Improved quantum error correction using soft information
Improved quantum error correction using soft information
复制标题
使用软信息改进量子纠错
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Nicolas Delfosse
中科院分区：
文献类型：
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作者：
C. Pattison;M. Beverland;M. Silva;Nicolas Delfosse
量子误差校正中测量噪声的典型模型是随机翻转二值测量结果。在实验中，测量产生更丰富的信息——例如，连续的电流值，离散的光子计数——然后通过丢弃一些信息将其映射为二进制结果。在这项工作中，我们考虑了将所有这些更丰富的信息（通常称为软信息）纳入量子纠错码解码的方法，特别是表面码。我们描述了如何修改最小权重完美匹配和联合查找解码器以利用软信息，并演示了这些软解码器优于只能访问二进制测量结果的标准（硬）解码器。此外，我们观察到，对于高斯软测量结果的现象噪声，软解码器的阈值比任何硬解码器高25%。我们还引入了一种带有振幅阻尼的软测量误差模型，其中测量时间导致测量分辨率和量子比特的额外干扰之间的权衡。在该模型下，我们观察到表面码的性能对测量时间的选择非常敏感——对于距离为19的表面码，测量时间增加5倍会导致逻辑错误率增加1000倍。此外，最小化物理错误率的测量时间与最小化逻辑性能的测量时间是不同的，这表明联合优化物理层和量子纠错层的好处。
The typical model for measurement noise in quantum error correction is to randomly flip the binary measurement outcome. In experiments, measurements yield much richer information - e.g., continuous current values, discrete photon counts - which is then mapped into binary outcomes by discarding some of this information. In this work, we consider methods to incorporate all of this richer information, typically called soft information, into the decoding of quantum error correction codes, and in particular the surface code. We describe how to modify both the Minimum Weight Perfect Matching and Union-Find decoders to leverage soft information, and demonstrate these soft decoders outperform the standard (hard) decoders that can only access the binary measurement outcomes. Moreover, we observe that the soft decoder achieves a threshold 25\% higher than any hard decoder for phenomenological noise with Gaussian soft measurement outcomes. We also introduce a soft measurement error model with amplitude damping, in which measurement time leads to a trade-off between measurement resolution and additional disturbance of the qubits. Under this model we observe that the performance of the surface code is very sensitive to the choice of the measurement time - for a distance-19 surface code, a five-fold increase in measurement time can lead to a thousand-fold increase in logical error rate. Moreover, the measurement time that minimizes the physical error rate is distinct from the one that minimizes the logical performance, pointing to the benefits of jointly optimizing the physical and quantum error correction layers.
影响因子：
2.9
作者：
Christophe Vuillot;H. Asasi;Yang Wang;L. Pryadko;B. Terhal
通讯作者：
Christophe Vuillot;H. Asasi;Yang Wang;L. Pryadko;B. Terhal
toric 码上的容错加权并查解码
影响因子：
2.9
作者：
Huang, Shilin;Newman, Michael;Brown, Kenneth R.
通讯作者：
Brown, Kenneth R.
影响因子：
6.7
作者：
Breuckmann, Nikolas P.;Vuillot, Christophe;Terhal, Barbara M.
通讯作者：
Terhal, Barbara M.