量子稀疏图码的译码可以由基于错误图样的和积译码算法来实现.本文在此基础上构建了一个新的反馈式迭代译码算法.其反馈策略不仅仅重新利用了错误图样,而且还利用了稳定子上相应元素的值和信道的错误模型.由此,本方法一方面可以克服传统的量子和积译码算法中遇到的所谓对称简并错误,另一方面还能反馈更多的有用信息到译码器中,帮助其产生有效的译码结果,大大提高译码器的译码能力.另外,本算法并没有增加量子测量的复杂度,而是对测量中所能获得的信息的更充分利用.
Decoding sparse quantum codes can be accomplished by syndrome-based decoding through using the sum-product algorithm (SPA).We significantly improve this decoding scheme by developing a new feedback adjustment strategy for the standard SPA.In our feedback strategy,we exploit not only the syndrome but also the values of the frustrated checks on individual qubits of the code and the channel model.Consequently,our decoding algorithm,on the 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 does not increase the measurement complexity compared with the previous method,but takes full advantage of the measured information.