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We consider the time discretization of a linear parabolic problem by the discontinuous Galerkin (DG) method using piecewise polynomials of degree at most $r-1$ in $t$, for $r\ge1$ and with maximum step size~$k$. It is well known that the…

Numerical Analysis · Mathematics 2022-09-23 William McLean , Kassem Mustapha

We prove the inf-sup stability of a discontinuous Galerkin scheme for second order elliptic operators in (unbalanced) mesh-dependent norms for quasi-uniform meshes for all spatial dimensions. This results in a priori error bounds in these…

Numerical Analysis · Mathematics 2017-03-30 Emmanuil H. Georgoulis , Tristan Pryer

In this paper, we propose and analyze an efficient preconditioning method for the elliptic problem based on the reconstructed discontinuous approximation method. We reconstruct a high-order piecewise polynomial space that arbitrary order…

Numerical Analysis · Mathematics 2024-07-16 Ruo Li , Qicheng Liu , Fanyi Yang

We propose and analyze discontinuous Galerkin (dG) approximations to 3D-1D coupled systems which model diffusion in a 3D domain containing a small inclusion reduced to its 1D centerline. Convergence to weak solutions of a steady state…

Numerical Analysis · Mathematics 2023-12-29 Rami Masri , Miroslav Kuchta , Beatrice Riviere

This study introduces the divergence-conforming discontinuous Galerkin finite element method (DGFEM) for numerically approximating optimal control problems with distributed constraints, specifically those governed by stationary generalized…

Numerical Analysis · Mathematics 2025-04-23 Harpal Singh , Arbaz Khan

We introduce a nodally bound-preserving Galerkin method for second-order elliptic problems on general polygonal/polyhedral, henceforth collectively termed as \emph{polytopic}, meshes. Starting from an interior penalty discontinuous Galerkin…

Numerical Analysis · Mathematics 2025-10-03 Abdolreza Amiri , Gabriel R. Barrenechea , Emmanuil H. Georgoulis , Tristan Pryer

We study a posteriori error analysis of linear-quadratic boundary control problems under bilateral box constraints on the control which acts through a Neumann type boundary condition. We adopt the hybridizable discontinuous Galerkin method…

Numerical Analysis · Mathematics 2020-04-21 Haitao Leng , Yanping Chen

We consider a discontinuous Galerkin method for the numerical solution of boundary value problems in two-dimensional domains with curved boundaries. A key challenge in this setting is the potential loss of convergence order due to…

Numerical Analysis · Mathematics 2026-01-16 Adérito Araújo , Milene Santos

We propose an abstract discontinuous Galerkin neural network (DGNN) framework for analyzing the convergence of least-squares methods based on the residual minimization when feasible solutions are neural networks. Within this framework, we…

Numerical Analysis · Mathematics 2025-11-11 Long Yuan , Hongxing Rui

We introduce a discontinuous Galerkin method for the mixed formulation of the elasticity eigenproblem with reduced symmetry. The analysis of the resulting discrete eigenproblem does not fit in the standard spectral approximation framework…

Numerical Analysis · Mathematics 2018-01-29 Felipe Lepe , Salim Meddahi , David Mora , Rodolfo Rodríguez

In this manuscript we present an approach to analyze the discontinuous Galerkin solution for general quasilinear elliptic problems. This approach is sufficiently general to extend most of the well-known discretization schemes, including…

Numerical Analysis · Mathematics 2017-02-10 Mohammad Zakerzadeh , Georg May

In this paper, we present error estimates of fully discrete Runge--Kutta discontinuous Galerkin (DG) schemes for linear time-dependent partial differential equations. The analysis applies to explicit Runge--Kutta time discretizations of any…

Numerical Analysis · Mathematics 2020-01-07 Zheng Sun , Chi-Wang Shu

We consider a semilinear parabolic equation with a large class of nonlinearities without any growth conditions. We discretize the problem with a discontinuous Galerkin scheme dG(0) in time (which is a variant of the implicit Euler scheme)…

Numerical Analysis · Mathematics 2018-08-17 Dominik Meidner , Boris Vexler

The heart of the a priori and a posteriori error control in convex minimization problems is the sharp control of the differences of discrete and exact minimal energy. Conforming finite element discretizations for p-Laplace type minimization…

Numerical Analysis · Mathematics 2026-04-23 Carsten Carstensen , Ngoc Tien Tran

In this paper, we apply discontinuous finite element Galerkin method to the time-dependent $2D$ incompressible Navier-Stokes model. We derive optimal error estimates in $L^\infty(\textbf{L}^2)$-norm for the velocity and in…

Numerical Analysis · Mathematics 2021-12-24 Saumya Bajpai , Deepjyoti Goswami , Kallol Ray

In this paper, we propose a class of adaptive multiresolution (also called adaptive sparse grid) discontinuous Galerkin (DG) methods for simulating scalar wave equations in second order form in space. The two key ingredients of the schemes…

Numerical Analysis · Mathematics 2020-04-21 Juntao Huang , Yuan Liu , Wei Guo , Zhanjing Tao , Yingda Cheng

Discontinuous Galerkin (DG) methods for hyperbolic partial differential equations (PDEs) with explicit time-stepping schemes, such as strong stability-preserving Runge-Kutta (SSP-RK), suffer from time-step restrictions that are…

Numerical Analysis · Mathematics 2019-03-11 Pierson T. Guthrey , James A. Rossmanith

In this paper, we develop a new discontinuous Galerkin method for solving several types of partial differential equations (PDEs) with high order spatial derivatives. We combine the advantages of local discontinuous Galerkin (LDG) method and…

Numerical Analysis · Mathematics 2020-03-13 Qi Tao , Yan Xu , Chi-Wang Shu

In this paper, we study the convergence of adaptive mixed interior penalty discontinuous Galerkin method for H(curl)-elliptic problems. We first get the mixed model of H(curl)-elliptic problem by introducing a new intermediate variable.…

Numerical Analysis · Mathematics 2023-01-05 K. Liu , M. Tang , X. Q. Xing , L. Q. Zhong

In recent years, there has been an increasing interest in using deep learning and neural networks to tackle scientific problems, particularly in solving partial differential equations (PDEs). However, many neural network-based methods, such…

Machine Learning · Computer Science 2025-02-14 Adrian Celaya , Yimo Wang , David Fuentes , Beatrice Riviere
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