Correlation defense for quantum randomness

N.S. Perminov^a,b , O.I. Bannik^a , D.U. Tarankova^a , R.R. Nigmatullin^a

^aKazan National Research Technical University named after A.N. Tupolev, Kazan, 420111 Russia

^bZavoisky Physical-Technical Institute, FRC Kazan Scientific Center, Russian Academy of Sciences, Kazan, 420029 Russia

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DOI: 10.26907/2541-7746.2020.1.98-106

For citation: Perminov N.S., Bannik O.I., Tarankova D.Yu., Nigmatullin R.R. Correlation defense for quantum randomness. Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 2020, vol. 162, no. 1, pp. 98–106. doi: 10.26907/2541-7746.2020.1.98-106.

Для цитирования: Perminov N.S., Bannik O.I., Tarankova D.Yu., Nigmatullin R.R. Correlation defense for quantum randomness // Учен. зап. Казан. ун-та. Сер. Физ.-матем. науки. – 2020. – Т. 162, кн. 1. – С. 98–106. – doi: 10.26907/2541-7746.2020.1.98-106.

Abstract

New nonparametric methods were developed for verification and monitoring of quantum randomness based on the ranged correlation function (RCF) and a sequence of the ranged amplitudes (SRA). RCF analysis of different topology subsamples from the raw data of the prototype of a quantum random number generator on homodyne detection was carried out. It was shown that in the real system there are weak local regression relations, for which it is possible to introduce a robust criterion of significance. Precise SRA identification of the long samples statistics was carried out. The obtained results extend the traditional entropy methods of the useful randomness analysis and open the way for creation of new strict quality quantum standards and defense for physical random number generators.

Keywords: quantum information, ranged correlation functions, RCF defense, quantum randomness, physical random number generator

Acknowledgments. The research of noise in the area of photonics and quantum technologies was funded by the Government of the Russian Federation (project no. 14.Z50.31.0040; Feb. 17, 2017 (experimental part)). The work was also supported in part by the grant for young scientists of the Republic of Tatarstan (project no. 06-36-ts-G 2018 (theoretical part)).

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