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Related papers: Convergence and Optimality of hp-AFEM

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In this article we develop a convergence theory for goal-oriented adaptive finite element algorithms designed for a class of second-order semilinear elliptic equations. We briefly discuss the target problem class, and introduce several…

Numerical Analysis · Mathematics 2014-04-24 Michael Holst , Sara Pollock , Yunrong Zhu

We prove the quasi-optimal convergence of a standard adaptive finite element method (AFEM) for nonlinear elliptic second-order equations of monotone type. The adaptive algorithm is based on residual-type a posteriori error estimators and…

Numerical Analysis · Mathematics 2010-10-07 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

We develop an efficient and reliable adaptive finite element method (AFEM) for the nonlinear Poisson-Boltzmann equation (PBE). We first examine the regularization technique of Chen, Holst, and Xu; this technique made possible the first a…

Numerical Analysis · Mathematics 2010-10-01 Michael Holst , James Andrew McCammon , Zeyun Yu , Yongcheng Zhou , Yunrong Zhu

Adaptive Finite Element Method (adaptivity) is known to be an effective numerical tool for some ill-posed problems. The key advantage of the adaptivity is the image improvement with local mesh refinements. A rigorous proof of this property…

Mathematical Physics · Physics 2012-10-30 Larisa Beilina , Michael V. Klibanov

In this paper, we present a finite element method (FEM) framework enhanced by an operator-adapted wavelet decomposition algorithm designed for the efficient analysis of multiscale electromagnetic problems. Usual adaptive FEM approaches,…

Computational Physics · Physics 2026-02-18 F. Şık , F. L. Teixeira , B. Shanker

The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) and polynomial degree ($p$) to be used on each cell - has long been known to have better theoretical convergence properties than either $h$-…

Numerical Analysis · Mathematics 2023-09-14 Marc Fehling , Wolfgang Bangerth

This paper introduces the Fej\'er-monotone hybrid steepest descent method (FM-HSDM), a new member to the HSDM family of algorithms, for solving affinely constrained minimization tasks in real Hilbert spaces, where convex smooth and…

Optimization and Control · Mathematics 2018-04-11 Konstantinos Slavakis , Isao Yamada

This chapter provides an overview of state-of-the-art adaptive finite element methods (AFEMs) for the numerical solution of second-order elliptic partial differential equations (PDEs), where the primary focus is on the optimal interplay of…

Numerical Analysis · Mathematics 2024-04-11 Philipp Bringmann , Ani Miraçi , Dirk Praetorius

The convergence analysis for least-squares finite element methods led to various adaptive mesh-refinement strategies: Collective marking algorithms driven by the built-in a posteriori error estimator or an alternative explicit…

Numerical Analysis · Mathematics 2023-09-18 Philipp Bringmann

We construct a finite element method (FEM) for the infinity Laplacian. Solutions of this problem may be singular, which has prompted us to conduct an a posteriori analysis of the method deriving residual based estimators to drive an…

Numerical Analysis · Mathematics 2017-05-17 Omar Lakkis , Tristan Pryer

We propose an adaptive iteratively linearized finite element method (AILFEM) in the context of strongly monotone nonlinear operators in Hilbert spaces. The approach combines adaptive mesh-refinement with an energy-contractive linearization…

Numerical Analysis · Mathematics 2025-03-18 Ani Miraçi , Dirk Praetorius , Julian Streitberger

We propose a new practical adaptive refinement strategy for $hp$-finite element approximations of elliptic problems. Following recent theoretical developments in polynomial-degree-robust a posteriori error analysis, we solve two types of…

Numerical Analysis · Mathematics 2018-10-17 Patrik Daniel , Alexandre Ern , Iain Smears , Martin Vohralík

The finite-element method is a preferred numerical method when electromagnetic fields at high accuracy are to be computed in nano-optics design. Here, we demonstrate a finite-element method using hp-adaptivity on tetrahedral meshes for…

It is shown that the h-adaptive mixed finite element method for the discretization of eigenvalue clusters of the Laplace operator produces optimal convergence rates in terms of nonlinear approximation classes. The results are valid for the…

Numerical Analysis · Mathematics 2015-04-27 Daniele Boffi , Dietmar Gallistl , Francesca Gardini , Lucia Gastaldi

Many problems in science and engineering can be rigorously recast into minimizing a suitable energy functional. We have been developing efficient and flexible solution strategies to tackle various minimization problems by employing finite…

Computational Engineering, Finance, and Science · Computer Science 2023-10-03 Miroslav Frost , Alexej Moskovka , Jan Valdman

We develop two adaptive discretization algorithms for convex semi-infinite optimization, which terminate after finitely many iterations at approximate solutions of arbitrary precision. In particular, they terminate at a feasible point of…

Optimization and Control · Mathematics 2022-01-14 Jochen Schmid , Miltiadis Poursanidis

We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai: SIAM J. Sci. Comput. 43, 2021]. S-AFEM modifies the classical adaptive finite element method…

Numerical Analysis · Mathematics 2026-01-29 Philipp Bringmann , Christoph Lietz , Dirk Praetorius

This is a survey on the theory of adaptive finite element methods (AFEMs), which are fundamental in modern computational science and engineering but whose mathematical assessment is a formidable challenge. We present a self-contained and…

Numerical Analysis · Mathematics 2024-11-20 Andrea Bonito , Claudio Canuto , Ricardo H. Nochetto , Andreas Veeser

In this paper, we study an adaptive finite element method for a class of a nonlinear eigenvalue problems that may be of nonconvex energy functional and consider its applications to quantum chemistry. We prove the convergence of adaptive…

Numerical Analysis · Mathematics 2010-01-15 H. Chen , X. Gong , L. He , A. Zhou

We develop approximation algorithms for set-selection problems with deterministic constraints, but random objective values, i.e., stochastic probing problems. When the goal is to maximize the objective, approximation algorithms for probing…

Data Structures and Algorithms · Computer Science 2021-11-04 Weina Wang , Anupam Gupta , Jalani Williams