Wednesday, 13th September 2023


The star-discrepancy measures how well a point set is distributed in the unit cube with respect to the uniform measure. It plays a role in the construction of uniformly distributed points and pseudo-random number generators. A result from 2001 in Acta Arithmetica by Heinrich et al asserts that there exists a point set with N points in the d dimensional unit cube whose star-discrepancy is bounded by $C \sqrt{d/N}$. The proof is based on concentration of measure and is not constructive. In this talk we discuss how the inverse of the star-discrepancy problem is related to pseudo-random number generators and driver sequences for Markov chain Monte Carlo and discuss recent progress on explicit constructions for similar problems.


Josef Dick

Research area

Number Theory




Wednesday 13 Sep 2023, 3.00 pm


RC-4082 (Anita B. Lawrence Center)