Operating on the principles of quantum mechanics, quantum algorithms hold the promise for solving problems that are beyond the reach of the best-available classical algorithms. An integral part of realizing such speedup is the implementation of quantum queries, which read data into forms that quantum computers can process. Quantum random access memory (QRAM) is a promising architecture for realizing quantum queries. However, implementing QRAM in practice poses significant challenges, including query latency, memory capacity and fault-tolerance. In this paper, we propose the first end-to-end system architecture for QRAM. First, we introduce a novel QRAM that hybridizes two existing implementations and achieves asymptotically superior scaling in space (qubit number) and time (circuit depth). Like in classical virtual memory, our construction enables queries to a virtual address space larger than what is actually available in hardware. Second, we present a compilation framework to synthesize, map, and schedule QRAM circuits on realistic hardware. For the first time, we demonstrate how to embed large-scale QRAM on a 2D Euclidean space, such as a grid layout, with minimal routing overhead. Third, we show how to leverage the intrinsic biased-noise resilience of the proposed QRAM for implementation on either Noisy Intermediate-Scale Quantum (NISQ) or Fault-Tolerant Quantum Computing (FTQC) hardware. Finally, we validate these results numerically via both classical simulation and quantum hardware experimentation. Our novel Feynman-path-based simulator allows for efficient simulation of noisy QRAM circuits at a larger scale than previously possible. Collectively, our results outline the set of software and hardware controls needed to implement practical QRAM.

翻译：基于量子力学原理运行的量子算法，有望解决现有最优经典算法无法企及的问题。实现这种加速的关键环节在于执行量子查询，即读取数据并将其转化为量子计算机可处理的形式。量子随机存取存储器是实现量子查询的一种有前景的架构。然而，在实际中实现QRAM面临重大挑战，包括查询延迟、存储容量和容错性。本文提出了首个端到端的QRAM系统架构。首先，我们引入一种新型QRAM，它混合了两种现有实现方案，在空间（量子比特数）和时间（电路深度）方面实现了渐近更优的缩放比例。类似于经典虚拟内存，我们的构造使得对大于硬件实际可用容量的虚拟地址空间进行查询成为可能。其次，我们提出一个编译框架，用于在真实硬件上合成、映射和调度QRAM电路。我们首次展示了如何将大规模QRAM嵌入到二维欧几里得空间（如网格布局）中，且路由开销最小。第三，我们展示了如何利用所提出QRAM固有的偏置噪声鲁棒性，使其既适用于含噪中等规模量子（NISQ）硬件，也适用于容错量子计算（FTQC）硬件。最后，我们通过经典模拟和量子硬件实验对数值结果进行了验证。我们基于费曼路径的新型模拟器能够以前所未有的规模高效模拟含噪QRAM电路。综合而言，我们的成果勾勒出了实现实用化QRAM所需的全套软件和硬件控制手段。