论文标题
光子量子处理器的量子体积
Quantum Volume for Photonic Quantum Processors
论文作者
论文摘要
定义近期量子计算处理器的指标一直是量子硬件研发工作的组成部分。这种定量特征不仅对于报告进度和比较不同的量子平台有用，而且对于识别瓶颈和设计技术路线图也至关重要。最初是针对基于电路的量子计算机引入的大多数指标，例如随机基准测量和量子体积，并且不适用于基于测量的量子计算（MBQC）处理器，例如在光子设备中。在本文中，我们通过提出一个框架来缩小这一差距，以将MBQC过程中的物理噪声和缺陷映射到等效量子电路中的逻辑错误，从而使众所周知的指标能够表征MBQC。为了展示我们的框架，我们研究了基于Gottesman-Kitaev-Preskill（GKP）编码的连续变化群集状态，该状态编码是光子量子计算的近期候选者，并得出有效的逻辑门误差通道，并根据GKP Squeeezing和Photon损失率计算量子量。
Defining metrics for near-term quantum computing processors has been an integral part of the quantum hardware research and development efforts. Such quantitative characteristics are not only useful for reporting the progress and comparing different quantum platforms, but also essential for identifying the bottlenecks and designing a technology roadmap. Most metrics such as randomized benchmarking and quantum volume were originally introduced for circuit-based quantum computers and were not immediately applicable to measurement-based quantum computing (MBQC) processors such as in photonic devices. In this paper, we close this gap by presenting a framework to map physical noises and imperfections in MBQC processes to logical errors in equivalent quantum circuits, whereby enabling the well-known metrics to characterize MBQC. To showcase our framework, we study a continuous-variable cluster state based on the Gottesman-Kitaev-Preskill (GKP) encoding as a near-term candidate for photonic quantum computing, and derive the effective logical gate error channels and calculate the quantum volume in terms of the GKP squeezing and photon loss rate.
