Published in:
Physical Review E 67,1 (2003) 016113;
Link to original published article:
http://dx.doi.org/10.1103/PhysRevE.67.016113
Abstract
We present a computational scheme, GRIP (geometric random inner products), for testing the quality of random number generators. The GRIP formalism utilizes geometric probability techniques to calculate the average scalar products of random vectors distributed in geometric objects, such as circles and spheres. We show that these average scalar products define a family of geometric constants which can be used to evaluate the quality of random number generators. We explicitly apply the GRIP tests to several random number generators frequently used in Monte Carlo simulations, and demonstrate a statistical property for good random number generators.
Keywords
monte-carlo simulations
Date of this Version
January 2003