Pseudo-random-number generators and the square site percolation threshold

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...

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...

Sponge-Based Pseudo-Random Number Generators

This paper proposes a new construction for the generation of pseudo-random numbers. The construction is based on sponge functions and is suitable for embedded security devices as it requires few resources. We propose a model for such generators and explain how to define one on top of a sponge function. The construction is a novel way to use a sponge function, and inputs and outputs blocks in a ...