一句话：提出 Fat-Tree QRAM 架构，以 O(N) 量子比特在 O(log N) 时间内并行执行 O(log N) 个量子查询。
量子随机存取存储器（QRAM）是支持量子算法以叠加态查询经典或量子数据的关键组件，但传统架构难以高效支持多个查询并行。本文提出 Fat-Tree QRAM，一种可同时流水线化多个量子查询的查询架构，在保持查询速度与保真度可扩展性的同时，使用 O(N) 个量子比特在 O(log N) 时间内完成 O(log N) 个独立查询。作者进一步基于超导电路给出模块化与片上实现，并在现实参数下分析性能与保真度。论文还提出查询调度协议以最大化硬件利用率并以最优速率访问底层数据。结果表明，Fat-Tree QRAM 有望成为实用量子计算共享内存系统中的有吸引力架构。
Quantum Random Access Memory (QRAM) is a crucial architectural component for querying classical or quantum data in superposition, enabling algorithms with wide-ranging applications in quantum arithmetic, quantum chemistry, machine learning, and quantum cryptography. In this work, we introduce Fat-Tree QRAM, a novel query architecture capable of pipelining multiple quantum queries simultaneously while maintaining desirable scalings in query speed and fidelity. Specifically, Fat-Tree QRAM performs O(log(N)) independent queries in O(log(N)) time using O(N) qubits, offering immense parallelism benefits over traditional QRAM architectures. To demonstrate its experimental feasibility, we propose modular and on-chip implementations of Fat-Tree QRAM based on superconducting circuits and analyze their performance and fidelity under realistic parameters. Furthermore, a query scheduling protocol is presented to maximize hardware utilization and access the underlying data at an optimal rate. These results suggest that Fat-Tree QRAM is an attractive architecture in a shared memory system for practical quantum computing.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2502-06767,
title = {Fat-Tree QRAM: A High-Bandwidth Shared Quantum Random Access Memory for Parallel Queries},
author = {Shifan Xu and Alvin Lu and Yongshan Ding},
booktitle = {ASPLOS},
year = {2025},
doi = {10.1145/3676641.3716256}
}