Improvement algorithm of random numbers generators used intensively on simulation of stochastic processes

Choice of effective and efficient algorithms for generation of random numbers is a key problem in simulations of stochastic processes; diffusion among them. The random walk model and the Langevin’s dynamical equation are the simplest ways to study computationally the diffusion. Both models, in the non-interacting free particles approximation, are used to test the quality of the random number generators which will be used in more complex computational simulations. In principle, generation of random numbers via computers is impossible because computers work through determinist algorithms; however, there are determinist generators which generate sequences of numbers that for practical applications could be considered random. In the present paper we present a improve algorithm random number generator obtained from a combination of those reported by Numerical Recipes, GNU Scientific Library, and that used by Linux operating system (based on hardware). The results obtained using our computational tool allows to improve the random characteristics of any pseudorandom generator, and the subsequent improving of the accuracy and efficiency of computational simulations of stochastic processes