English

Optimal numerical integration and approximation of functions on $\mathbb{R}^d$ equipped with Gaussian measure

Numerical Analysis 2023-06-21 v3 Numerical Analysis

Abstract

We investigate the numerical approximation of integrals over Rd\mathbb{R}^d equipped with the standard Gaussian measure γ\gamma for integrands belonging to the Gaussian-weighted Sobolev spaces Wpα(Rd,γ)W^\alpha_p(\mathbb{R}^d, \gamma) of mixed smoothness αN\alpha \in \mathbb{N} for 1<p<1 < p < \infty. We prove the asymptotic order of the convergence of optimal quadratures based on nn integration nodes and propose a novel method for constructing asymptotically optimal quadratures. As for related problems, we establish by a similar technique the asymptotic order of the linear, Kolmogorov and sampling nn-widths in the Gaussian-weighted space Lq(Rd,γ)L_q(\mathbb{R}^d, \gamma) of the unit ball of Wpα(Rd,γ)W^\alpha_p(\mathbb{R}^d, \gamma) for 1q<p<1 \leq q < p < \infty and q=p=2q=p=2.

Keywords

Cite

@article{arxiv.2207.01155,
  title  = {Optimal numerical integration and approximation of functions on $\mathbb{R}^d$ equipped with Gaussian measure},
  author = {Dinh Dũng and Van Kien Nguyen},
  journal= {arXiv preprint arXiv:2207.01155},
  year   = {2023}
}

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23 pages