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[[Low-discrepancy sequences]] are often used instead of random sampling from a space as they ensure even coverage and normally have a faster order of convergence than Monte Carlo simulations using random or pseudorandom sequences. Methods based on their use are called [[quasi-Monte Carlo method]]s.
In an effort to assess the impact of random number quality on Monte Carlo simulation outcomes, astrophysical researchers tested cryptographically-secure pseudorandom numbers generated via Intel's [[RDRAND]] instruction set, as compared to those derived from algorithms, like the [[Mersenne Twister]], in Monte Carlo simulations of radio flares from [[brown dwarfs]]. RDRAND is the closest pseudorandom number generator to a true random number generator.{{cn}} No statistically significant difference was found between models generated with typical pseudorandom number generators and RDRAND for trials consisting of the generation of 10<sup>7</sup> random numbers.<ref>{{cite journal|author-last1=Route |author-first1=Matthew |title=Radio-flaring Ultracool Dwarf Population Synthesis |journal=The Astrophysical Journal |date=August 10, 2017 |volume=845 |issue=1 |page=66 |doi=10.3847/1538-4357/aa7ede |arxiv=1707.02212 |bibcode=2017ApJ...845...66R |s2cid=118895524 |doi-access=free }}</ref>
=== Monte Carlo simulation versus "what if" scenarios ===
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