Local SVD preprocessing of BP log-likelihood vectors reduces BP-OSD complexity for distributed surface codes while roughly preserving logical accuracy in small-scale simulations.
Accelerating BP-based decoders for QLDPC Codes with Local Syndrome-Based Preprocessing
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abstract
Due to the high error rate of qubits, detecting and correcting errors is essential for achieving fault-tolerant quantum computing (FTQC). Quantum low-density parity-check (QLDPC) codes are one of the most promising quantum error correction (QEC) methods due to their high encoding rates. BP (Belief Propagation)-based decoders are widely used and highly competitive for QLDPC codes because BP offers inherent parallelism and strong scalability. However, BP-based decoders still suffer from high decoding latency, a large portion of which is spent in the iterative BP stage. In this paper, we propose a lightweight preprocessing step that utilizes local patterns in the syndrome to detect likely trivial error events and provide them as hints to BP-based decoders. These hints accelerate BP convergence and thereby reduce the overall decoding time. The proposed preprocessing step offers a broadly compatible approach to reducing the latency of BP-based QLDPC decodes. On the bivariate bicycle code $[[144,12,12]]$ at low physical error rates, our method achieves a $10\times$ speedup in decoding time for BP-OSD, and more than $2\times$ speedup for both BP-LSD and Relay-BP. Our method maintains the logical error rate when combined with BP-OSD and Relay-BP, while further achieving a significant reduction in logical error rate when combined with BP-LSD.
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quant-ph 1years
2026 1verdicts
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Parallel QEC Decoding Applied to Distributed Quantum Computing
Local SVD preprocessing of BP log-likelihood vectors reduces BP-OSD complexity for distributed surface codes while roughly preserving logical accuracy in small-scale simulations.