AI 中文总结
研究硅自旋量子比特编译难题，基于平面上的蛇模型引入编译框架，提出最短路径和基于旋转的算法等，评估显示最短路径方法在稀疏场景优，基于旋转的方法在高密度环境好，实现开源。
AI 中文摘要
硅自旋量子比特因其良好的扩展性和制造特性成为有前景的量子比特技术。然而，将量子电路有效编译到自旋量子比特平台仍具挑战，尤其是考虑硬件限制和对静态缺陷的高敏感性时。现有编译方法要么很大程度忽略纠错，要么专注低级调度构建，缺少逻辑、纠错算法的高级编译和路由。为填补空白，我们基于平面上的蛇模型引入自旋量子比特编译框架，利用二维表面码和量子比特隐形传态减轻错误。在此模型基础上，提出最短路径和基于旋转的算法及其他缺陷处理和初始映射策略。我们在不同架构设置和问题规模下评估两种算法，表明最短路径方法在稀疏、低缺陷场景中表现出色，基于旋转的方法在高密度环境中性能更佳。该实现作为开源在GitHub上公开可用。
英文摘要
Silicon spin qubits have emerged as a promising qubit technology due to their favorable scaling and fabrication properties. However, efficiently compiling quantum circuits onto spin qubit platforms remains challenging, particularly when accounting for hardware constraints and the high sensitivity to static defects. Existing compilation approaches for spin qubits either largely ignore error correction, despite its critical role for large-scale quantum computation, or focus on low-level schedule constructions, missing a high-level compilation and routing for logical, error-corrected algorithms. To address this gap, we introduce a compilation framework for spin qubits based on the recent snakes on a plane model, which utilizes a 2D surface code and qubit teleportation to mitigate errors. Building on this model, we propose shortest-path and rotation-based algorithms as two novel classes of qubit-routing techniques, along with additional defect-handling and initial-mapping strategies. We evaluate both algorithms across diverse architectural settings and problem sizes, demonstrating that shortest-path methods excel in sparse, low-defect scenarios, while rotation-based approaches perform better in high-density environments. An open-source implementation of our framework is publicly available on GitHub as part of the Munich Quantum Toolkit (MQT) at https://github.com/munich-quantum-toolkit/spin-qubit-routing.
Comments11 pages, 14 figures, 1 table, minor changes, accepted at the IEEE International Conference on Quantum Computing and Engineering (QCE), 2026
