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We develop a numerical strategy to solve multi-dimensional Poisson equations on dynamically adapted grids for evolutionary problems disclosing propagating fronts. The method is an extension of the multiresolution finite volume scheme used…

Analysis of PDEs · Mathematics 2015-05-12 Max Duarte , Zdenek Bonaventura , Marc Massot , Anne Bourdon

Uniform convergence of the geometric multigrid V-cycle is proven for HDG methods with a new set of assumptions on the injection operators from coarser to finer meshes. The scheme involves standard smoothers and local solvers which are…

Numerical Analysis · Mathematics 2024-01-11 Peipei Lu , Andreas Rupp , Guido Kanschat

I propose a vertex patch smoother where local problems are solved inexactly by a nested, matrix-free p-multigrid, creating a multigrid-within-multigrid framework. A single iteration of the local solver can be evaluated with…

Numerical Analysis · Mathematics 2025-10-21 Michał Wichrowski

Monotone finite difference methods provide stable convergent discretizations of a class of degenerate elliptic and parabolic Partial Differential Equations (PDEs). These methods are best suited to regular rectangular grids, which leads to…

Numerical Analysis · Mathematics 2015-11-19 Adam M. Oberman , Ian Zwiers

We deal with the numerical solution of the time-dependent partial differential equations using the adaptive space-time discontinuous Galerkin (DG) method. The discretization leads to a nonlinear algebraic system at each time level, the size…

Numerical Analysis · Mathematics 2026-01-29 Vit Dolejsi , Jakub Sistek

Matrix-free finite element implementations for large applications provide an attractive alternative to standard sparse matrix data formats due to the significantly reduced memory consumption. Here, we show that they are also competitive…

Computational Engineering, Finance, and Science · Computer Science 2020-03-19 Daniel Drzisga , Ulrich Rüde , Barbara Wohlmuth

We propose a state redistribution method for high order discontinuous Galerkin methods on curvilinear embedded boundary grids. State redistribution relaxes the overly restrictive CFL condition that results from arbitrarily small cut cells…

Numerical Analysis · Mathematics 2021-12-07 Andrew Giuliani

We consider the parallel time integration of the linear advection equation with the Parareal and two-level multigrid-reduction-in-time (MGRIT) algorithms. Our aim is to develop a better understanding of the convergence behaviour of these…

Numerical Analysis · Mathematics 2019-10-15 Oliver A. Krzysik , Hans De Sterck , Scott P. MacLachlan , Stephanie Friedhoff

The bootstrap algebraic multigrid framework allows for the adaptive construction of algebraic multigrid methods in situations where geometric multigrid methods are not known or not available at all. While there has been some work on…

Numerical Analysis · Mathematics 2018-02-05 Karsten Kahl , Matthias Rottmann

We present a new multigrid solver that is suitable for the Dirac operator in the presence of disordered gauge fields. The key behind the success of the algorithm is an adaptive projection onto the coarse grids that preserves the near null…

High Energy Physics - Lattice · Physics 2008-11-26 J. Brannick , R. C. Brower , M. A. Clark , J. C. Osborn , C. Rebbi

Multigrid solvers face multiple challenges on parallel computers. Two fundamental ones read as follows: Multiplicative solvers issue coarse grid solves which exhibit low concurrency and many multigrid implementations suffer from an…

Numerical Analysis · Mathematics 2020-07-02 Charles D. Murray , Tobias Weinzierl

We present a stability analysis of the Discontinuous Galerkin method on polygonal and polyhedral meshes (PolyDG) for the Stokes problem. In particular, we analyze the discrete inf-sup condition for different choices of the polynomial…

Numerical Analysis · Mathematics 2020-12-24 Paola F. Antonietti , Lorenzo Mascotto , Marco Verani , Stefano Zonca

The efficient solution of sparse, linear systems resulting from the discretization of partial differential equations is crucial to the performance of many physics-based simulations. The algorithmic optimality of multilevel approaches for…

Mathematical Software · Computer Science 2018-03-08 Andrew Reisner , Luke N. Olson , J. David Moulton

In the frame of isogeometric analysis, we consider a Galerkin boundary element discretization of the hyper-singular integral equation associated with the 2D Laplacian. We propose and analyze an adaptive algorithm which locally refines the…

Numerical Analysis · Mathematics 2020-03-03 Gregor Gantner , Dirk Praetorius , Stefan Schimanko

We investigate a numerical behaviour of robust deterministic optimal control problem subject to a convection diffusion equation containing uncertain inputs. Stochastic Galerkin approach, turning the original optimization problem containing…

Numerical Analysis · Mathematics 2023-03-01 Pelin Çiloğlu , Hamdullah Yücel

In this study, we present an $hp$-multigrid preconditioner for a divergence-conforming HDG scheme for the generalized Stokes and the Navier-Stokes equations using an augmented Lagrangian formulation. Our method relies on conforming…

Numerical Analysis · Mathematics 2023-03-14 Guosheng Fu , Wenzheng Kuang

This paper develops a high-order selective discontinuous Galerkin (SDG) method for solving elliptic interface problems on interface-unfitted Cartesian meshes. This method applies the discontinuous Galerkin (DG) formulation on interface…

Numerical Analysis · Mathematics 2026-05-20 Fang Liu , Haroun Meghaichi , Xu Zhang

Implicit time integration is key to robustly simulating stiff materials and large deformations, but its performance is often dominated by repeatedly solving large linear systems. Adaptive coarsening can reduce this cost by concentrating…

Graphics · Computer Science 2026-05-07 Xuan Wang , Zhaofeng Luo , Minchen Li , Taku Komura , Kemeng Huang

This paper introduces a novel geometric multigrid solver for unstructured curved surfaces. Multigrid methods are highly efficient iterative methods for solving systems of linear equations. Despite the success in solving problems defined on…

Graphics · Computer Science 2021-05-05 Hsueh-Ti Derek Liu , Jiayi Eris Zhang , Mirela Ben-Chen , Alec Jacobson

For low-dimensional data sets with a large amount of data points, standard kernel methods are usually not feasible for regression anymore. Besides simple linear models or involved heuristic deep learning models, grid-based discretizations…

Machine Learning · Computer Science 2019-03-01 Bastian Bohn , Michael Griebel , Jens Oettershagen
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