Improvement algorithm of random numbers generators used intensively on simulation of stochastic processes
La
elección de algoritmos eficaces y eficientes para la generación de
números aleatorios es un problema clave en simulaciones de procesos
estocásticos; siendo la difusión uno de ellos. El modelo del caminante
aleatorio y la ecuación dinámica del Langevin son las formas más
sencillas para el estudio computacional de la difusión. Ambos modelos,
donde las partículas no interactúan y se mueven libremente, se utilizan
para probar la calidad de los generadores de números aleatorios que se
van a utilizar en simulaciones computacionales más complejas. En
principio, la generación de números aleatorios a través de ordenadores
es imposible porque los ordenadores funcionan a través de algoritmos
deterministas, sin embargo, se pueden utilizar generadores deterministas
cuyas secuencias de números que para las aplicaciones prácticas podrían
considerarse aleatoria.
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.
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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.
Puede acceder al artículo completo aquí.
You can purchase the full paper here
Si le resulta interesante nuestro trabajo deje su comentario y si puede contribuya con nosotros:
1L7GNWbLR53CvcW3Wn47WPNJrCssqC8EDW
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