论文标题
古典阴影的量子电路切割
Quantum Circuit Cutting for Classical Shadows
论文作者
论文摘要
经典影子层析成像是一种样品效率高效的技术，用于表征量子系统并预测其许多特性。电路切割是一种将大量子电路分为较小的片段的技术，可以使用较少的量子资源来更坚固地执行。我们介绍了一种分裂和诱导电路切割方法，用于估计使用经典阴影的可观察结果的期望值。我们得出了一个通用公式，用于使用任意剪切电路的电路片段的经典阴影进行预测，并为可观测值分解跨片段的情况提供样本复杂性分析。然后，我们从数字上表明，当估计在许多量子位上非努力作用的高重量可观察物时，我们的分裂方法优于传统的未切割阴影断层扫描，并讨论了这一优势的机制。
Classical shadow tomography is a sample-efficient technique for characterizing quantum systems and predicting many of their properties. Circuit cutting is a technique for dividing large quantum circuits into smaller fragments that can be executed more robustly using fewer quantum resources. We introduce a divide-and-conquer circuit cutting method for estimating the expectation values of observables using classical shadows. We derive a general formula for making predictions using the classical shadows of circuit fragments from arbitrarily cut circuits, and provide the sample complexity analysis for the case when observables factorize across fragments. Then, we numerically show that our divide-and-conquer method outperforms traditional uncut shadow tomography when estimating high-weight observables that act non-trivially on many qubits, and discuss the mechanisms for this advantage.
