ANALYSIS OF RANDOM NUMBER GENERATORS USING MONTE CARLO SIMULATION

Author:

CODDINGTON P.D.1

Affiliation:

1. Northeast Parallel Architectures Center, Syracuse University 111 College Place, Syracuse, NY 13244, U.S.A.

Abstract

Monte Carlo simulation is one of the main applications involving the use of random number generators. It is also one of the best methods of testing the randomness properties of such generators, by comparing results of simulations using different generators with each other, or with analytic results. Here we compare the performance of some popular random number generators by high precision Monte Carlo simulation of the 2-d Ising model, for which exact results are known, using the Metropolis, Swendsen-Wang, and Wolff Monte Carlo algorithms. Many widely used generators that perform well in standard statistical tests are shown to fail these Monte Carlo tests.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

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