English

Tusn\'ady's problem, the transference principle, and non-uniform QMC sampling

Combinatorics 2017-03-20 v1 Computational Complexity Numerical Analysis Probability

Abstract

It is well-known that for every N1N \geq 1 and d1d \geq 1 there exist point sets x1,,xN[0,1]dx_1, \dots, x_N \in [0,1]^d whose discrepancy with respect to the Lebesgue measure is of order at most (logN)d1N1(\log N)^{d-1} N^{-1}. In a more general setting, the first author proved together with Josef Dick that for any normalized measure μ\mu on [0,1]d[0,1]^d there exist points x1,,xNx_1, \dots, x_N whose discrepancy with respect to μ\mu is of order at most (logN)(3d+1)/2N1(\log N)^{(3d+1)/2} N^{-1}. The proof used methods from combinatorial mathematics, and in particular a result of Banaszczyk on balancings of vectors. In the present note we use a version of the so-called transference principle together with recent results on the discrepancy of red-blue colorings to show that for any μ\mu there even exist points having discrepancy of order at most (logN)d12N1(\log N)^{d-\frac12} N^{-1}, which is almost as good as the discrepancy bound in the case of the Lebesgue measure.

Keywords

Cite

@article{arxiv.1703.06127,
  title  = {Tusn\'ady's problem, the transference principle, and non-uniform QMC sampling},
  author = {Christoph Aistleitner and Dmitriy Bilyk and Aleksandar Nikolov},
  journal= {arXiv preprint arXiv:1703.06127},
  year   = {2017}
}

Comments

11 pages

R2 v1 2026-06-22T18:49:08.139Z