Random number generators: Pretty good ones are easy to find

  title={Random number generators: Pretty good ones are easy to find},
  author={Clifford A. Pickover},
  journal={The Visual Computer},
  • C. Pickover
  • Published 1 July 1995
  • Computer Science
  • The Visual Computer
A popular conception is that random number generators are very difficult to build. I informally discuss some easily programmed, easily remembered, random number generators. Simple graphical techniques are introduced for assessing the quality of the generators with little training. To encourage reader involvement, computational recipes are included. 

Multiplicative congruential generators, their lattice structure, its relation to lattice-sublattice transformations and applications in crystallography.

From an analysis of similar sublattices with hexagonal and square symmetry it is conjectured that the cycle structure of the permutation has its crystallographic counterpart in the description of crystallographic orbits.



Random number generators: good ones are hard to find

Practical and theoretical issues are presented concerning the design, implementation, and use of a good, minimal standard random number generator that will port to virtually all systems.

Some portable very-long-period random number generators

It is found that a proposed random number generator ran2 is a good one, but a number of generators are presented that are at least as good and are simpler, much faster, and with periods ‘‘billions and billions’’ of times longer.

A random number generator based on the logit transform of the logistic variable

A nonperiodic random number generator, which is based on the logistic equation, is presented and the associated algorithm can be easily utilized in laboratory exercises, classroom demonstrations, and software written for stochastic modeling purposes.

Monte Carlo simulations: Hidden errors from "good" random number generators.

This work shows how the Wolff algorithm, now accepted as the best cluster-flipping Monte Carlo algorithm for beating ``critical slowing down,'' can yield incorrect answers due to subtle correlations in ``high quality'' random number generators.

A pseudorandom number generator

A simple deterministic algorithm produces a finite sequence which exhibits three iniportant statistical properties. This algo rithm should prove to be useful in simulating some random processes.

Graphical representation of pseudorandom sequences

  • T. Richards
  • Computer Science, Mathematics
    Comput. Graph.
  • 1989