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arXiv 2408.04566quant-ph
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多输入多输出量子场景中的随机性与非局域性

Randomness versus Nonlocality in Multi-input and Multi-output Quantum Scenario

Chao Zhang, Yi Li, Xiao-Min Hu, Yu Xiang, Chuan-Feng Li, Guang-Can Guo, Jordi Tura, Qihuang Gong, Qiongyi He, Bi-Heng Liu

AI总结:

该研究厘清量子随机性认证所需的最小非局域资源:证明任意两输入贝尔不等式违反是充要条件,但多输入情形不充分;通过高维光子实验比较两类多输入多输出贝尔不等式,揭示随机性与非局域性的内在联系,并实现每光子对1.867±0.018比特的私密随机数生成率。

摘要:

基于贝尔非局域性的设备无关随机性认证不需要对设备做任何假设,因此能提供充分的安全性。已有大量工作致力于证明非局域性对于产生量子随机性是必要的,但随机数生成所需的最小资源尚未被厘清。在此,我们首先证明并通过实验演示:违反任意两输入贝尔不等式对于认证随机性既是必要条件也是充分条件;然而,在多输入情形下,这一充分性不再成立,导致某些态表现出贝尔非局域性却不具备认证随机性的能力。我们在高维光子系统中考察了两类典型的多输入多输出贝尔不等式,即面不等式和Salavrakos-Augusiak-Tura-Wittek-Acín-Pironio贝尔不等式,并观察到违反后者总能认证随机性,而前者并非如此。在3输入4输出的Salavrakos-Augusiak-Tura-Wittek-Acín-Pironio贝尔不等式场景下,获得了每光子对1.867±0.018比特的私密随机数生成率。我们的工作揭示了随机性与非局域性之间的内在联系,并有效提升了设备无关随机数生成等任务的性能。

英文摘要:

Device-independent randomness certification based on Bell nonlocality does not require any assumptions about the devices and therefore provides adequate security. Great effort has been made to demonstrate that nonlocality is necessary for generating quantum randomness, but the minimal resource required for random number generation has not been clarified. Here we first prove and experimentally demonstrate that violating any two-input Bell inequality is both necessary and sufficient for certifying randomness, however, for the multi-input cases, this sufficiency ceases to apply, leading to certain states exhibiting Bell nonlocality without the capability to certify randomness. We examine two typical classes of Bell inequalities with multi-input and multi-output, the facet inequalities and Salavrakos-Augusiak-Tura-Wittek-Acín-Pironio Bell inequalities, in the high-dimensional photonic system, and observe the violation of the latter one can always certify randomness which is not true for the former. The private randomness with a generation rate of 1.867\pm0.018 bits per photon pair is obtained in the scenario of Salavrakos-Augusiak-Tura-Wittek-Acín-Pironio Bell inequalities with 3-input and 4-output. Our work unravels the internal connection between randomness and nonlocality, and effectively enhances the performance of tasks such as device-independent random number generation.

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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