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Paper 1
Efficient Approximate Degenerate Ordered Statistics Decoding for Quantum Codes via Reliable Subset Reduction
Ching-Feng Kung, Kao-Yueh Kuo, Ching-Yi Lai
- Year
- 2024
- Journal
- arXiv preprint
- DOI
- arXiv:2412.21118
- arXiv
- 2412.21118
Efficient and scalable decoding of quantum codes is essential for high-performance quantum error correction. In this work, we introduce Reliable Subset Reduction (RSR), a reliability-driven preprocessing framework that leverages belief propagation (BP) statistics to identify and remove highly reliable qubits, substantially reducing the effective problem size. Additionally, we identify a degeneracy condition that allows high-order OSD to be simplified to order-0 OSD. By integrating these techniques, we present an ADOSD algorithm that significantly improves OSD efficiency. Our BP+RSR+ADOSD framework extends naturally to circuit-level noise and can handle large-scale codes with more than $10^4$ error variables. Through extensive simulations, we demonstrate improved performance over MWPM and Localized Statistics Decoding for a variety of CSS and non-CSS codes under the code-capacity noise model, and for rotated surface codes under realistic circuit-level noise. At low physical error rates, RSR reduces the effective problem size to less than 5\%, enabling higher-order OSD with accelerated runtime. These results highlight the practical efficiency and broad applicability of the BP+ADOSD framework for both theoretical and realistic quantum error correction scenarios.
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Demonstration of high-fidelity entangled logical qubits using transmons.
Vezvaee A, Tripathi V, Morford-Oberst M, Butt F, Kasatkin V, Lidar DA.
- Year
- 2026
- Journal
- Nat Commun
- DOI
- 10.1038/s41467-026-70011-3
- arXiv
- -
No abstract.
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