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This research identifies a specific failure mode in linear programming decoders for quantum LDPC codes, where constant-weight errors produce ambiguous fractional solutions that standard rounding cannot resolve. By integrating ordered statistics decoding (OSD) as a post-processing step, the authors demonstrate that these augmented LP decoders outperform belief propagation for intermediate code sizes up to hundreds of qubits. These findings provide a practical pathway to improving fault-tolerant quantum computation by leveraging optimization algorithms with targeted error-correction enhancements.
Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes
arXiv:2508.04769v2 Announce Type: replace Abstract: Decoding quantum error-correcting codes is a key challenge in enabling fault-tolerant quantum computation. In the classical setting, linear programming (LP) decoders offer provable performance guarantees and can leverage fast practical optimization algorithms. Although LP decoders have been proposed for quantum codes, their performance and limitations remain relatively underexplored. In this work, we uncover a key limitation of LP decoding for quantum low-density parity-check (LDPC) codes: certain constant-weight error patterns lead to ambiguous fractional solutions that cannot be resolved through independent rounding. To address this issue, we incorporate a post-processing technique known as ordered statistics decoding (OSD), which significantly enhances LP decoding performance in practice. Our results show that LP decoding, when augmented with OSD, can outperform belief propagation with the same post-processing for intermediate code sizes of up to hundreds of qubits. These findings suggest that LP-based decoders, equipped with effective post-processing, offer a promising approach for decoding near-term quantum LDPC codes.
Abstract:Decoding quantum error-correcting codes is a key challenge in enabling fault-tolerant quantum computation. In the classical setting, linear programming (LP) decoders offer provable performance guarantees and can leverage fast practical optimization algorithms. Although LP decoders have been proposed for quantum codes, their performance and limitations remain relatively underexplored. In this work, we uncover a key limitation of LP decoding for quantum low-density parity-check (LDPC) codes: certain constant-weight error patterns lead to ambiguous fractional solutions that cannot be resolved through independent rounding. To address this issue, we incorporate a post-processing technique known as ordered statistics decoding (OSD), which significantly enhances LP decoding performance in practice. Our results show that LP decoding, when augmented with OSD, can outperform belief propagation with the same post-processing for intermediate code sizes of up to hundreds of qubits. These findings suggest that LP-based decoders, equipped with effective post-processing, offer a promising approach for decoding near-term quantum LDPC codes.
Quantum Physics (quant-ph); Information Theory (cs.IT)
arXiv:2508.04769 [quant-ph]
(or arXiv:2508.04769v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2508.04769 Focus to learn more arXiv-issued DOI via DataCite
IEEE Trans. Inf. Theory. 72, 10 (2026)
https://doi.org/10.1109/TIT.2026.3715538 Focus to learn more DOI(s) linking to related resources
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