem needs to be solved accurately and at speeds sufficient for fast feedback. Existing decoding systems fail to satisfy both of these requirements, meaning they either slow down the quantum computer or reduce the number of operations that can be performed before the quantum information is corrupted. We introduce the Local Clustering Decoder as a solution that simultaneously achieves the accuracy and speed requirements of a real-time decoding system. Our decoder is implemented on FPGAs and exploits hardware parallelism to keep pace with the fastest qubit types. Further, it comprises an adaptivity engine that allows the decoder to update itself in real-time in response to control signals, such as heralded leakage events. Under a realistic circuit-level noise model where leakage is a dominant error source, our decoder enables one million error-free quantum operations with 4x fewer physical qubits when compared to standard non-adaptive decoding. This is achieved whilst decoding in under 1 μs per round with modest FPGA resources, demonstrating that high-accuracy real-time decoding is possible, and reducing the qubit counts required for large-scale fault-tolerant quantum computation.

Nature CommunicationsVol. 16(1)
University of Bristol (GB), Riverlane (United Kingdom) (GB), Bristol Robotics Laboratory (GB)
Openalex Percentile: Top 3%
Quantum Computing Algorithms and Architecture
7.44
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