发表机构
Kingston University London; Endava plc（伦敦金斯顿大学; 恩达瓦公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究量子中继器网络在经典控制平面受攻击时自适应控制策略的权衡。开发CUDA-Q/SeQUeNCe联合仿真工作流，对比多种纯化策略，结果表明网络态势感知能通过牺牲原始吞吐量来提高量子网络中合格纠缠传递的保真度。
AI 中文摘要
量子中继器网络需要能平衡纠缠生成率、端到端保真度、纯化开销和内存延迟的自适应控制策略。当经典控制平面因网络异常或拒绝服务流量而退化时，这种权衡会变得更加复杂。我们开发了一种CUDA-Q/SeQUeNCe联合仿真工作流，用于研究异构线性中继器链中的自适应纠缠纯化。CUDA-Q噪声量子内核用于估计原始纠缠纯化和交换行为，而SeQUeNCe提供了一个事件层模型，用于随机链路生成、等待时间相关内存衰减、纯化失败和端到端交换。在稳定条件下，我们比较了无纯化、局部阈值纯化、平均场预测纯化、固定纯化和资源惩罚风险感知预测策略。在一个8节点链中，资源惩罚风险感知控制器相对于固定纯化提高了高于目标的传递概率，同时降低了延迟和纯化开销。然后，我们将量子网络控制器与从CSE-CIC-IDS2018良性到SSDP入侵检测跟踪中得出的异常分数相结合。在攻击期间, 无攻击感知控制器保持高原始传递率，但其高于目标的纠缠传递率降至0.098±0.007；IDS感知资源自适应控制器切换到更多的重纯化掩码，并将高于目标的传递率提高到0.344±0.011，与近似0.335的预言机感知值紧密匹配。这些结果表明，网络态势感知可以通过牺牲原始吞吐量来提高有用的量子网络结果，以实现保真度合格的纠缠传递。
英文摘要
Quantum-repeater networks require adaptive control policies that balance entanglement generation rate, end-to-end fidelity, purification overhead, and memory-induced latency. This tradeoff becomes more complex when the classical control plane is degraded by cyber anomalies or denial-of-service traffic. We develop a CUDA-Q/SeQUeNCe co-simulation workflow for studying adaptive entanglement purification in heterogeneous linear repeater chains. CUDA-Q noisy quantum kernels are used to estimate primitive entanglement purification and swapping behavior, while SeQUeNCe provides an event-layer model for stochastic link generation, waiting-time-dependent memory decay, purification failure, and end-to-end swapping. Under stationary conditions, we compare no purification, local threshold purification, mean-field predictive purification, fixed purification, and a resource-penalized risk-aware predictive policy. In an 8-node chain, the resource-penalized risk-aware controller increases above-target delivery probability relative to fixed purification while reducing latency and purification overhead. We then couple the quantum-network controller to anomaly scores derived from the CSE-CIC-IDS2018 benign-to-SSDP intrusion-detection trace. During the attack period, the attack-unaware controller maintains high raw delivery, but its above-target entanglement delivery falls to 0.098+/-0.007; the IDS-aware resource-adaptive controller switches to more purification-heavy masks and increases above-target delivery to 0.344+/-0.011, closely matching the oracle-aware value of approximately 0.335. These results demonstrate that cyber-state awareness can improve useful quantum-network outcomes by trading raw throughput for fidelity-qualified entanglement delivery.
