发表机构
Georgia Institute of Technology（佐治亚理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
ReFINE是一种需求感知的抢占式调度器，通过动态调度纠缠蒸馏与编码增强内存的形成，在量子网络中实现速率与保真度的最优权衡。
AI 中文摘要
在量子网络中，节点通过共享爱因斯坦-波多尔斯基-罗森（EPR）对进行连接，理想情况下具有高保真度和高速率。然而，由于不完美的生成和退相干误差，EPR对的保真度会降低。纠缠蒸馏是一种提高保真度的方法，但其操作是概率性的，并且失败时可能破坏所有涉及的EPR对。这种失败减少了可用于应用服务的EPR对数量，从而降低了服务速率。量子纠错（QEC）是另一种保护EPR对免受错误影响的机制，通过形成我们称之为编码增强内存（CEM）的方式实现。虽然有效，但CEM需要额外的时间和资源来形成编码，这也降低了服务速率。现有方法通常使用蒸馏和CEM的静态组合，忽略了需求变化。这导致服务速率低且保真度提升不显著。有限的资源以及这种速率-保真度权衡使得调度何时运行蒸馏、形成CEM或服务请求变得至关重要。我们提出ReFINE，一种需求感知的抢占式调度器，它基于应用需求要么立即服务可用的EPR对，要么将其保存在CEM中。这种仅在需要时选择性使用CEM的方式，能够比始终使用CEM更好地平衡速率-保真度权衡。在请求到达之间，ReFINE要么调度蒸馏EPR对，要么形成CEM以保护蒸馏后的对，遵循以下三种优先级策略之一：ReFINE-D（蒸馏优先）首先生成EPR对用于蒸馏，然后形成CEM，优先考虑服务速率。ReFINE-M（内存优先）首先形成CEM，然后生成EPR对用于蒸馏，优先考虑保真度。ReFINE-C（并发）同时执行蒸馏和CEM形成，在保真度和服务速率之间取得平衡。
英文摘要
In quantum networks, nodes are connected via sharing of Einstein-Podolsky-Rosen (EPR) pairs, ideally with high fidelity and high rate. However, the fidelity of EPR pairs degrades due to imperfect generation and decoherence errors. Entanglement Distillation is a method that increases the fidelity but operates probabilistically and may destroy all involved EPR pairs upon failure. This failure reduces available EPR pairs for application use, thereby decreasing the service rate. Quantum Error Correction (QEC) is another mechanism to protect EPR pairs against error by forming what we term as Coding-Enhanced Memory (CEM). While effective, CEM requires extra time and resources to form the code, which also reduces the service rate. Existing methods often use static combinations of distillation and CEM, ignoring demand variations. This results in a low service rate without significant fidelity gain. Limited resources together with this rate-fidelity tradeoff make it essential to schedule when to run distillation, form CEM, or serve requests. We propose ReFINE, a demand-aware preemptive scheduler that based on application requirements either serves an available EPR pair immediately or preserves it in CEM. This selective use of CEM, only when needed, enables a better balance for rate-fidelity tradeoff than always using CEM. Between request arrivals, ReFINE either schedules distilling EPR pairs or forming CEM to protect distilled pairs, following one of the three priority policies: ReFINE-D (Distillation-First) first generates EPR pairs for distillation and then forms the CEM, prioritizing service rate. ReFINE-M (Memory-First) first forms the CEM, then generates the EPR pairs for distillation, prioritizing fidelity. ReFINE-C (Concurrent) performs both distillation and CEM formation concurrently, balancing between fidelity and service rate.
