AI 中文总结
针对量子网络中多对感知保真度的速率分配问题，证明三类速率分配问题为NP难，提出FPTAS求解其优化版本，实验验证了方案的有效性。
AI 中文摘要
量子网络中的纠缠分发必须同时考虑有限的链路容量、概率性纠缠交换以及异构链路保真度。本文研究量子网络中多对感知保真度的速率分配问题，构建三类速率分配问题：速率和、受最小速率约束的速率和，以及最大最小公平性。现有工作仅研究了速率和问题的特殊情况，即所有链路保真度相同，该情况存在多项式时间算法。本文证明上述三类问题均为NP难问题，随后研究其优化版本，即在吞吐量或公平性约束下最大化最小端到端保真度，并为这些优化问题提出完全多项式时间近似方案（FPTAS）。在随机生成的网络上开展的实验验证了所提方案的计算有效性。
英文摘要
Entanglement distribution in quantum networks must jointly account for limited link capacities, probabilistic entanglement swapping, and heterogeneous link fidelities. In this paper, we study multi-pair fidelity-aware rate allocation in quantum networks. We formulate three rate-allocation problems: rate sum, rate sum subject to minimum-rate constraints, and max-min fairness. Prior work has studied a special case of the rate sum problem, where all links have identical fidelity. This special case admits a polynomial-time algorithm. We prove that all three problems are NP-hard. We then study optimization versions of these problems which maximize the minimum end-to-end fidelity subject to throughput or fairness requirements. We present fully polynomial-time approximation schemes (FPTAS) for solving these optimization problems. Experiments on randomly generated networks demonstrate the computational effectiveness of the proposed schemes.
