Transient errors from the dynamic NISQ noise landscape are challenging to comprehend and are especially detrimental to classes of applications that are iterative and/or long-running, and therefore their timely mitigation is important for quantum advantage in real-world applications. The most popular examples of iterative long-running quantum applications are variational quantum algorithms (VQAs). Iteratively, VQA's classical optimizer evaluates circuit candidates on an objective function and picks the best circuits towards achieving the application's target. Noise fluctuation can cause a significant transient impact on the objective function estimation of the VQA iterations / tuning candidates. This can severely affect VQA tuning and, by extension, its accuracy and convergence. This paper proposes QISMET: Quantum Iteration Skipping to Mitigate Error Transients, to navigate the dynamic noise landscape of VQAs. QISMET actively avoids instances of high fluctuating noise which are predicted to have a significant transient error impact on specific VQA iterations. To achieve this, QISMET estimates transient error in VQA iterations and designs a controller to keep the VQA tuning faithful to the transient-free scenario. By doing so, QISMET efficiently mitigates a large portion of the transient noise impact on VQAs and is able to improve the fidelity by 1.3x-3x over a traditional VQA baseline, with 1.6-2.4x improvement over alternative approaches, across different applications and machines. Further, to diligently analyze the effects of transients, this work also builds transient noise models for target VQA applications from observing real machine transients. These are then integrated with the Qiskit simulator.

翻译：摘要：动态NISQ噪声景观中的瞬态误差难以理解，且对迭代式和/或长时间运行的应用程序类别尤为不利，因此及时缓解这类误差对于在实际应用中实现量子优势至关重要。迭代式长时间量子应用中最典型的例子是变分量子算法（VQA）。在迭代过程中，VQA的经典优化器会在目标函数上评估电路候选方案，并挑选出最有助于实现应用目标的电路。噪声波动会对VQA迭代/调优候选方案的目标函数估计产生显著的瞬态影响，进而严重影响VQA的调优过程及其精度与收敛性。本文提出QISMET：量子迭代跳过以缓解误差瞬态，旨在驾驭VQA的动态噪声景观。QISMET主动避开预测会对特定VQA迭代产生显著瞬态误差影响的高波动噪声实例。为此，QISMET估计VQA迭代中的瞬态误差，并设计一个控制器，使VQA调优保持与无瞬态场景一致。通过这种方式，QISMET有效缓解了瞬态噪声对VQA的大部分影响，能够将保真度较传统VQA基线提升1.3倍至3倍，较其他替代方法提升1.6倍至2.4倍（跨不同应用与量子设备）。此外，为深入分析瞬态效应，本文还通过观测真实量子设备瞬态现象，为目标VQA应用构建了瞬态噪声模型，并将其集成至Qiskit模拟器中。