在含噪声量子计算机上测试平台无关的量子错误缓解
Testing platform-independent quantum error mitigation on noisy quantum computers
AI总结：
本文提出资源归一化的“改进因子”，在 IBM、IonQ、Rigetti 及含噪声模拟器上用零噪声外推和概率错误抵消评估两类基准，证明量子错误缓解平均有益但性能依赖平台。
AI中文摘要：
我们将量子错误缓解技术应用于多种基准问题和量子计算机，以在实践中评估量子错误缓解的性能。为此，我们定义了一种由经验驱动、按资源归一化的错误缓解改进度量，称之为改进因子，并为我们执行的每个实验计算该度量。我们所做的实验包括将零噪声外推和概率错误抵消应用于在 IBM、IonQ 和 Rigetti 量子计算机以及含噪声量子计算机模拟器上运行的两个基准问题。结果表明，即使按所使用的额外资源进行归一化，错误缓解平均而言也比不进行错误缓解更有益；但结果也强调，量子错误缓解的性能依赖于底层计算机。
英文摘要：
We apply quantum error mitigation techniques to a variety of benchmark problems and quantum computers to evaluate the performance of quantum error mitigation in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation which we call the improvement factor, and calculate this metric for each experiment we perform. The experiments we perform consist of zero-noise extrapolation and probabilistic error cancellation applied to two benchmark problems run on IBM, IonQ, and Rigetti quantum computers, as well as noisy quantum computer simulators. Our results show that error mitigation is on average more beneficial than no error mitigation - even when normalized by the additional resources used - but also emphasize that the performance of quantum error mitigation depends on the underlying computer.
