QROB：通过反向构造量化量子编译中的实现开销
QROB: Quantifying Realization Overhead in Quantum Compilation via Reverse Construction
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中文总结 AI 辅助
提出QROB反向构造方法，为量子编译生成与编译器无关的参考实现，揭示现有工具高达24.1倍SWAP和7.0倍时间开销差距，训练的路由器优于SABRE，并在真实硬件上提升1.65倍镜像电路存活率。
中文摘要 AI 辅助
量子编译协调程序理想化的交互拓扑与硬件局部性约束，然而大规模评估缺乏用于实现开销的校准参考。我们提出QROB，一种可扩展的反向构造方法，该方法从可直接实现的配置向后生成编译实例，保留逆向路径作为可行的、与编译器无关的参考。QROB为NISQ SWAP路由和容错晶格手术调度提供了共同的评估基础，同时将其参考保持原则扩展到容量受限的量子内存访问调度。在从9到156量子比特的系统中，评估突显了QROB作为诊断基准和数据源的双重效用。首先，对于编译器表征，QROB揭示了现有工具中巨大的实现差距，NISQ编译器产生的参考SWAP成本高达24.1倍，容错编译器所需的参考制造时间（makespan）高达7.0倍。其次，作为数据驱动编译的监督源，在QROB参考上训练的路由器在84.8%的真实应用电路上优于Qiskit SABRE。最后，在真实硬件上，QROB参考实现在三个156量子比特的IBM Heron-r2处理器上实现了中位镜像电路存活率，为完整Qiskit O3编译的1.65倍，表明缩小算法编译差距可直接转化为物理保真度的提升。
英文摘要
Quantum compilation reconciles a program's idealized interaction topology with hardware locality constraints, yet evaluations at scale lack calibrated references for realization overhead. We present QROB, a scalable reverse-construction methodology that generates compilation instances backward from directly realizable configurations, retaining the inverse paths as feasible, compiler-independent references. QROB provides a common evaluation substrate for NISQ SWAP routing and fault-tolerant lattice-surgery scheduling, while extending its reference-preserving principle to capacity-constrained quantum memory-access scheduling. Across systems ranging from 9 to 156 qubits, evaluations highlight QROB's utility as both a diagnostic benchmark and a data source. First, for compiler characterization, QROB reveals substantial realization gaps in existing tools, with NISQ compilers incurring up to 24.1x the reference SWAP cost and fault-tolerant compilers requiring up to 7.0x the reference makespan. Second, as a supervision source for data-driven compilation, a router trained on QROB references outperforms Qiskit SABRE on 84.8% of real-world application circuits. Finally, on real hardware, QROB reference realizations achieve a median mirror-circuit survival rate 1.65x that of full Qiskit O3 compilations across three 156-qubit IBM Heron-r2 processors, demonstrating that closing algorithmic compilation gaps translates directly into physical fidelity gains.
发表机构
- Beijing Academy of Quantum Information Sciences（北京量子信息科学研究院）
- Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）
- Institute of Physics, Chinese Academy of Sciences（中国科学院物理研究所）
- Hefei National Laboratory（合肥国家实验室）
机构由 AI 辅助整理，请以论文原文为准。
