论文标题
相关的随机基准测试
Correlated Randomized Benchmarking
论文作者
论文摘要
为了提高量子设备上多量算法的性能，具有表征非本地量子误差（例如串扰）的方法至关重要。为了解决此问题，我们提出并测试扩展对同时随机基准数据数据的分析 - 相关的随机基准测试。我们将相关极化的衰变与固定重量去极化图的组成形成，以表征串扰误差的位置和重量。从这些错误中，我们引入了一个串扰度量，该指标指示只有局部误差的距离。我们使用四量量超导装置实验证明了这项技术，并在实施回声序列时利用相关的RB来验证串扰降低。
To improve the performance of multi-qubit algorithms on quantum devices it is critical to have methods for characterizing non-local quantum errors such as crosstalk. To address this issue, we propose and test an extension to the analysis of simultaneous randomized benchmarking data -- correlated randomized benchmarking. We fit the decay of correlated polarizations to a composition of fixed-weight depolarizing maps to characterize the locality and weight of crosstalk errors. From these errors we introduce a crosstalk metric which indicates the distance to the closest map with only local errors. We demonstrate this technique experimentally with a four-qubit superconducting device and utilize correlated RB to validate crosstalk reduction when we implement an echo sequence.
