[论文] Quality-of-Transmission Estimation in Quantum Networks: Compute, Simul...

论文概要

研究领域: ML
作者: Anis Bekri, Amar Abane, Van Sy Mai, Abdella Battou, Saddek Bensalem
发布时间: 2026-10-16
arXiv: 2610.23827

中文摘要

未来的量子网络将依赖控制平面决策，如路由、调度、纠缠供应、纯化和内存分配。每个决策都依赖于对候选路径所能提供的纠缠质量的及时可靠估计，其中端到端保真度是核心指标。受光网络中传输质量（QoT）估计经验的启发，本文探讨量子控制器何时应解析计算保真度、何时应仿真、或何时应学习代理模型。光学类比有用但不完整：光 QoT 估计通常预测标量传输余量，而量子 QoT 估计必须考虑概率性纠缠生成、随机内存等待时间、退相干、状态消耗和测量约束，这些因素使保真度成为随机目标。我们提出量子 QoT 估计的计算/仿真/学习框架，并以仿真概念验证加以说明。研究表明，简单情形下解析组合已足够；当随机内存效应塑造交付保真度分布时仿真变得必要；轻量级学习代理可以近似仿真器标签，为在线控制提供低得多的运行时成本。我们最后讨论了部署的开放挑战，包括随机目标、仿真到真实迁移、数据生成成本、物理信息学习以及从单路径到全网拓扑的泛化。

原文摘要

Future quantum networks will rely on control-plane decisions such as routing, scheduling, entanglement provisioning, purification, and memory allocation. Each decision depends on a timely and reliable estimate of the quality of the entanglement that a candidate path can deliver, with end-to-end fidelity as a central metric. Inspired by the optical-networking experience with quality-of-transmission (QoT) estimation, this article asks when a quantum controller should compute fidelity analytically, simulate it, or learn a surrogate model. The optical analogy is useful but incomplete: optical QoT estimation often predicts a scalar transmission margin, whereas quantum QoT estimation must account for probabilistic entanglement generation, random memory waiting times, decoherence, state consumpti...

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