论文标题
通过缩放表面代码逻辑量子量抑制量子错误
Suppressing quantum errors by scaling a surface code logical qubit
论文作者
论文摘要
实用的量子计算将需要远低于物理Qubits可实现的错误率。量子误差校正通过编码许多物理量子位的逻辑Qubits来提供与算法相关的错误率的途径，其中增加物理量子的数量可以增强对物理错误的保护。但是，引入更多量子位也增加了错误源的数量，因此错误的密度必须足够低，以使逻辑性能以随着代码大小的增加而改善。在这里，我们报告了跨多个代码尺寸的逻辑量子量表缩放的测量，并证明我们的超导Qubits系统具有足够的性能，可以克服增加量子数的额外错误。我们发现我们的距离-5表面代码逻辑Qubit适度胜过距离3逻辑Qubits的合奏，无论是在25个周期以上的逻辑错误概率和每个周期逻辑上的误差方面，均等（2.914 \％\％\％\ pm 0.016 \％$ $ 3.028 \％\％\％\％\％\％\％\％\％\％\％\％\％\％\％\％\％\％）。为了调查损坏，低概率错误源，我们运行距离25的重复代码，并观察$ 1.7 \ times10^{ - 6} $每回合逻辑误差，由一个高能事件设置（$ 1.6 \ times10 \ times10^{ - 7} $，在排除此事件时）。我们能够准确地对我们的实验进行建模，从该模型中，我们可以提取错误预算，以突出未来系统面临的最大挑战。这些结果标志着第一个实验证明，其中量子误差校正开始随着量子数的增加而开始提高性能，从而阐明了达到计算所需的逻辑错误率的路径。
Practical quantum computing will require error rates that are well below what is achievable with physical qubits. Quantum error correction offers a path to algorithmically-relevant error rates by encoding logical qubits within many physical qubits, where increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low in order for logical performance to improve with increasing code size. Here, we report the measurement of logical qubit performance scaling across multiple code sizes, and demonstrate that our system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number. We find our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3 logical qubits on average, both in terms of logical error probability over 25 cycles and logical error per cycle ($2.914\%\pm 0.016\%$ compared to $3.028\%\pm 0.023\%$). To investigate damaging, low-probability error sources, we run a distance-25 repetition code and observe a $1.7\times10^{-6}$ logical error per round floor set by a single high-energy event ($1.6\times10^{-7}$ when excluding this event). We are able to accurately model our experiment, and from this model we can extract error budgets that highlight the biggest challenges for future systems. These results mark the first experimental demonstration where quantum error correction begins to improve performance with increasing qubit number, illuminating the path to reaching the logical error rates required for computation.
