On the orthogonality of the Chebyshev–Frolov lattice and applications

On the orthogonality of the Chebyshev–Frolov lattice and applications
复制标题

ChebyshevâFrolov 格子的正交性及其应用

DOI:
10.1007/s00605-017-1078-2
复制
发表时间:
2017
期刊:
Monatshefte für Mathematik
影响因子:
--
通讯作者:
T. Ullrich
T. Ullrich
中科院分区:
--
文献类型:
--
作者:
C. Kacwin;J. Oettershagen;T. Ullrich

文献摘要

参考文献

被引文献

相似文献

我们处理由与切比雪夫多项式的根相关的Vandermonde矩阵生成的格。如果格的维度是2的幂,即所得到的格是Skriganov意义下的容许格。我们证明了这些格是正交的,并且具有具有正交列和不大于2(模数)的项的格表示矩阵。特别地,我们证明了高维上的正交容许格的存在性。正交性属性允许在轴平行方框中有效地枚举这些晶格。因此,它们是Frolov立方公式的实际实现,该公式最近因其在广泛的Besov-Lizorkin-Triebel空间中的最优收敛速度而引起了人们的注意。作为应用,我们有效地枚举了维立方体中的Frolov立方体节点。
We deal with lattices that are generated by the Vandermonde matrices associated to the roots of Chebyshev polynomials. If the dimensiondof the lattice is a power of two, i.e., the resulting lattice is an admissible lattice in the sense of Skriganov. We prove that these lattices are orthogonal and possess a lattice representation matrix with orthogonal columns and entries not larger than 2 (in modulus). In particular, we clarify the existence of orthogonal admissible lattices in higher dimensions. The orthogonality property allows for an efficient enumeration of these lattices in axis parallel boxes. Hence they serve for a practical implementation of the Frolov cubature formulas, which recently drew attention due to their optimal convergence rates in a broad range of Besov–Lizorkin–Triebel spaces. As an application, we efficiently enumerate the Frolov cubature nodes in thed-cubeup to dimension.
有界混合导数函数的 Frolov 体积公式的作用
DOI: 10.1137/15m1014814
发表时间: 2016
期刊: SIAM J. Numer. Anal.
影响因子: --
作者:
M. Ullrich;T. Ullrich
通讯作者: T. Ullrich
DOI: 10.1137/16m106580x
发表时间: 2015-05
期刊: SIAM J. Numer. Anal.
影响因子: --
作者:
T. Kühn;Sebastian Mayer;T. Ullrich
通讯作者: T. Kühn;Sebastian Mayer;T. Ullrich
DOI: 10.1007/0-387-22081-x_7
发表时间: 2020-05
期刊: An Introduction to Probabilistic Number Theory
影响因子: --
作者:
Don Redmond
通讯作者: Don Redmond
DOI: --
发表时间: 2003
影响因子: 1.7
作者:
V. Temlyakov
通讯作者: V. Temlyakov
DOI: --
发表时间: 2016
影响因子: 2.9
作者:
Mario Ullrich
通讯作者: Mario Ullrich