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1.中国科学技术大学 微电子学院,安徽 合肥 230026
2.中国科学院大学 材料与光电研究中心,吉林 长春 130033
3.中国科学院 长春光学精密机械与物理研究所 发光学及应用国家重点实验室,吉林 长春 130033
[ "余恒炜 (1992-),男,安徽池州人,硕士研究生,主要从事光电探测器及其读出电路方面的研究。E-mail:yhw520@mail.ustc.edu.cn" ]
黎大兵(1975-),男,湖北通城人,研究员,博士生导师,1998年、2001年于吉林大学分别获得学士、硕士学位,2004年于中国科学院半导体所获得博士学位,主要从事AlGaN基宽禁带半导体光电材料与器件的研究。E-mail: lidb@ciomp.ac.cn LI Da-bing, E-mail: lidb@ciomp.ac.cn
收稿日期:2018-12-11,
录用日期:2019-1-29,
纸质出版日期:2019-07-15
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余恒炜, 孙晓娟, 王星辰, 等. 量子随机数高斯噪声信号发生器[J]. 光学 精密工程, 2019,27(7):1492-1499.
Heng-wei YU, Xiao-juan SUN, Xing-chen WANG, et al. Quantum random number Gaussian noise signal generator[J]. Optics and precision engineering, 2019, 27(7): 1492-1499.
余恒炜, 孙晓娟, 王星辰, 等. 量子随机数高斯噪声信号发生器[J]. 光学 精密工程, 2019,27(7):1492-1499. DOI: 10.3788/OPE.20192707.1492.
Heng-wei YU, Xiao-juan SUN, Xing-chen WANG, et al. Quantum random number Gaussian noise signal generator[J]. Optics and precision engineering, 2019, 27(7): 1492-1499. DOI: 10.3788/OPE.20192707.1492.
现有的高斯噪声信号发生器都是采用数学计算的方式生成随机数的,这种方式不能实现真正的随机信号,与实际噪声信号不符。本文提出基于量子随机数的高斯噪声信号发生器,通过单光子探测器对选择路径的光子信号的探测作为随机数的来源,实现基于真随机的高斯噪声信号发生器。将得到的随机数经过WGN高斯算法处理得到高斯噪声信号,在FPGA中使用verilog语言实现。对产生的噪声信号进行幅度谱和功率谱分析,结果表明产生的噪声信号幅度值在0~255之间变化,幅度谱服从高斯分布,噪声信号的功率谱在20 dB上下均匀波动,服从均匀分布,满足高斯白噪声的特性。与现有的噪声信号发生器相比,基于量子随机数的实现方式,其随机数来源清晰,能够做到真正的随机性,为实现真随机数的高斯噪声信号发生器提供了一种简易的方案。
The existing method used to generate Gaussian noise signals is to generate random numbers through mathematical calculation. However
this method cannot achieve a true random signal nor can it match the actual noise signal. In this study
a Gaussian noise signal generator based on a quantum random number is proposed. A single-photon detector detects the photon signal of the selected path as the source of the random number and realizes the Gaussian noise signal generator based on a true random number. The random number is processed by a weighted Girvan-Newman Gaussian algorithm to obtain the Gaussian noise signal
which is implemented using the Verilog language in a field programmable gate array. The results show that the amplitude of the generated noise signal varies from 0 to 255. A statistical analysis of the amplitude spectrum obeys the Gaussian distribution. The power spectrum of the noise signal fluctuates uniformly at approximately 20 dB and follows a uniform distribution
thus satisfying the characteristics of the Gaussian white noise. Compared with existing methods based on quantum random numbers
the source of the random number is distinct in the present case
and the proposed generator can achieve real randomness. A simple scheme for realizing a true random number for a Gaussian noise signal generator is therefore presented.
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