一种应对量子机器中串扰的协同编译工作流
A Synergistic Compilation Workflow for Tackling Crosstalk in Quantum Machines
AI总结：
本文提出 CQC 串扰感知量子编译框架，在编译早期联合优化算法逻辑、路由与串扰缓解，并利用 VQE 等应用结构，在 IBM-Q 上显著降低错误率和电路深度。
摘要：
近期量子系统往往存在噪声。串扰噪声已被认为是超导含噪中等规模量子（NISQ）设备中几类主要噪声之一。串扰源于在邻近量子比特上并发执行双量子比特门（例如 \ exttt{CX}）。与单独运行这些门相比，串扰可能显著提高门的错误率。串扰可以通过调度或硬件机器调谐来缓解。然而，以往的科学研究在编译过程中非常晚的阶段才处理串扰，通常是在硬件映射完成之后。这可能会错失同时优化算法逻辑、路由和串扰的良好机会。在本文中，我们通过在非常早的编译阶段同时考虑所有这些因素来进行突破。我们提出了一个名为 CQC 的串扰感知量子程序编译框架，它能够增强串扰缓解效果，同时实现令人满意的电路深度。此外，我们识别了从中间表示到电路的转换中用于面向应用的串扰缓解的机会，例如变分量子本征求解器（VQE）中的 \ exttt{CX} 梯形构造。仿真和真实 IBM-Q 设备上的评估表明，与最先进的门调度方法相比，我们的框架可将错误率显著降低至多 6 倍，而电路深度仅约为其 60%。特别是对于 VQE，我们使用 IBMQ Guadalupe 在 H4 分子上展示了相对于现有方法 49% 的电路深度降低和 9.6% 的保真度提升。我们的 CQC 框架将在 GitHub 上发布。
英文摘要：
Near-term quantum systems tend to be noisy. Crosstalk noise has been recognized as one of several major types of noises in superconducting Noisy Intermediate-Scale Quantum (NISQ) devices. Crosstalk arises from the concurrent execution of two-qubit gates on nearby qubits, such as \texttt{CX}. It might significantly raise the error rate of gates in comparison to running them individually. Crosstalk can be mitigated through scheduling or hardware machine tuning. Prior scientific studies, however, manage crosstalk at a really late phase in the compilation process, usually after hardware mapping is done. It may miss great opportunities of optimizing algorithm logic, routing, and crosstalk at the same time. In this paper, we push the envelope by considering all these factors simultaneously at the very early compilation stage. We propose a crosstalk-aware quantum program compilation framework called CQC that can enhance crosstalk mitigation while achieving satisfactory circuit depth. Moreover, we identify opportunities for translation from intermediate representation to the circuit for application-specific crosstalk mitigation, for instance, the \texttt{CX} ladder construction in variational quantum eigensolvers (VQE). Evaluations through simulation and on real IBM-Q devices show that our framework can significantly reduce the error rate by up to 6$\times$, with only $\sim$60\% circuit depth compared to state-of-the-art gate scheduling approaches. In particular, for VQE, we demonstrate 49\% circuit depth reduction with 9.6\% fidelity improvement over prior art on the H4 molecule using IBMQ Guadalupe. Our CQC framework will be released on GitHub.
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