AI 中文总结
本文针对受稳定子码保护的量子网络，提出跨层时空路径优化的单流、多流路由算法，可降低单流路由成本与多流归一化拥塞，为QEC感知路由提供算法组件。
AI 中文摘要
量子纠错（QEC）保护的直接传输是在脆弱量子态通过含噪量子网络物理转发时，对其进行保护的基础方法。当逻辑量子比特经过多跳时，具备QEC能力的选定节点可在其沿路由继续传输前恢复编码态。因此，最终传输策略的可行性与成本取决于我们如何联合选择路径、恢复位置及保护方案。本文针对分块式稳定子码保护的直接传输，构建并分析了跨层时空路径优化问题。主要成果包括固定方案与灵活方案的单流路由算法，以及多流路由算法。本文开发的框架可作为算法组件，用于满足逻辑错误与逻辑寿命约束的QEC感知路由。仿真显示，与Decode-Alway算法相比，该方法将单流平均路由成本降低约25%-30%；与Greedy-Assignment算法相比，将多流吞吐量归一化拥塞降低约28%-31%。
英文摘要
Quantum Error Correction~(QEC)-protected direct transmission is a fundamental approach to preserve fragile quantum states while they are physically forwarded across noisy quantum networks. When a logical qubit traverses multiple hops, selected QEC-capable nodes may recover the encoded state before it continues along the route. The feasibility and cost of the final transmission strategy therefore depend on how we jointly choose the path, the recovery locations, and the protection schemes. In this paper, we formulate and analyze a cross-layer spatio-temporal path optimization problem for block-style stabilizer-code-protected direct transmission. Our main results include fixed-scheme and flexible-scheme single-flow routing algorithms, as well as a multi-flow routing algorithm. The framework developed in this paper can serve as an algorithmic building block for QEC-aware routing under logical-error and logical-lifetime constraints. Simulations show that it reduces single-flow average routing cost by approximately 25--30\% over Decode-Always and lowers multi-flow throughput-normalized congestion by approximately 28--31\% over Greedy-Assignment.
CommentsICNP 2026 extended version
