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arXiv 2205.04036quant-phcs.NI
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量子网络中纠缠的预分布

Pre-Distribution of Entanglements in Quantum Networks

Mohammad Ghaderibaneh, Himanshu Gupta, C. R. Ramakrishnan, Ertai Luo

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11 pages, 9 figures
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摘要：

量子网络通信具有挑战性，因为量子机制中的不可克隆定理使得许多经典技术无法适用。对于长距离通信，唯一可行的方法是量子态的隐形传态，这需要量子比特的纠缠对（EP）的先验分布。由于底层物理过程成功的可能性很低，因此跨远程节点建立EP可能会导致显著的延迟。为了减少EP生成等待时间，先前的工作已经着眼于选择有效的纠缠路由路径以及同时使用多个这样的路径来生成EP。在本文中，我们提出并研究了一种补充技术，以减少EP生成延迟-预先分配EP在某些（预定）对网络节点，这些预先分配的EP，然后可以用来生成EP的请求对，当需要时，具有较低的生成延迟。对于这样的预分布的方法是最有效的，我们需要解决的优化问题，选择节点对的EP应预分布，以尽量减少预期的EP请求的生成延迟，在给定的成本约束下。在本文中，我们适当地制定上述优化问题，并设计了两个有效的算法，其中之一是一个贪婪的方法的基础上的近似算法的特殊情况。通过广泛的评估NetSquid模拟器，我们证明了我们的方法和开发的技术的有效性，我们表明，我们开发的算法优于天真的方法高达一个数量级。

英文摘要：

Quantum network communication is challenging, as the No-Cloning theorem in quantum regime makes many classical techniques inapplicable. For long-distance communication, the only viable approach is teleportation of quantum states, which requires a prior distribution of entangled pairs (EPs) of qubits. Establishment of EPs across remote nodes can incur significant latency due to the low probability of success of the underlying physical processes. To reduce EP generation latency, prior works have looked at selection of efficient entanglement-routing paths and simultaneous use of multiple such paths for EP generation. In this paper, we propose and investigate a complementary technique to reduce EP generation latency--to pre-distribute EPs over certain (pre-determined) pairs of network nodes; these pre-distributed EPs can then be used to generate EPs for the requested pairs, when needed, with lower generation latency. For such an pre-distribution approach to be most effective, we need to address an optimization problem of selection of node-pairs where the EPs should be pre-distributed to minimize the generation latency of expected EP requests, under a given cost constraint. In this paper, we appropriately formulate the above optimization problem and design two efficient algorithms, one of which is a greedy approach based on an approximation algorithm for a special case. Via extensive evaluations over the NetSquid simulator, we demonstrate the effectiveness of our approach and developed techniques; we show that our developed algorithms outperform a naive approach by up to an order of magnitude.

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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