针对X-Z型Pauli信道的量子稀疏图码的反馈式和积译码算法

本文针对X-Z型Pauli量子信道构建了一个量子稀疏图码的反馈式和积译码算法.相比较之前的基本和积算法,该反馈式译码策略利用了错误图样的比较, 稳定子中相关元素的值,特别的还根据信道的特征充分考虑了各变量所占错误的比重,并由此来调整信息节点的概率分布.该反馈式策略起到了经典译码中的软判决技术的作用,不但克服了对称简并问题带来的不利影响,更重要的是还给译码器提供了更多的有效信息,从而大大提高了译码器的纠错译码能力.另外,反馈式译码和积译码算法是基于GF(4)的,大大拓展了和积译码器关于量子译码 关键词： 量子稀疏图码 和积算法 量子纠错码 量子信息

Feedback sum-product decoding of sparse quantum codes for X-Z Pauli channels

In this paper, a feedback sum-product decoding algorithm of sparse quantum codes for X-Z Pauli channels is developed. Compared with the previous decoding algorithm, our feedback strategy exploits not just the syndrome but also the values of the frustrated checks on individual qubits of the code and the character of the channel model with the portion of each error to adjust the probability distribution of information nodes. Due to the smart adjustment, our decoding algorithm, on one hand, can break the symmetric degeneracy, and on the other hand, can feed back more useful information to the SPA decoder to help the decoder determine a valid output, thereby significantly improving the decoding ability of the decoder. Moreover, our algorithm, which is based on GF(4), overcomes the limitation caused by decoding in GF(2). Finally, we want to point out that, our method does not increase the measurement overhead in comparison wioth the previous methods, as the extra information comes for free from the requisite stabilizer measurement.