论文标题

多指数错误外推和组合NISQ应用程序的错误缓解技术

Multi-exponential Error Extrapolation and Combining Error Mitigation Techniques for NISQ Applications

论文作者

Cai, Zhenyu

论文摘要

量子硬件中的噪声仍然是实施量子计算机的最大障碍。为了在近期量子计算机的实际应用中打击噪声,而不是依靠需要大型量子开销的量子误差校正,而是转向量子误差缓解,在这种情况下,我们可以利用额外的测量值。误差外推是一种已成功实现的误差缓解技术。数值模拟和启发式论证表明,指数曲线可有效在大电路极限中外推,而围绕统一的预期电路误差计数。在本文中,我们将其扩展到多指数误差外推,并为其在Pauli噪声下的有效性提供了更严格的证据。通过我们的数值模拟进一步验证了这一点,显示了单个指数外推的估计精度的数量级提高。此外,我们通过利用这些单个技术的特征来开发将误差外推与其他两种误差缓解技术结合的方法:准概率和对称性验证。如我们的仿真所示,我们的组合方法可以实现低估计偏置,而采样的成本比准概率小,而无需能够根据规范错误外推的要求调整硬件错误率。

Noise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.

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