The error threshold of a one-parameter family of quantum channels is defined as the largest noise level such that the quantum capacity of the channel remains positive. This in turn guarantees the existence of a quantum error correction code for noise modeled by that channel. Discretizing the single-qubit errors leads to the important family of Pauli quantum channels; curiously, multipartite entangled states can increase the threshold of these channels beyond the so-called hashing bound, an effect termed superadditivity of coherent information. In this work, we divide the simplex of Pauli channels into one-parameter families and compute numerical lower bounds on their error thresholds. We find substantial increases of error thresholds relative to the hashing bound for large regions in the Pauli simplex corresponding to biased noise, which is a realistic noise model in promising quantum computing architectures. The error thresholds are computed on the family of graph states, a special type of stabilizer state. In order to determine the coherent information of a graph state, we devise an algorithm that exploits the symmetries of the underlying graph, resulting in a substantial computational speed-up. This algorithm uses tools from computational group theory and allows us to consider symmetric graph states on a large number of vertices. Our algorithm works particularly well for repetition codes and concatenated repetition codes (or cat codes), for which our results provide the first comprehensive study of superadditivity for arbitrary Pauli channels. In addition, we identify a novel family of quantum codes based on tree graphs. The error thresholds of these tree graph states outperform repetition and cat codes in large regions of the Pauli simplex, and hence form a new code family with desirable error correction properties.
翻译:量子频道一参数系列的错误阈值被定义为最大噪声水平, 使频道的量子能力保持正数。 这反过来保证了该频道所建噪音的量子错误校正代码的存在。 分解单位差错导致保利量频道的重要家族; 奇怪的是, 多方纠结状态可以提高这些频道的阈值, 超越所谓的“ 散列约束 ”, 一种被称为一致性信息的超增加性效应。 在这项工作中, 我们将保利频道的简单值错误分解成一个参数家族, 并计算出其错误值值的任意度阈值。 我们发现, 相对于保利简单线大区域的误差值校正代码, 这是在有希望的量子计算结构中现实的噪音模型模型。 在图形状态组中计算错误阈值, 一种叫做“ 稳定状态 ” 。 为了确定一个图形状态的一致信息, 我们设计一种算法, 利用基础图表的精确度的精确度的精确度值, 并计算其直径直径直值值值的直径直径直径值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值值比值比值比值比值值值值值比值比值值值值值值比值比值比值比值比值比值比值比值比值, 。, 。,,,,,,,,,,,,,,,, 也就是为我们算算算算算算算算算算算算算算法算算算算算法,,, 。算算算算算算算算算算法工具,, 算算算算算算算法系计算法,, 算算算算算算算算法,, 算算算算算算算算算