mlsanityData to 7 Oct 2026

Efficient and Universal Neural-Network Decoder for Stabilizer-Based Quantum Error Correction

arXiv 2502.19971 ↗First posted 27 Feb 2025quant-ph cs.AIcited by 6

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Abstract (arXiv)

Scaling quantum computing to practical applications necessitates reliable quantum error correction. Although numerous correction codes have been proposed, the overall correction efficiency critically limited by the decode algorithms. We introduce GraphQEC, a code-agnostic decoder leveraging machine-learning on the graph structure of stabilizer codes with linear time complexity. GraphQEC demonstrates unprecedented accuracy and efficiency across all tested code families, including surface codes, color codes, and quantum low-density parity-check (QLDPC) codes. For instance, on a distance-12 QLDPC code, GraphQEC achieves a logical error rate of 9.55 × 10-5, an 18-fold improvement over the previous best specialized decoder's 1.74 × 10-3 under p=0.005 physical error rates, while maintaining 157μs/cycle decoding speed. Our approach represents the first universal solution for real-time quantum error correction across arbitrary stabilizer codes.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 11 of its 57 references that are in the map. First posted on arXiv 27 Feb 2025.

Builds on

11 of 57 references.

References · 11

  1. 2017Attention Is All You Needcited by 59,932
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  3. 2019Root Mean Square Layer Normalizationcited by 1,425
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  8. 2023Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Networkcited by 40
  9. 2018Deep neural decoders for near term fault-tolerant experimentscited by 14
  10. 2018Advantages of versatile neural-network decoding for topological codescited by 9
  11. 2023qecGPT: decoding Quantum Error-correcting Codes with Generative Pre-trained Transformerscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.

  1. 2025A scalable and real-time neural decoder for topological quantum codescited by 8
  2. 2026Learning to Decode in Parallel: Self-Coordinating Neural Network for Real-Time Quantum Error Correctioncited by 2
  3. 2026Maximum Likelihood Decoding of Quantum Error Correction Codescited by 1
  4. 2026Efficient foundation decoders for fault-tolerant quantum computingcited by 1
  5. 2025Data-Driven Learnability Transition of Measurement-Induced Entanglementcited by 0
  6. 2026Machine Learning Approaches to Decoding Topological Quantum Codescited by 0