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How do we solve numerical problems efficiently?
Our research includes quasi-Monte Carlo methods, adaptive algorithms, and information based complexity.
This site shares the scholarly activity of Fred Hickernell and his collaborators. We welcome inquiries.
Automatic Quasi-Monte Carlo Algorithms
Automatic Quasi-Monte Carlo Algorithms
Performing simulations with low discrepancy (LD) sequences rather than independent and identically distributed (IID) sequences can improve performance 100 fold. The image on the left shows an LD sequence mimicking a Gaussian distribution.
Stopping criteria for quasi-Monte Carlo simulation automatically determine the sample size needed to achieve the desired error tolerance.
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