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arXiv 2408.06207cs.NIquant-ph
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真实拓扑中的多树量子路由

Multi-tree Quantum Routing in Realistic Topologies

Zebo Yang, Ali Ghubaish, Raj Jain, Ramana Kompella, Hassan Shapourian

AI总结:

针对量子纠缠分发网络长距离高效建链需求,提出含多个DODAG的多树异步路由方法,仿真验证其在多种拓扑下较单树方法可显著提升端到端纠缠速率。

摘要:

在纠缠分发网络中,两个节点之间的通信需要通过中间节点的纠缠交换生成端到端纠缠。长距离下高效创建端到端纠缠是核心目标。在我们此前关于异步路由的研究中,仅利用节点纠缠链路的本地知识就提升了这些纠缠速率。该研究通过构建树结构(尤其是面向目的地的有向无环图DODAG或生成树)实现这一点,消除了同步操作并保留了未使用的纠缠链路。本文中,我们提出一种包含多个DODAG的多树方法,旨在提升大规模网络中的端到端纠缠速率,专门适配多种网络拓扑,包括网格拓扑、杠铃拓扑,以及ESnet和Internet2等研究测试床中的真实拓扑。我们的仿真显示,与单树方法相比,该方法在特定拓扑下的端到端纠缠速率有显著提升。本研究凸显了量子网络中异步路由方案的潜力,阐明了异步路由在不同网络拓扑下的有效性,并提出了一种更优的路由策略。

英文摘要:

In entanglement distribution networks, communication between two nodes necessitates the generation of end-to-end entanglement by entanglement swapping at intermediate nodes. Efficiently creating end-to-end entanglements over long distances is a key objective. In our prior study on asynchronous routing, we enhanced these entanglement rates by leveraging solely the local knowledge of the entanglement links of a node. This was achieved by creating a tree structure, particularly a destination-oriented directed acyclic graph (DODAG) or a spanning tree, eliminating synchronous operations and conserving unused entanglement links. In this article, we present a multi-tree approach with multiple DODAGs designed to improve end-to-end entanglement rates in large-scale networks, specifically catering to a range of network topologies, including grids and barbells, as well as realistic topologies found in research testbeds like ESnet and Internet2. Our simulations show a marked improvement in end-to-end entanglement rates for specific topologies compared to the single-tree method. This study underscores the promise of asynchronous routing schemes in quantum networks, highlighting the effectiveness of asynchronous routing across different network topologies and proposing a superior routing tactic.

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。

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