Additive congruential pseudo-random number generators

Pseudo-Random Number Generators

The first option here is not easy. Some pieces of data of this kind exist, for example from the decay of radioactive elements, but generally generation is slow and you cannot get the quantity of random numbers you require for modern applications. The second option here is what I’ll talk about today. Algorithms of this type are called “PseudoRandom Number Generators” (PRNGs). Many bad algorithms...

Criterion of Spectral Test for Linear Congruential Random Number Generators

The criterion issue of spectral test in a linear congruential random number generator is considered. In this paper, we report on four variants of the normalized spectral test, measured both relative to either a theoretical or exact lower bound and aggregative to either a worst-case or average-case method. Computer exhaustive searches are conducted to evaluate and compare their statistical behav...

Entropy of pseudo-random-number generators.

Since the work of Phys. Rev. Lett. 69, 3382 (1992)]] some pseudo-random-number generators are known to yield wrong results in cluster Monte Carlo simulations. In this contribution the fundamental mechanism behind this failure is discussed. Almost all random-number generators calculate a new pseudo-random-number x(i) from preceding values, x(i) =f( x(i-1), x(i-2), ..., x(i-q) ). Failure of these...

On Quaternionic Pseudo-Random Number Generators

Class of Trustworthy Pseudo-Random Number Generators

With the widespread use of communication technologies, cryptosystems are therefore critical to guarantee security over open networks as the Internet. Pseudo-random number generators (PRNGs) are fundamental in cryptosystems and information hiding schemes. One of the existing chaos-based PRNGs is using chaotic iterations schemes. In prior literature, the iterate function is just the vectorial boo...