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In this paper, we develop the auxiliary space preconditioners for solving the linear system arising from the virtual element methods discretization on polytopal meshes for the second order elliptic equations. The preconditioners are…

Numerical Analysis · Mathematics 2018-12-12 Yunrong Zhu

When solving the Poisson equation by the finite element method, we use one degree of freedom for interpolation by the given Laplacian - the right hand side function in the partial differential equation. The finite element solution is the…

Numerical Analysis · Mathematics 2020-10-06 Tatyana Sorokina , Shangyou Zhang

Although some preconditioners are available for solving dense linear systems, there are still many matrices for which preconditioners are lacking, in particular in cases where the size of the matrix $N$ becomes very large. There remains…

Numerical Analysis · Mathematics 2016-02-05 Pieter Coulier , Hadi Pouransari , Eric Darve

The matrix element method utilizes ab initio calculations of probability densities as powerful discriminants for processes of interest in experimental particle physics. The method has already been used successfully at previous and current…

Computational Physics · Physics 2015-05-20 Doug Schouten , Adam DeAbreu , Bernd Stelzer

The discretization of certain integral equations, e.g., the first-kind Fredholm equation of Laplace's equation, leads to symmetric positive-definite linear systems, where the coefficient matrix is dense and often ill-conditioned. We…

Numerical Analysis · Mathematics 2022-08-22 Chao Chen , George Biros

We propose an explicit construction of Poincar\'e operators for the lowest order finite element spaces, by employing spanning trees in the grid. In turn, a stable decomposition of the discrete spaces is derived that leads to an efficient…

Numerical Analysis · Mathematics 2024-10-14 Wietse M. Boon

Fast computation of demagnetization curves is essential for the computational design of soft magnetic sensors or permanent magnet materials. We show that a sparse preconditioner for a nonlinear conjugate gradient energy minimizer can lead…

Computational Physics · Physics 2018-10-23 Lukas Exl , Johann Fischbacher , Alexander Kovacs , Harald Oezelt , Markus Gusenbauer , Thomas Schrefl

The Poisson-Boltzmann equation offers an efficient way to study electrostatics in molecular settings. Its numerical solution with the boundary element method is widely used, as the complicated molecular surface is accurately represented by…

Numerical Analysis · Mathematics 2021-08-25 Stefan D. Search , Christopher D. Cooper , Elwin van't Wout

We propose a two-level nested preconditioned iterative scheme for solving sparse linear systems of equations in which the coefficient matrix is symmetric and indefinite with relatively small number of negative eigenvalues. The proposed…

Numerical Analysis · Computer Science 2019-01-29 Murat Manguoglu , Volker Mehrmann

This note proposes an efficient preconditioner for solving linear and semi-linear parabolic equations. With the Crank-Nicholson time stepping method, the algebraic system of equations at each time step is solved with the conjugate gradient…

Numerical Analysis · Mathematics 2021-05-11 Jordi Feliu-Fabà , Lexing Ying

Solving systems of linear equations is a problem occuring frequently in water engineering applications. Usually the size of the problem is too large to be solved via direct factorization. One can resort to iterative approaches, in…

Machine Learning · Computer Science 2019-06-18 Johannes Sappl , Laurent Seiler , Matthias Harders , Wolfgang Rauch

In this study, the $\theta$-method is used for discretizing a class of evolutionary partial differential equations. Then, we transform the resultant all-at-once linear system and introduce a novel one-sided preconditioner, which can be fast…

Numerical Analysis · Mathematics 2024-08-08 Yuan-Yuan Huang , Po Yin Fung , Sean Y. Hon , Xue-Lei Lin

Gaussian processes provide probabilistic surrogates for various applications including classification, uncertainty quantification, and optimization. Using a gradient-enhanced covariance matrix can be beneficial since it provides a more…

Optimization and Control · Mathematics 2023-07-13 André L. Marchildon , David W. Zingg

Model predictive control (MPC) for linear dynamical systems requires solving an optimal control structured quadratic program (QP) at each sampling instant. This paper proposes a primal active-set strategy (PRESAS) for the efficient solution…

Optimization and Control · Mathematics 2020-07-14 Rien Quirynen , Stefano Di Cairano

PDE-constrained optimization aims at finding optimal setups for partial differential equations so that relevant quantities are minimized. Including sparsity promoting terms in the formulation of such problems results in more practically…

Numerical Analysis · Mathematics 2016-11-23 Margherita Porcelli , Valeria Simoncini , Martin Stoll

A new domain decomposition preconditioner is introduced for efficiently solving linear systems Ax = b with a symmetric positive definite matrix A. The particularity of the new preconditioner is that it is not necessary to have access to the…

Numerical Analysis · Mathematics 2021-06-23 Nicole Spillane

In this paper, we revisit an auxiliary space preconditioning method proposed by Xu [Computing 56, 1996], in which low-order finite element spaces are employed as auxiliary spaces for solving linear algebraic systems arising from high-order…

Numerical Analysis · Mathematics 2012-04-13 Young-Ju Lee , Wei Leng , Chen-Song Zhang

We derive parameter-robust quasi-optimal error estimates for mixed finite element methods for the nonlinear Darcy--Forchheimer equations with mixed boundary conditions. Using the framework of operator preconditioning, we also design…

Numerical Analysis · Mathematics 2026-02-25 Rishi Das , Harsha Hutridurga , Amiya K. Pani , Ricardo Ruiz-Baier

This report shows on real data that the direct methods such as LDL decomposition and Gaussian elimination for solving linear systems with ill-conditioned matrices provide inaccurate results due to divisions by very small numbers, which in…

Optimization and Control · Mathematics 2023-02-20 Alexander Stotsky

The convergence of the conjugate gradient method for solving large-scale and sparse linear equation systems depends on the spectral properties of the system matrix, which can be improved by preconditioning. In this paper, we develop a…

Optimization and Control · Mathematics 2024-10-25 Paul Häusner , Ozan Öktem , Jens Sjölund
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