ACORN—A new method for generating sequences of uniformly distributed Pseudo-random numbers
Journal of Computational Physics
Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
TestU01: A C library for empirical testing of random number generators
ACM Transactions on Mathematical Software (TOMS)
The additive congruential random number generator-A special case of a multiple recursive generator
Journal of Computational and Applied Mathematics
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Additive Congruential Random Number (ACORN) generators represent an approach to generating uniformly distributed pseudo-random numbers that is straightforward to implement efficiently for arbitrarily large order and modulus; if it is implemented using integer arithmetic, it becomes possible to generate identical sequences on any machine. This paper briefly reviews existing results concerning ACORN generators and relevant theory concerning sequences that are well distributed mod 1 in k dimensions. It then demonstrates some new theoretical results for ACORN generators implemented in integer arithmetic with modulus M=2^@m showing that they are a family of generators that converge (in a sense that is defined in the paper) to being well distributed mod 1 in k dimensions, as @m=log"2M tends to infinity. By increasing k, it is possible to increase without limit the number of dimensions in which the resulting sequences approximate to well distributed. The paper concludes by applying the standard TestU01 test suite to ACORN generators for selected values of the modulus (between 2^6^0 and 2^1^5^0), the order (between 4 and 30) and various odd seed values. On the basis of these and earlier results, it is recommended that an order of at least 9 be used together with an odd seed and modulus equal to 2^3^0^p, for a small integer value of p. While a choice of p=2 should be adequate for most typical applications, increasing p to 3 or 4 gives a sequence that will consistently pass all the tests in the TestU01 test suite, giving additional confidence in more demanding applications. The results demonstrate that the ACORN generators are a reliable source of uniformly distributed pseudo-random numbers, and that in practice (as suggested by the theoretical convergence results) the quality of the ACORN sequences increases with increasing modulus and order.