南京理工大学学报（自然科学版）2026，Vol.50Issue(2)：220-229,10.DOI:10.14177/j.cnki.32-1397n.2026.50.02.011
神经网络辅助的非二进制量子LDPC码置信传播译码研究
Neural network-assisted belief propagation decoding of quantum LDPC codes over non-binary fields
摘要
Abstract
Belief propagation(BP)algorithm has made many advances in decoding quantum low-density parity check(LDPC)codes.A new recurrent neural network-based belief propagation(RNBP)decoding scheme is proposed for the problems of quantum short-cycle and error degeneracy under non-binary conditions.Specifically,in the loss function section,RNBP combines the cross-entropy loss applicable to classical error patterns,with the logical loss applicable to quantum error patterns,and sets a hyperparameter for this loss function to better accomplish this multi-objective task.Simulation results show that the RNBP decoding scheme mitigates the quantum short-cycle problem by detecting degeneracy errors with a high probability.On the standard CSS form quantum codes tested in this article,the RNBP scheme decodes better than the conventional BP,suppressing the logic error rate from 10-2 to between 10-3 and 10-4.The RNBP also considers asymmetric channel decoding,which also performs better than the conventional BP.On the XZZX form twisted quantum codes,the logic error rate achievable by the conventional BP is suppressed from 10-2 to around 10-3.关键词
量子LDPC码/神经网络译码/量子简并/非对称信道Key words
quantum LDPC codes/neural network decoding/quantum degeneracy/asymmetric channel分类
信息技术与安全科学引用本文复制引用
张千辉,樊继豪..神经网络辅助的非二进制量子LDPC码置信传播译码研究[J].南京理工大学学报（自然科学版）,2026,50(2):220-229,10.基金项目
国家重点研发计划(2022YFB3103802) （2022YFB3103802）
国家自然科学基金(62371240 （）
61802175) （）
中央高校基本科研业务费专项资金(30923011014) （30923011014）
