George Forsythe's last paper
arXiv:1005.09091 citationsh-index: 46
Originality Synthesis-oriented
AI Analysis
Historical survey of random number generation techniques for computational scientists.
The paper recounts von Neumann's exponential sampling method, Forsythe's generalization to densities exp(-G(x)), and the author's refinement for efficient normal random number generation, with later developments noted.
We describe von Neumann's elegant idea for sampling from the exponential distribution, Forsythe's generalization for sampling from a probability distribution whose density has the form exp(-G(x)), where G(x) is easy to compute (e.g. a polynomial), and my refinement of these ideas to give an efficient algorithm for generating pseudo-random numbers with a normal distribution. Later developments are also mentioned.