A Gaussian-Distributed Quantum Random Number Generator Using Vacuum Shot Noise

• Main Authors: Min Huang, Ziyang Chen, Yichen Zhang, Hong Guo
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Entropy
• Subjects: quantum random number generator; vacuum fluctuation; Gaussian distribution; goodness of fit test
• Online Access: https://www.mdpi.com/1099-4300/22/6/618

Among all the methods of extracting randomness, quantum random number generators are promising for their genuine randomness. However, existing quantum random number generator schemes aim at generating sequences with a uniform distribution, which may not meet the requirements of specific applications such as a continuous-variable quantum key distribution system. In this paper, we demonstrate a practical quantum random number generation scheme directly generating Gaussian distributed random sequences based on measuring vacuum shot noise. Particularly, the impact of the sampling device in the practical system is analyzed. Furthermore, a related post-processing method, which maintains the fine distribution and autocorrelation properties of raw data, is exploited to extend the precision of generated Gaussian distributed random numbers to over 20 bits, making the sequences possible to be utilized by the following system with requiring high precision numbers. Finally, the results of normality and randomness tests prove that the generated sequences satisfy Gaussian distribution and can pass the randomness testing well.