Adaptive stochastic Galerkin finite element methods: Optimality and non-affine coefficients

Fuente: arXiv
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Main Authors: Bachmayr, Markus, Eisenmann, Henrik, Voulis, Igor
Format: Preprint
Published: 2025
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_version_ 1866910890288218112
author Bachmayr, Markus
Eisenmann, Henrik
Voulis, Igor
author_facet Bachmayr, Markus
Eisenmann, Henrik
Voulis, Igor
contents Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions of random diffusion coefficients and combines operator compression in the stochastic variables with error estimation using finite element frames in space. A new operator compression strategy is introduced for nonlinear coefficient expansions, such as diffusion coefficients with log-affine structure.
format Preprint
id arxiv_https___arxiv_org_abs_2503_18704
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Adaptive stochastic Galerkin finite element methods: Optimality and non-affine coefficients
Bachmayr, Markus
Eisenmann, Henrik
Voulis, Igor
Numerical Analysis
35J25, 35R60, 41A10, 41A63, 42C10, 65N50, 65N30
Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions of random diffusion coefficients and combines operator compression in the stochastic variables with error estimation using finite element frames in space. A new operator compression strategy is introduced for nonlinear coefficient expansions, such as diffusion coefficients with log-affine structure.
title Adaptive stochastic Galerkin finite element methods: Optimality and non-affine coefficients
topic Numerical Analysis
35J25, 35R60, 41A10, 41A63, 42C10, 65N50, 65N30
url https://arxiv.org/abs/2503.18704