论文标题
使用过度检查矩阵对量子LDPC代码的神经信念传播解码
Neural Belief Propagation Decoding of Quantum LDPC Codes Using Overcomplete Check Matrices
论文作者
论文摘要
最近在渐近构建良好的量子低密度奇偶校验检查（QLDPC）代码方面的成功使该代码成为量子计算中错误纠正方案的有前途的候选人。但是，由于其制革厂图中存在不可避免的短周期和特殊的退化现象，因此QLDPC代码的常规信念传播（BP）解码不会产生令人满意的性能。在这项工作中，我们建议基于基于冗余行的检查矩阵来解码QLDPC代码，这是由原始检查矩阵中行的线性组合生成的。这种方法在解码延迟的附加优势中可以显着改善解码性能。此外，我们提出了一种基于QLDPC代码的第四纪BP解码器的新型神经信念传播解码器，从而导致进一步解码性能改进。
The recent success in constructing asymptotically good quantum low-density parity-check (QLDPC) codes makes this family of codes a promising candidate for error-correcting schemes in quantum computing. However, conventional belief propagation (BP) decoding of QLDPC codes does not yield satisfying performance due to the presence of unavoidable short cycles in their Tanner graph and the special degeneracy phenomenon. In this work, we propose to decode QLDPC codes based on a check matrix with redundant rows, generated from linear combinations of the rows in the original check matrix. This approach yields a significant improvement in decoding performance with the additional advantage of very low decoding latency. Furthermore, we propose a novel neural belief propagation decoder based on the quaternary BP decoder of QLDPC codes which leads to further decoding performance improvements.
