基于内存量子网络的动态调度线性代数框架
A Linear Algebraic Framework for Dynamic Scheduling Over Memory-Equipped Quantum Networks
AI总结：
本文提出线性代数框架，利用量子内存创建中间纠缠链路，结合李雅普诺夫漂移最小化推导调度策略，并引入低计算成本的类最大权重策略，通过模拟器验证其在有损量子网络中的性能。
摘要：
量子互联网是一个新兴领域，有望带来众多有趣的应用，其中许多应用需要在任意用户对之间分发纠缠。本文研究了在任意纠缠交换量子网络（通常称为第一代量子网络）中的调度问题，采用其一般拓扑、多商品、有损公式化表述。我们引入了一个线性代数框架，通过创建中间纠缠链路来利用量子内存。该框架随后被用于应用李雅普诺夫漂移最小化（经典网络科学中的一种标准技术），以数学推导出一类自然的量子网络调度策略，该策略最小化用户需求积压的平方范数。此外，我们还提出并基准测试了一类受最大权重启发的额外策略，该策略以轻微的性能下降为代价，显著降低了计算成本。通过一个允许用户提供网络拓扑和调度策略的专用模拟器，从信息可用性、定位和整体网络性能方面对这些策略进行了比较，以展示所提供的工具在量子网络设计中的潜在应用。
英文摘要：
Quantum Internetworking is a recent field that promises numerous interesting applications, many of which require the distribution of entanglement between arbitrary pairs of users. This work deals with the problem of scheduling in an arbitrary entanglement swapping quantum network - often called first generation quantum network - in its general topology, multicommodity, loss-aware formulation. We introduce a linear algebraic framework that exploits quantum memory through the creation of intermediate entangled links. The framework is then employed to apply Lyapunov Drift Minimization (a standard technique in classical network science) to mathematically derive a natural class of scheduling policies for quantum networks minimizing the square norm of the user demand backlog. Moreover, an additional class of Max-Weight inspired policies is proposed and benchmarked, reducing significantly the computation cost at the price of a slight performance degradation. The policies are compared in terms of information availability, localization and overall network performance through an ad-hoc simulator that admits user-provided network topologies and scheduling policies in order to showcase the potential application of the provided tools to quantum network design.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
