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Quantum random number generator

Version 2.5.1 (3.41 KB) by gorka zubia
This code returns a "n" amount of random numbers, which are obtained in real time from the ANU Quantum Random Numbers Server.
5.0
(2)

159 Downloads

Updated Sun, 26 Apr 2020 15:36:46 +0000

From GitHub

View License on GitHub

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Introduction
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The aim of this function is to provide real random numbers for sensitive applications, which cannot accept the pseudorandomness of Matlab's "randperm(N, K)"
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Description
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This function returns a row vector with "n" REAL RANDOM NUMBERS with values between [1-"n"] and NO REPETITION.
These random numbers are generated in real time (Internet connection is needed) from the Australian National University's Quantum Random Numbers Server.
The returned numbers can be "uint8" (0 to 255) or "uint16" (0 to 65,535) type of integers
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Elapsed time
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The function needs a random time to retrieve the asked array of numbers. As an illustration, using a computer with 6 cores, these are the obtained results for different scenarios:
########## Executed command ########## || ########## Elapsed time (s) ##########
>> quantumRandomGenerator( 1, 'uint8') 0.73
>> quantumRandomGenerator( 50, 'uint8') 0.73
>> quantumRandomGenerator( 100, 'uint8') 0.73
>> quantumRandomGenerator( 150, 'uint8') 0.73
>> quantumRandomGenerator( 200, 'uint8') 0.73
>> quantumRandomGenerator( 200, 'uint16') 35.95
>> quantumRandomGenerator( 852, 'uint16') 57.03
>> quantumRandomGenerator(4216, 'uint16') 53.22
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Cite As

gorka zubia (2023). Quantum random number generator (https://github.com/gzubia/quantum-random-number-generator/releases/tag/2.5.1), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
2.5.1

See release notes for this release on GitHub: https://github.com/gzubia/quantum-random-number-generator/releases/tag/2.5.1
2.5.0

Timeout has been set to 'Inf' in order to avoid "time out" errors (line '59').
2.0.0

SOLVED: in line 70 the 'unique' function from Matlab returned the data ordered, destroying the randomness. To solve that, the flag 'stable' has been added

ok_rnd = unique(rnd(rnd<=n),'stable'); % Comprobation that any of the random number
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.