Quantum physics random number source.
This product is a well established random number
generation access for many years. The interface is the interface between your
code and the SG100 or SG100 Evo USB. The devices are interchangeable in your
application if you use the PSDK. Example source code for many applications is
The SG100 is
available in two basic packages; Developer and Runtime.
One SG100 Generator.
Runtime Package, Protego SDK (PSDK)
You can purchase a Protego SDK (PSDK) separately. The price is 110 Euros. The kit is available for electronic download after payment. The kit must only be used with genuine Protego products.
For S&H add 53 Euro
Prices and specification subject to change without prior notice.
The simplest statistical test is to check if the SG100 random number strings has about the same number of ones and zeroes. A test program (N1_TEST.EXE, included in Developer Package) is written that counts bytes and bits. The output is given in absolute and relative frequency.
To make comparison easy the difference between a relative frequency of 50% and observed frequency is computed relative to the standard deviation. These values are seldom higher than three, for random output.
Note, that as the program outputs a large number of sigma values, it sometimes happens that a sigma value higher than three is found. This is normal for random strings. If in doubt, accuracy can be increased by counting a longer string.
If we, as an example, count 6,400,000 bytes and find 25,603,990 "one" bits then we have a relative frequency of 0.50007793 Sigma = 1.1 That is 50.008% one bits.
To increase accuracy we count 441,600,000 bytes. We find 1,766,378,269 "one" bits yielding a frequency of 0.49999385 ( Sigma = -0.7) That was very close to 50% "one" bits and 50% "zero" bits. Desperately we can read 1,651,200,000 bytes and count to 6,604,734,712 "one" bits and the frequency is 0.49999506 ( Sigma = -1.1).
pLab load test of the SG100
Research Group of the Institut für Mathematik, Universität Salzburg has
conducted a load test of the SG100™. The report contains commented
simulation results for SG100™. Each page contains the plot of the
truncated Kolmogorov-Smirnov-values and the according
uppeirtail-probabilities for the Load Test'(LT).
The SG100 also passes the Diehard test. The Diehard test, by George Marsaglia, consists of several statistical counts that should have a specified distribution if the input string is random. By comparing observed counts to a theoretical count we can see if a string is random or not.
For a sample of size 500: mean SG100.DAT using bits 6 to 29 1.942
Chisquare with 6 d.o.f. = 2.61 p-value= .143850
observations above are to few to give high accuracy. This problem
originates in that the Diehard program do not adjust the sample sizes
to a larger test file.
Robert Davies test of SG100
Robert Davies have tested hardware random number generators, including the SG100, for a lottery application.
EMC Test Reports
Electrical Characteristics and Measurements — SG100 eBook
diagram of the SG100 circuit is displayed below. To the left we find
You can also
choose to download the test in pdf format
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