发表机构
memQ Inc.（memQ公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一个开源的、拓扑感知的分布式量子计算编译与调度框架，通过模块化接口支持跨QPU操作和多种纠缠生成模型，实验表明编译策略和拓扑显著影响纠缠成本，强调软硬件协同设计。
AI 中文摘要
分布式量子计算（DQC）旨在通过基于纠缠的链路互连多个量子处理单元（QPU），从而超越单片处理器的规模限制。实现这一愿景需要跨量子网络、编译和调度领域对硬件和软件进行协同设计，然而现有工具仍然在单片电路编译器和长距离量子网络模拟器之间呈现碎片化状态。我们提出一个开源的、拓扑感知的框架，用于分布式量子程序的编译和调度。给定一个输入电路和目标网络的描述，该框架将电路划分并重构为一个分布式程序，该程序尊重指定的QPU间和QPU内拓扑，通过门传送和态传送覆盖跨QPU操作，并在确定性或随机纠缠生成模型下调度结果。通过接受和发出标准OpenQASM，该框架与现有单片工具链互操作，其标准化模块接口允许划分和调度策略被互换和基准测试。使用该框架，我们表明最佳性能的编译策略在测试的电路和网络配置中有所不同，并且网络拓扑和QPU内连接性都显著影响执行的纠缠成本。这些发现强调了分布式量子计算需要协同设计方法，而我们的框架正是为此设计的。
英文摘要
Distributed quantum computing (DQC) seeks to scale beyond the limits of monolithic processors by interconnecting multiple quantum processing units (QPUs) through entanglement-based links. Realizing this vision requires the co-design of hardware and software across the domains of quantum networking, compilation, and scheduling, yet existing tools remain fragmented between monolithic circuit compilers and long-distance quantum network simulators. We present an open-source, topology-informed framework for the compilation and scheduling of distributed quantum programs. Given an input circuit and a description of the target network, the framework partitions and reconstructs the circuit into a distributed program that respects the specified inter- and intra-QPU topology, covers cross-QPU operations through gate and state teleportation, and schedules the result under either deterministic or stochastic entanglement-generation models. By accepting and emitting standard OpenQASM, the framework interoperates with existing monolithic toolchains, and its standardized module interfaces allow partitioning and scheduling strategies to be interchanged and benchmarked. Using this framework, we show that the best-performing compilation strategy varies across the tested circuits and network configurations, and that both network topology and intra-QPU connectivity substantially affect the entanglement cost of execution. These findings underscore the need for a co-design approach to distributed quantum computing, which our framework is designed to support.
Comments20 pages, 15 figures, 5 tables. Code: https://github.com/memQGit/dqc ; archived at https://doi.org/10.5281/zenodo.22260966
