Quantum networks (QNs) distribute entangled states to enable distributed quantum computing and sensing applications. However, in such QNs, quantum switches (QSs) have limited resources that are highly sensitive to noise and losses and must be carefully allocated to minimize entanglement distribution delay. In this paper, a QS resource allocation framework is proposed, which jointly optimizes the average entanglement distribution delay and entanglement distillation operations, to enhance the end-to-end (e2e) fidelity and satisfy minimum rate and fidelity requirements. The proposed framework considers realistic QN noise and includes the derivation of the analytical expressions for the average quantum memory decoherence noise parameter, and the resulting e2e fidelity after distillation. Finally, practical QN deployment aspects are considered, where QSs can control 1) nitrogen-vacancy (NV) center SPS types based on their isotopic decomposition, and 2) nuclear spin regions based on their distance and coupling strength with the electron spin of NV centers. A simulated annealing metaheuristic algorithm is proposed to solve the QS resource allocation optimization problem. Simulation results show that the proposed framework manages to satisfy all users rate and fidelity requirements, unlike existing distillation-agnostic (DA), minimal distillation (MD), and physics-agnostic (PA) frameworks which do not perform distillation, perform minimal distillation, and does not control the physics-based NV center characteristics, respectively. Furthermore, the proposed framework results in around 30% and 50% reductions in the average e2e entanglement distribution delay compared to existing PA and MD frameworks, respectively. Moreover, the proposed framework results in around 5%, 7%, and 11% reductions in the average e2e fidelity compared to existing DA, PA, and MD frameworks, respectively.

翻译：量子网络（QN）通过分发纠缠态实现分布式量子计算与传感应用。然而，在这种网络中，量子交换机（QS）具有对噪声和损耗高度敏感的有限资源，必须精心分配以最小化纠缠分发延迟。本文提出一种QS资源分配框架，通过联合优化平均纠缠分发延迟与纠缠蒸馏操作，以提升端到端（e2e）保真度并满足最低速率与保真度要求。该框架考虑了真实的QN噪声，推导了平均量子存储退相干噪声参数以及蒸馏后e2e保真度的解析表达式。最后，本文考虑了实际的QN部署场景，其中QS可控制：1）基于同位素分解的氮空位（NV）中心单光子源（SPS）类型，以及2）基于与NV中心电子自旋的距离和耦合强度的核自旋区域。提出一种模拟退火元启发式算法来解决QS资源分配优化问题。仿真结果表明，与现有不执行蒸馏的蒸馏不可知（DA）框架、执行最小蒸馏的最小蒸馏（MD）框架以及不控制基于物理的NV中心特性的物理不可知（PA）框架相比，所提框架能够满足所有用户的速率与保真度要求。此外，与PA和MD框架相比，所提框架的平均e2e纠缠分发延迟分别降低约30%和50%。同时，与DA、PA和MD框架相比，所提框架的平均e2e保真度分别降低约5%、7%和11%。