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arXiv 1012.1960quant-ph
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值不确定性证明的量子随机数Generator

A Quantum Random Number Generator Certified by Value Indefiniteness

Alastair A. Abbott, Cristian S. Calude, Karl Svozil

摘要:

本文提出了一种利用Bell单态纠缠光子对的量子随机数发生器(QRNG),并通过数值不确定性得到了明确的证明。虽然“真正的随机性”在数学上是不可能的,但数值不确定性的证明确保了量子随机比特在最强意义上是不可计算的。这是第一个QRNG设置,其中物理原理(Kochen-Specker值不确定性)保证没有单个量子比特可以被经典计算(再现和验证),这是逐位物理不可预测性的数学形式。详细讨论了各种实验缺陷的影响,特别是那些与检测器效率,上下文对齐和位之间的时间相关性。该分析在很大程度上与基于分束器的任何QRNG的构造相关。通过在最大未对准的上下文中测量两个纠缠光子并利用获得两个位串而不是一个位串的事实,可以应用更有效和鲁棒的去偏置技术。一个强大的和有效的程序的基础上XOR的位串在一起-基本上使用一个作为一个一次性垫的其他-提出了提取随机位的实验缺陷的存在下,以及一个更有效的修改冯诺依曼程序相同的任务。还讨论了一些悬而未决的问题。

英文摘要:

In this paper we propose a quantum random number generator (QRNG) which utilizes an entangled photon pair in a Bell singlet state, and is certified explicitly by value indefiniteness. While "true randomness" is a mathematical impossibility, the certification by value indefiniteness ensures the quantum random bits are incomputable in the strongest sense. This is the first QRNG setup in which a physical principle (Kochen-Specker value indefiniteness) guarantees that no single quantum bit produced can be classically computed (reproduced and validated), the mathematical form of bitwise physical unpredictability. The effects of various experimental imperfections are discussed in detail, particularly those related to detector efficiencies, context alignment and temporal correlations between bits. The analysis is to a large extent relevant for the construction of any QRNG based on beam-splitters. By measuring the two entangled photons in maximally misaligned contexts and utilizing the fact that two rather than one bitstring are obtained, more efficient and robust unbiasing techniques can be applied. A robust and efficient procedure based on XORing the bitstrings together---essentially using one as a one-time-pad for the other---is proposed to extract random bits in the presence of experimental imperfections, as well as a more efficient modification of the von Neumann procedure for the same task. Some open problems are also discussed.

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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