Improvementalgorithmofrandomnumbersgeneratorsusedintensively on simulation of stochastic processes

Revista Cubana de Ciencias Informáticas

卷:8

Giuseppe B. Suffritti¹  Jorge Gulín González²  Edisel Navas Conyedo³  Carlos Torres Pupo³ 

[1] Dipartimento di Chimica, Università de glistudi di Sassari, and Consorzio Ineruniversitario Nazionale per la Scienzae Tecnologiade i Materiali (INSTM), Unità di ricerca di Sassari, Via Vienna, 2, I-07100 Sassari, Italy;

[2] Dirección de Investigaciones. Universidad de las Ciencias Informáticas, Carretera a San Antonio de los Baños, km2½, Torrens, Boyeros, La Habana, Cuba. CP.: 19370;

[3] Grupo de Matemática y Física Computacional. Universidad de las Ciencias Informáticas, Carretera a San Antonio delos Baños, km 2½, Torrens, Boyeros, La Habana, Cuba. CP.: 19370;

关键词: Diffusion;    random walk;    langevin’s dynamical equation;    random number generators;    stochastic processes;   

DOI  :  

来源: DOAJ

【 摘 要 】

Choiceofeffectiveandefficientalgorithmsforgenerationofrandomnumbersisakeyprobleminsimulationsof stochastic processes; diffusion among them. The random walk model and the Langevin’sdynamical equation are the simplestwaystostudycomputationallythediffusion.Bothmodels,inthenon-interactingfreeparticles approximation, are used to test the quality of the random number generators which will be used in more complex computationalsimulations.Inprinciple,generationofrandomnumbersviacomputersisimpossiblebecause computers work through determinist algorithms; however, there are determinist generators which generate sequences of numbers that for practical applications couldbe considered random. In the present paper we present a improve algorithmrandomnumbergeneratorobtainedfromacombinationofthosereportedbyNumericalRecipes,GNU ScientificLibrary,andthatusedbyLinuxoperatingsystem(basedonhardware).Theresultsobtainedusingour 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.

【 授权许可】

Unknown