English(EN) Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems

新的图神经网络框架优化了多量子比特处理器系统的量子线路调度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-11 04:00

研究人员开发了一个新的框架，用于在多量子比特处理器系统上调度量子线路，旨在最大化执行保真度。该系统利用图神经网络（GNN）在编译前估计量子线路在不同量子比特处理器上的预期保真度。然后，调度器利用这些估计来平衡保真度和并行性，提供了一种比暴力方法更具资源效率的方案。 AI

影响这项研究通过优化复杂的多量子比特处理器系统的量子线路执行效率和可靠性，有望提高量子计算的效率和可靠性。

排序理由详细介绍量子计算新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto, Patrick Hopf, Deborah Volpe, Helmut Seidl, Giovanna Turvani, Robert Wille, Christian B. Mendl, Martin Schulz · 2026-09-11 04:00

面向多量子比特处理器系统的保真度感知量子线路调度

arXiv:2609.09980v1 Announce Type: cross Abstract: High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics. For current noisy devices, errors compound …