# RANLUX: A Fortran implementation of the high-quality pseudorandom number generator of Lüscher

@article{James1994RANLUXAF, title={RANLUX: A Fortran implementation of the high-quality pseudorandom number generator of L{\"u}scher}, author={F. James}, journal={Computer Physics Communications}, year={1994}, volume={79}, pages={111-114} }

Abstract Following some remarks on the quality of pseudorandom number generators commonly used in Monte Carlo calculations in computational physics, we offer a portable Fortran 77 implementation of a high-quality generator called RANLUX (for LUXury RANdom numbers), using the algorithm of Martin Luscher described in an accompanying article. The implementation allows the user to select different quality or luxury levels, where higher quality requires somewhat longer computing time for the… Expand

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#### References

SHOWING 1-5 OF 5 REFERENCES

A Review of Pseudorandom Number Generators

- Mathematics
- 1990

This is a brief review of the current situation concerning practical pseudorandom number generation for Monte Carlo calculations. The conclusion is that pseudorandom number generators with the… Expand

Pseudorandom number generators for personal computers

- Computer Science
- 1993

The pseudorandom number generators that are provided by several popular PC Fortran compilers are tested and timed, and compared to two algorithms that were previously published in this journal. Expand

A portable high-quality random number generator for lattice field theory simulations

- Mathematics, Physics
- 1994

Abstract The theory underlying a proposed random number generator for numerical simulations in elementary particle physics and statistical mechanics is discussed. The generator is based on an… Expand

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

- Computer Science, Medicine
- Physical review letters
- 1992

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. Expand