Discrete weak duality of hybrid high-order methods for convex minimization problems

Fuente: arXiv
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Main Author: Tran, Ngoc Tien
Format: Preprint
Published: 2023
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author Tran, Ngoc Tien
author_facet Tran, Ngoc Tien
contents This paper derives a discrete dual problem for a prototypical hybrid high-order method for convex minimization problems. The discrete primal and dual problem satisfy a weak convex duality that leads to a priori error estimates with convergence rates under additional smoothness assumptions. This duality holds for general polyhedral meshes and arbitrary polynomial degrees of the discretization. A novel postprocessing is proposed and allows for a~posteriori error estimates on regular triangulations into simplices using primal-dual techniques. This motivates an adaptive mesh-refining algorithm, which performs superiorly compared to uniform mesh refinements.
format Preprint
id arxiv_https___arxiv_org_abs_2308_03223
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Discrete weak duality of hybrid high-order methods for convex minimization problems
Tran, Ngoc Tien
Numerical Analysis
65N12, 65N30, 65Y20
This paper derives a discrete dual problem for a prototypical hybrid high-order method for convex minimization problems. The discrete primal and dual problem satisfy a weak convex duality that leads to a priori error estimates with convergence rates under additional smoothness assumptions. This duality holds for general polyhedral meshes and arbitrary polynomial degrees of the discretization. A novel postprocessing is proposed and allows for a~posteriori error estimates on regular triangulations into simplices using primal-dual techniques. This motivates an adaptive mesh-refining algorithm, which performs superiorly compared to uniform mesh refinements.
title Discrete weak duality of hybrid high-order methods for convex minimization problems
topic Numerical Analysis
65N12, 65N30, 65Y20
url https://arxiv.org/abs/2308.03223