稀疏量子码的增强反馈迭代译码
Enhanced Feedback Iterative Decoding of Sparse Quantum Codes
摘要：
稀疏量子码的译码可以通过基于征兆的置信传播（BP）算法来实现，本文通过对标准BP算法提出一种新的反馈调整策略，对该译码方案进行了改进。在我们的反馈过程中，我们利用了来自稳定器的许多信息，不仅是综合征，而且还有对代码和信道模型的单个量子位的受挫检查的值。此外，我们表明，我们的解码算法是优于信仰传播算法，只使用在反馈过程中的所有情况下的去极化信道的综合征。我们的算法不增加测量开销相比，以前的方法，因为额外的信息来自免费的必要的稳定器测量。
英文摘要：
Decoding sparse quantum codes can be accomplished by syndrome-based decoding using a belief propagation (BP) algorithm.We significantly improve this decoding scheme by developing a new feedback adjustment strategy for the standard BP algorithm. In our feedback procedure, we exploit much of the information from stabilizers, not just the syndrome but also the values of the frustrated checks on individual qubits of the code and the channel model. Furthermore we show that our decoding algorithm is superior to belief propagation algorithms using only the syndrome in the feedback procedure for all cases of the depolarizing channel. Our algorithm does not increase the measurement overhead compared to the previous method, as the extra information comes for free from the requisite stabilizer measurements.
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