论文标题

分布式量子计算的最佳随机资源分配

Optimal Stochastic Resource Allocation for Distributed Quantum Computing

论文作者

Ngoenriang, Napat, Xu, Minrui, Supittayapornpong, Sucha, Niyato, Dusit, Yu, Han, Xuemin, Shen

论文摘要

随着互连的量子计算机的出现,即分布式量子计算(DQC),多个量子计算机现在可以通过量子网络协作以执行大量复杂的计算任务。但是,DQC面临共享量子信息的问题,因为它不能在量子计算机之间克隆或重复。多亏了高级量子力学,量子计算机可以在量子网络上传送量子信息。但是,由于其能力和特性,例如不确定的Qubit Fidelity和量子通道噪声,在DQC中出现了有效量子资源(例如量子计算机和量子通道)的挑战。在本文中,我们提出了基于随机编程的DQC的资源分配方案,以最大程度地降低量子资源的总部署成本。从本质上讲,配制了两阶段随机编程模型,以处理量子计算需求,计算能力和量子网络中的保真度的不确定性。绩效评估表明,提议的方案平衡量子计算机和按需量子计算机利用的有效性和能力,同时最大程度地降低了不确定性下的准备成本的总体成本。

With the advent of interconnected quantum computers, i.e., distributed quantum computing (DQC), multiple quantum computers can now collaborate via quantum networks to perform massively complex computational tasks. However, DQC faces problems sharing quantum information because it cannot be cloned or duplicated between quantum computers. Thanks to advanced quantum mechanics, quantum computers can teleport quantum information across quantum networks. However, challenges to utilizing efficiently quantum resources, e.g., quantum computers and quantum channels, arise in DQC due to their capabilities and properties, such as uncertain qubit fidelity and quantum channel noise. In this paper, we propose a resource allocation scheme for DQC based on stochastic programming to minimize the total deployment cost for quantum resources. Essentially, the two-stage stochastic programming model is formulated to handle the uncertainty of quantum computing demands, computing power, and fidelity in quantum networks. The performance evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers while minimizing the overall cost of provisioning under uncertainty.

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