English

Sparsity for parametric PDEs with log-gamma random inputs and applications

Numerical Analysis 2026-03-17 v1 Numerical Analysis

Abstract

We propose a novel method for establishing the sparsity of the coefficients of the Laguerre generalized polynomial chaos expansion of solutions to parametric elliptic PDEs with log-gamma inputs on R+\mathbb{R}_+^\infty. The established sparsity is quantified by p\ell_p-summability and weighted 2\ell_2-summability of the coefficients. Building on these sparsity results, we derive convergence rates for semi-discrete approximations in the parametric variables. These rates apply to sparse-grid polynomial interpolations, extended least-squares approximations and the associated semi-discrete quadrature rules. Moreover, a counterpart of our method for parametric elliptic PDEs with log-normal inputs yields a significant improvement in the sufficient condition for p\ell_p-summability when the component functions in the log-normal representation of the parametric diffusion coefficients have global support, compared with results obtained in prior works.

Keywords

Cite

@article{arxiv.2603.14813,
  title  = {Sparsity for parametric PDEs with log-gamma random inputs and applications},
  author = {Dinh Dũng and Van Kien Nguyen and Viet Ha Hoang},
  journal= {arXiv preprint arXiv:2603.14813},
  year   = {2026}
}
R2 v1 2026-07-01T11:21:27.308Z