NPAC Technical Report SCCS-526
Analysis of Random Number Generators Using Monte Carlo Simulation
Paul Coddington
Submitted October 14 1993
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.