scholarly journals Advanced Statistical Testing of Quantum Random Number Generators

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 886 ◽  
Author(s):  
Aldo Martínez ◽  
Aldo Solis ◽  
Rafael Díaz Hernández Rojas ◽  
Alfred U'Ren ◽  
Jorge Hirsch ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Methods ◽  
Random Number ◽  
Quantum States ◽  
Statistical Testing ◽  
Random Numbers ◽  
Simple Method ◽  
Random Number Generators ◽  
Random Sequences ◽  
Natural Laws

Pseudo-random number generators are widely used in many branches of science, mainly in applications related to Monte Carlo methods, although they are deterministic in design and, therefore, unsuitable for tackling fundamental problems in security and cryptography. The natural laws of the microscopic realm provide a fairly simple method to generate non-deterministic sequences of random numbers, based on measurements of quantum states. In practice, however, the experimental devices on which quantum random number generators are based are often unable to pass some tests of randomness. In this review, we briefly discuss two such tests, point out the challenges that we have encountered in experimental implementations and finally present a fairly simple method that successfully generates non-deterministic maximally random sequences.

Pseudorandom Number Generators

2017 ◽  
pp. 1-25
Keyword(s):  
Random Number ◽  
Pseudorandom Number ◽  
Random Numbers ◽  
Pseudorandom Sequences ◽  
Random Number Generators ◽  
Random Sequences ◽  
Pseudorandom Number Generators ◽  
Pseudo Random Number

In this chapter, the author considers existing methods and means of forming pseudo-random sequences of numbers and also are described the main characteristics of random and pseudorandom sequences of numbers. The main theoretical aspects of the construction of pseudo-random number generators are considered. Classification of pseudorandom number generators is presented. The structures and models of the most popular pseudo-random number generators are considered, the main characteristics of generators that affect the quality of the formation of pseudorandom bit sequences are described. The models of the basic mathematical generators of pseudo-random numbers are considered, and also the principles of building hardware generators are presented.

scholarly journals Design of True Random Number Circuit with Controllable Frequency

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1517
Author(s):  
Xinsheng Wang ◽  
Xiyue Wang
Keyword(s):  
Random Number ◽  
Noise Source ◽  
State Of The Art ◽  
Building Blocks ◽  
Encryption Algorithm ◽  
Random Numbers ◽  
Random Number Generators ◽  
Random Telegraph Noise ◽  
Telegraph Noise ◽  
Novel Method

True random number generators (TRNGs) have been a research hotspot due to secure encryption algorithm requirements. Therefore, such circuits are necessary building blocks in state-of-the-art security controllers. In this paper, a TRNG based on random telegraph noise (RTN) with a controllable rate is proposed. A novel method of noise array circuits is presented, which consists of digital decoder circuits and RTN noise circuits. The frequency of generating random numbers is controlled by the speed of selecting different gating signals. The results of simulation show that the array circuits consist of 64 noise source circuits that can generate random numbers by a frequency from 1 kHz to 16 kHz.

scholarly journals Enhancing the operational efficiency of quantum random number generators

2021 ◽  
Vol 13 (2) ◽  
pp. 10-18
Author(s):  
Botond L. Márton ◽  
Dóra Istenes ◽  
László Bacsárdi
Keyword(s):  
Random Number ◽  
Statistical Tests ◽  
Practical Implementation ◽  
Random Numbers ◽  
Random Number Generators ◽  
Original Source ◽  
Negative Effect ◽  
Quantum Phenomena ◽  
The Right

Random numbers are of vital importance in today’s world and used for example in many cryptographical protocols to secure the communication over the internet. The generators producing these numbers are Pseudo Random Number Generators (PRNGs) or True Random Number Generators (TRNGs). A subclass of TRNGs are the Quantum based Random Number Generators (QRNGs) whose generation processes are based on quantum phenomena. However, the achievable quality of the numbers generated from a practical implementation can differ from the theoretically possible. To ease this negative effect post-processing can be used, which contains the use of extractors. They extract as much entropy as possible from the original source and produce a new output with better properties. The quality and the different properties of a given output can be measured with the help of statistical tests. In our work we examined the effect of different extractors on two QRNG outputs and found that witg the right extractor we can improve their quality.

Improving Random Number Generators in the Monte Carlo simulations via twisting and combining

2008 ◽  
Vol 178 (6) ◽  
pp. 401-408 ◽  
Author(s):  
Lih-Yuan Deng ◽  
Rui Guo ◽  
Dennis K.J. Lin ◽  
Fengshan Bai
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Random Number ◽  
Random Number Generators
Sign in / Sign up

Export Citation Format

Share Document