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实时在线光子随机数生成

Real-time online photonic random number generation.

作者信息

Li Pu, Zhang Jianguo, Sang Luxiao, Liu Xianglian, Guo Yanqiang, Guo Xiaomin, Wang Anbang, Alan Shore K, Wang Yuncai

出版信息

Opt Lett. 2017 Jul 15;42(14):2699-2702. doi: 10.1364/OL.42.002699.

Abstract

We present a real-time scheme for ultrafast random number (RN) extraction from a broadband photonic entropy source. Ultralow jitter mode-locked pulses are used to sample the stochastic intensity fluctuations of the entropy source in the optical domain. A discrete self-delay comparison technology is exploited to quantize the sampled pulses into continuous RN streams directly. This scheme is bias free, eliminates the electronic jitter bottleneck confronted by currently available physical RN generators, and has no need for threshold tuning and post-processing. To demonstrate its feasibility, we perform a proof-of-principle experiment using an optically injected chaotic laser diode. RN streams at up to 7  Gb/s with verified randomness were thereby successfully extracted in real time. With the provision of a photonic entropy source with sufficient bandwidth, the present approach is expected to provide RN generation rates of several tens of gigabits per second.

摘要

我们提出了一种从宽带光子熵源中提取超快随机数(RN)的实时方案。利用超低抖动锁模脉冲在光域中对熵源的随机强度涨落进行采样。采用离散自延迟比较技术直接将采样脉冲量化为连续的随机数流。该方案无偏置,消除了现有物理随机数发生器面临的电子抖动瓶颈,且无需阈值调整和后处理。为证明其可行性,我们使用光注入混沌激光二极管进行了原理验证实验。由此成功实时提取了高达7 Gb/s且随机性经过验证的随机数流。若能提供具有足够带宽的光子熵源,预计本方法可实现每秒数十吉比特的随机数生成速率。

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