Rethink the Role of Neural Decoders in Quantum Error Correction
Quantum error correction (QEC) is essential for enabling quantum advantages, with decoding as a central algorithmic primitive. Owing to its importance and intrinsic difficulty, substantial effort has been made to QEC decoder design, among which neural decoders have recently emerged as a promising data-driven paradigm. Despite this progress, practical deployment remains hindered by a fundamental accuracy-latency tradeoff, often on the microsecond timescale. To address this challenge, here we revisit neural decoders for surface-code decoding under explicit accuracy-latency constraints, considering code distances up to d=9 (161 physical qubits). We unify and redesign representative neural de...
| Authors | Ge Yan, Shanchuan Li, Yuxuan Du |
|---|---|
| Primary category | quant-ph |
| Published | 12 May 2026 |
| Last updated at source | 12 May 2026 |
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