ANALYSIS OF RANDOM NUMBER GENERATORS USING MONTE-CARLO SIMULATION

Monte Carlo simulation is one of the main applications involving the u se of random number generators. It is also one of the best methods of testing the randomness properties of such generators, by comparing res ults of simulations using different generators with each other, or wit h analytic results. Here we compare the performance of some popular ra ndom number generators by high precision Monte Carlo simulation of the 2-d Ising model, for which exact results are known, using the Metropo lis, 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.