Algorithmic advances based on low-discrepancy point sets.

In the past decade a lot of theory has been developed on the computability of high-dimensional integrals. This is still a very active research area. This project will mainly concentrate on computational techniques for multivariate integrals based on low-discrepancy point sets, and builds on our current expertise. These techniques are called quasi-Monte Carlo methods. The aim of this research project is to investigate shortcomings of existing computational techniques and to develop new quasi-Monte Carlo algorithms tailored for specific problems.

Keywords:numerical integration, quadrature, quasi-Monte Carlo, cubature

Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences