论文标题
切割量子电路以在量子和经典平台上运行
Cutting Quantum Circuits to Run on Quantum and Classical Platforms
论文作者
论文摘要
量子计算（QC）提供了一种新的计算范式，该范式有可能在经典计算上提供重要的加速。每个附加量子量都会使量子算法可用的计算状态空间的大小增加一倍。这种指数扩展的覆盖范围是质量控制的力量，但同时却对量子处理单元（QPU）硬件提出了苛刻的要求。另一方面，中央处理单元（CPU）或图形处理单元（GPU）纯粹对量子电路的纯典模拟，因为它们迅速被运行时和内存瓶装瓶装。本文介绍了CUTQC，CUTQC是一种可扩展的混合计算方法，该方法将大量子电路分布到量子（QPU）和经典平台（CPU或GPU）上。 CUTQC证明了对QPU或经典模拟极限的量子电路的评估，并且比在实际系统运行中实现的大型NISQ设备获得了更高的量子电路评估保真度。
Quantum computing (QC) offers a new computing paradigm that has the potential to provide significant speedups over classical computing. Each additional qubit doubles the size of the computational state space available to a quantum algorithm. Such exponentially expanding reach underlies QC's power, but at the same time puts demanding requirements on the quantum processing units (QPU) hardware. On the other hand, purely classical simulations of quantum circuits on either central processing unit (CPU) or graphics processing unit (GPU) scale poorly as they quickly become bottlenecked by runtime and memory. This paper introduces CutQC, a scalable hybrid computing approach that distributes a large quantum circuit onto quantum (QPU) and classical platforms (CPU or GPU) for co-processing. CutQC demonstrates evaluation of quantum circuits that are larger than the limit of QPU or classical simulation, and achieves much higher quantum circuit evaluation fidelity than the large NISQ devices achieve in real-system runs.
