Contemporary methods for benchmarking noisy quantum processors typically measure average error rates or process infidelities. However, thresholds for fault-tolerant quantum error correction are given in terms of worst-case error rates—defined via the diamond norm—which can differ from average error rates by orders of magnitude. One method for resolving this discrepancy is to randomize the physical implementation of quantum gates, using techniques like randomized compiling (RC). In this work, we use gate set tomography to perform precision characterization of a set of two-qubit logic gates to study RC on a superconducting quantum processor. We find that, under RC, gate errors are accurately described by a stochastic Pauli noise model without coherent errors, and that spatially correlated coherent errors and non-Markovian errors are strongly suppressed. We further show that the average and worst-case error rates are equal for randomly compiled gates, and measure a maximum worst-case error of 0.0197(3) for our gate set. Our results show that randomized benchmarks are a viable route to both verifying that a quantum processor’s error rates are below a fault-tolerance threshold, and to bounding the failure rates of near-term algorithms, if—and only if—gates are implemented via randomization methods which tailor noise.

现代用于对噪声量子处理器进行基准测试的方法通常会测量平均错误率或过程不真实性。然而，容错量子纠错的阈值是根据最坏情况错误率（通过钻石范数定义）给出的，这可能与平均错误率有几个数量级的差异。解决这种差异的一种方法是使用随机编译 (RC) 等技术来随机化量子门的物理实现。在这项工作中，我们使用门组层析成像技术对一组双量子位逻辑门进行精确表征，以研究超导量子处理器上的 RC。我们发现，在 RC 下，门误差可以通过随机泡利噪声模型准确描述，而没有相干误差，并且空间相关相干误差和非马尔可夫误差被强烈抑制。我们进一步表明，随机编译门的平均错误率和最坏情况错误率是相等的，并测量我们的门集的最大最坏情况错误为 0.0197(3)。我们的结果表明，当且仅当通过随机化实现门时，随机基准测试是验证量子处理器的错误率低于容错阈值和限制近期算法的失败率的可行途径定制噪声的方法。