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We present a novel implementation of an iterative solver for the solution of the Poisson equation in the PLUTO code for astrophysical fluid dynamics. Our solver relies on a relaxation method in which convergence is sought as the…

Instrumentation and Methods for Astrophysics · Physics 2023-09-15 Ankush Mandal , Dipanjan Mukherjee , Andrea Mignone

We consider discrete Poisson interface problems resulting from linear unfitted finite elements, also called cut finite elements (CutFEM). Three of these unfitted finite element methods known from the literature are studied. All three…

Numerical Analysis · Mathematics 2018-07-27 Thomas Ludescher , Sven Gross , Arnold Reusken

In this paper, the authors constructed an auxiliary space multigrid preconditioner for the weak Galerkin finite element method for second-order diffusion equations, discretized on simplicial 2D or 3D meshes. The idea of the auxiliary space…

Numerical Analysis · Mathematics 2014-10-07 Long Chen , Junping Wang , Yanqiu Wang , Xiu Ye

We design and investigate efficient multigrid solvers for multiphase Stokes problems discretised via mixed-degree local discontinuous Galerkin methods. Using the template of a standard multigrid V-cycle, we develop a smoother analogous to…

Numerical Analysis · Mathematics 2025-11-26 Robert I. Saye

We present multigrid methods for solving elliptic partial differential equations on arbitrary domains using the nodal ghost finite element method, an unfitted boundary approach where the domain is implicitly defined by a level-set function.…

Numerical Analysis · Mathematics 2025-05-09 Hridya Dilip , Armando Coco

The multigrid algorithm is an efficient numerical method for solving a variety of elliptic partial differential equations (PDEs). The method damps errors at progressively finer grid scales, resulting in faster convergence compared to…

Numerical Analysis · Mathematics 2021-05-06 Francisco Holguin , GS Sidharth , Gavin Portwood

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

An expandable local and parallel two-grid finite element scheme based on superposition principle for elliptic problems is proposed and analyzed in this paper by taking example of Poisson equation. Compared with the usual local and parallel…

Numerical Analysis · Mathematics 2015-09-10 Yanren Hou , Guangzhi Du

In this paper, a symmetrized two-scale finite element method is proposed for a class of partial differential equations with symmetric solutions. With this method, the finite element approximation on a fine tensor product grid is reduced to…

Numerical Analysis · Mathematics 2022-06-01 Pengyu Hou , Fang Liu , Aihui Zhou

We develop a nonlinear multigrid method to solve the steady state of microflow, which is modeled by the high order moment system derived recently for the steady-state Boltzmann equation with ES-BGK collision term. The solver adopts a…

Numerical Analysis · Mathematics 2014-12-15 Zhicheng Hu , Ruo Li

Application of multigrid solvers in shifted linear systems is studied. We focus on accelerating the rational approximation needed for simulating single flavor operators. This is particularly useful, in the case of twisted mass fermions for…

High Energy Physics - Lattice · Physics 2019-02-20 Constantia Alexandrou , Simone Bacchio , Jacob Finkenrath

Common efficient schemes for the incompressible Navier-Stokes equations, such as projection or fractional step methods, have limited temporal accuracy as a result of matrix splitting errors, or introduce errors near the domain boundaries…

Numerical Analysis · Mathematics 2015-05-20 David Shirokoff , Rodolfo Ruben Rosales

In this paper, we propose an efficient extrapolation cascadic multigrid (EXCMG) method combined with 25-point difference approximation to solve the three-dimensional biharmonic equation. First, through applying Richardson extrapolation and…

Numerical Analysis · Mathematics 2024-12-20 Kejia Pan , Dongdong He , Runxin Ni

The aim of this paper is to develop an algebraic multigrid method to solve eigenvalue problems based on the combination of the multilevel correction scheme and the algebraic multigrid method for linear equations. Our approach uses the…

Numerical Analysis · Mathematics 2020-03-02 Ning Zhang , Xiaole Han , Yunhui He , Hehu Xie , Chun'guang You

Divergence constraints are present in the governing equations of numerous physical phenomena, and they usually lead to a Poisson equation whose solution represents a bottleneck in many simulation codes. Algebraic Multigrid (AMG) is arguably…

Numerical Analysis · Mathematics 2024-12-06 Àdel Alsalti-Baldellou , Carlo Janna , Xavier Álvarez-Farré , F. Xavier Trias

The constraints of the superfield method in two-dimensional supergravity are adapted to allow for nonvanishing bosonic torsion. As the analysis of the Bianchi identities reveals, a new vector superfield is encountered besides the well-known…

High Energy Physics - Theory · Physics 2007-05-23 Martin Franz Ertl

A high-order Newton multigrid method is proposed for steady-state shallow water flows in open channels with regular and irregular geometries. The method integrates a finite volume discretization with third-order weighted essentially…

Numerical Analysis · Mathematics 2026-05-29 Zhicheng Hu , Guanghan Li , Chunwu Wang , Xiaowen Wang

The analysis of second-order optimization methods based either on sub-sampling, randomization or sketching has two serious shortcomings compared to the conventional Newton method. The first shortcoming is that the analysis of the iterates…

Optimization and Control · Mathematics 2024-04-05 Nick Tsipinakis , Panos Parpas

In this paper, a full (nested) multigrid scheme is proposed to solve eigenvalue problems. The idea here is to use the multilevel correction method to transform the solution of eigenvalue problem to a series of solutions of the corresponding…

Numerical Analysis · Mathematics 2015-06-23 Hehu Xie

With the rapid advancement of graphical processing units, Physics-Informed Neural Networks (PINNs) are emerging as a promising tool for solving partial differential equations (PDEs). However, PINNs are not well suited for solving PDEs with…

Machine Learning · Computer Science 2024-05-28 Yuxiang Gao , Soheil Kolouri , Ravindra Duddu