2000 character limit reached
Digital Nets and Sequences for Quasi-Monte Carlo Methods (2207.13802v1)
Published 27 Jul 2022 in math.NA, cs.MS, and cs.NA
Abstract: Quasi-Monte Carlo methods are a way of improving the efficiency of Monte Carlo methods. Digital nets and sequences are one of the low discrepancy point sets used in quasi-Monte Carlo methods. This thesis presents the three new results pertaining to digital nets and sequences: implementing randomized digital nets, finding the distribution of the discrepancy of scrambled digital nets, and obtaining better quality of digital nets through evolutionary computation. Finally, applications of scrambled and non-scrambled digital nets are provided.