collaborators

8 papers

math.NA2026

The -Discrepancy with Nonnegative Weights Suffers from the Curse of Dimensionality

Josef Dick

We prove that the -discrepancy with arbitrary nonnegative weights suffers from the curse of dimensionality. More precisely, for every and $d \in \mathb…

math.NA2026

Spherical Cap Discrepancy -- Blessing of Dimensionality and a Balanced Large-Cap Variant

Johann S. Brauchart, Josef Dick, Friedrich Pillichshammer

We prove that the information complexity (i.e., the inverse) of the classical spherical cap discrepancy on the -dimensional sphere decreases with dimension…

math.NA2026

Worst-case -approximation of periodic functions using median lattice algorithms

Zexin Pan, Mou Cai, Josef Dick +2

We study the worst-case approximation of multivariate periodic functions from the weighted Korobov space with smoothness in the Lebesgue norm

math.NT2026

On the quasi-uniformity properties of quasi-Monte Carlo point sets and sequences -- Part I: Lattices and Kronecker sequences

Josef Dick, Takashi Goda, Gerhard Larcher +2

The discrepancy of a point set quantifies how well the points are distributed, with low-discrepancy point sets demonstrating exceptional uniform distribution properties. Such sets…

math.NT2026

On the quasi-uniformity properties of quasi-Monte Carlo point sets and sequences -- Part II: digital nets and sequences

Josef Dick, Takashi Goda, Kosuke Suzuki

We study the quasi-uniformity properties of digital nets, a class of quasi-Monte Carlo point sets. Quasi-uniformity is a space-filling property used for instance in experimental de…

math.NA2026

The inverse of the star discrepancy of a union of randomly shifted Korobov rank-1 lattice point sets depends polynomially on the dimension

Jiarui Du, Josef Dick

The inverse of the star discrepancy, , defined as the minimum number of points required to achieve a star discrepancy of at most in dimension , is known to depend…