Quantum information needs to be protected by quantum error-correcting codes due to imperfect physical devices and operations. One would like to have an efficient and high-performance decoding procedure for the class of quantum stabilizer codes. A potential candidate is Pearl's belief propagation (BP), but its performance suffers from the many short cycles inherent in a quantum stabilizer code, especially highly-degenerate codes. A general impression exists that BP is not effective for topological codes. In this paper, we propose a decoding algorithm for quantum codes based on quaternary BP with additional memory effects (called MBP). This MBP is like a recursive neural network with inhibitions between neurons (edges with negative weights), which enhance the perception capability of a network. Moreover, MBP exploits the degeneracy of a quantum code so that the most probable error or its degenerate errors can be found with high probability. The decoding performance is significantly improved over the conventional BP for various quantum codes, including quantum bicycle, hypergraph-product, surface and toric codes. For MBP on the surface and toric codes over depolarizing errors, we observe error thresholds of 16% and 17.5%, respectively.
翻译:由于物理器件和操作不完美,量子信息需要由量子纠错码进行保护。对于量子稳定器码,我们希望拥有一种高效且高性能的解码过程。一个潜在的选择是Pearl的置信传播(BP),但是其性能受到量子稳定器码中存在的许多短周期的影响,特别是高度退化的码。一般认为BP对于拓扑码不利于有效率的解码。在本文中,我们提出了一种基于四元BP的量子码解码算法,并添加了附加的记忆效应(称为MBP)。这个MBP像具有神经元间抑制作用的递归神经网络(边具有负权重一样),它增强了网络的感知能力。此外,MBP利用了量子码的退化性质,以便最有可能的错误或其退化错误可以以高概率找到。对于包括量子自行车、超图积、表和托林码在内的各种量子码,解码性能都比传统BP显著提高。对于表和托林码上的MBP,其错误阈值分别为16%和17.5%。
Translated title: 量子码退化利用的置信传播解码优化
Translated abstract:
由于物理器件和操作不完美,量子信息需要由量子纠错码进行保护。对于量子稳定器码,我们希望拥有一种高效且高性能的解码过程。一个潜在的选择是Pearl的置信传播(BP),但是其性能受到量子稳定器码中存在的许多短周期的影响,特别是高度退化的码。一般认为BP对于拓扑码不利于有效率的解码。在本文中,我们提出了一种基于四元BP的量子码解码算法,并添加了附加的记忆效应(称为MBP)。这个MBP像具有神经元间抑制作用的递归神经网络(边具有负权重一样),它增强了网络的感知能力。此外,MBP利用了量子码的退化性质,以便最有可能的错误或其退化错误可以以高概率找到。对于包括量子自行车、超图积、表和托林码在内的各种量子码,解码性能都比传统BP显著提高。对于表和托林码上的MBP,其错误阈值分别为16%和17.5%。