Experimental solutions to the high-dimensional mean king’s problem

Tareq Jaouni, Xiaoqin Gao, Sören Arlt, Mario Krenn, and Ebrahim Karimi
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引用次数: 1

Abstract

Vaidman, Aharanov, and Albert [Phys. Rev. Lett. 58(14), 1385 (1987) [CrossRef] ] put forward a puzzle called the mean king’s problem (MKP) that can be solved only by harnessing quantum entanglement. Prime-powered solutions to the problem have been shown to exist, but they have not yet been experimentally realized for any dimension beyond two. We propose a general first-of-its-kind experimental scheme for solving the MKP in prime dimensions (D). Our search is guided by the digital discovery framework Pytheus, which finds highly interpretable graph-based representations of quantum optical experimental setups; using it, we find specific solutions and generalize to higher dimensions through human insight. As proof of principle, we present a detailed investigation of our solution for the three-, five-, and seven-dimensional cases. We obtain maximum success probabilities of 82.3%, 56.2%, and 35.5%, respectively. We therefore posit that our computer-inspired scheme yields solutions that implement Alice’s strategy with quantum advantage, demonstrating its promise for experimental implementation in quantum communication tasks.
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高维均值王问题的实验解决方案
Vaidman, Aharanov 和 Albert [Phys.58(14), 1385 (1987) [CrossRef] ]提出了一个名为平均王问题(MKP)的难题,只有利用量子纠缠才能解决。该问题的主要解决方案已被证明是存在的,但尚未在实验中实现二维以上的任何维度。我们提出了一个同类首创的通用实验方案,用于解决质子维度(D)的 MKP 问题。我们的搜索以数字发现框架 Pytheus 为指导,该框架可以找到量子光学实验设置的高度可解释的基于图的表示;利用它,我们可以找到具体的解决方案,并通过人类的洞察力推广到更高维度。作为原理证明,我们对三维、五维和七维情况下的解决方案进行了详细研究。我们获得的最大成功概率分别为 82.3%82.3{\% }、56.2%56.2{/\% } 和 35.5%35.5 {\% }。因此,我们认为我们的计算机启发方案产生的解决方案能以量子优势实现爱丽丝的策略,证明了它在量子通信任务中的实验实现前景。
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