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We apply the local discontinuous Galerkin (LDG for short) method to solve a mixed boundary value problems for the Helmholtz equation in bounded polygonal domain in 2D. Under some assumptions on regularity of the solution of an adjoint…

Numerical Analysis · Mathematics 2013-10-11 T. P. Barrios , R. Bustinza , V. Dominguez

We consider the problem of how to compute eigenvalues of a self-adjoint operator when a direct application of the Galerkin (finite-section) method is unreliable. The last two decades have seen the development of the so-called quadratic…

Spectral Theory · Mathematics 2015-06-16 James Hinchcliffe , Michael Strauss

We propose a inexact Newton method for solving inverse eigenvalue problems (IEP). This method is globalized by employing the classical backtracking techniques. A global convergence analysis of this method is provided and the R-order…

Numerical Analysis · Mathematics 2013-04-24 Yonghui Ling , Xiubin Xu

This article proposes a novel least-squares weak Galerkin (LS-WG) method for second-order elliptic equations in non-divergence form. The approach leverages a locally defined discrete weak Hessian operator constructed within the weak…

Numerical Analysis · Mathematics 2026-05-13 Chunmei Wang , Shangyou Zhang

The conforming finite element Galerkin method is applied to discretise in the spatial direction for a class of strongly nonlinear parabolic problems. Using elliptic projection of the associated linearised stationary problem with Gronwall…

Numerical Analysis · Mathematics 2021-08-04 Ambit Kumar Pany , Morrakot Khebchareon , Amiya K. Pani

ADER-WENO methods have proved extremely useful in obtaining arbitrarily high-order solutions to problems involving hyperbolic systems of PDEs. For example, it has been demonstrated that for the same computational cost as a Runge-Kutta…

Computational Physics · Physics 2017-03-08 Haran Jackson

An adaptive algorithm, based on residual type a posteriori indicators of errors measured in $L^{\infty}(L^2)$ and $L^2(L^2)$ norms, for a numerical scheme consisting of implicit Euler method in time and discontinuous Galerkin method in…

Numerical Analysis · Mathematics 2013-03-12 Emmanuil H. Georgoulis , Juha M. Virtanen

We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the…

Numerical Analysis · Mathematics 2015-04-24 Michael Feischl , Gregor Gantner , Dirk Praetorius

This paper proposes hybrid high-order eigensolvers for the computation of guaranteed lower eigenvalue bounds. These bounds display higher order convergence rates and are accessible to adaptive mesh-refining algorithms. The involved…

Numerical Analysis · Mathematics 2026-04-23 Ngoc Tien Tran

A C^0-weak Galerkin (WG) method is introduced and analyzed for solving the biharmonic equation in 2D and 3D. A weak Laplacian is defined for C^0 functions in the new weak formulation. This WG finite element formulation is symmetric,…

Numerical Analysis · Mathematics 2012-12-04 Lin Mu , Junping Wang , Xiu Ye , Shangyou Zhang

We consider Galerkin approximations of holomorphic Fredholm operator eigenvalue problems for which the operator values don't have the structure "coercive+compact". In this case the regularity (in sense of [O. Karma, Numer. Funct. Anal.…

Numerical Analysis · Mathematics 2019-08-15 Martin Halla

This paper generalizes the earlier work on the energy-based discontinuous Galerkin method for second-order wave equations to fourth-order semilinear wave equations. We first rewrite the problem into a system with a second-order spatial…

Numerical Analysis · Mathematics 2022-07-25 Lu Zhang

In this work, we study the inverse problem of analog gravity systems which admit rotation and energy-dependent boundary conditions. By extending two recent results, we provide a recipe that allows one to relate resonant transmission spectra…

General Relativity and Quantum Cosmology · Physics 2024-10-01 Saulo Albuquerque , Sebastian H. Völkel , Kostas D. Kokkotas , Valdir B. Bezerra

The convergence of GMRES for solving linear systems can be influenced heavily by the structure of the right hand side. Within the solution of eigenvalue problems via inverse iteration or subspace iteration, the right hand side is generally…

Numerical Analysis · Mathematics 2017-05-31 Melina Freitag , Patrick Kürschner , Jennifer Pestana

In this article, we present two new greedy algorithms for the computation of the lowest eigenvalue (and an associated eigenvector) of a high-dimensional eigenvalue problem, and prove some convergence results for these algorithms and their…

Numerical Analysis · Mathematics 2013-04-10 Eric Cancès , Virginie Ehrlacher , Tony Lelièvre

We present a method for linear stability analysis of systems with parametric uncertainty formulated in the stochastic Galerkin framework. Specifically, we assume that for a model partial differential equation, the parameter is given in the…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Kookjin Lee

We propose a neural-enhanced weak Galerkin (WG) finite element method for second-order elliptic problems with low-regularity solutions. The method augments the classical WG approximation space with neural network functions constructed via a…

Numerical Analysis · Mathematics 2026-04-08 Chunmei Wang

The iterative algorithm recently proposed by Waxman for solving eigenvalue problems, which relies on the method of moments, has been modified to improve its convergence considerably without sacrificing its benefits or elegance. The…

Mathematical Physics · Physics 2009-11-11 W. A. Berger , H. G. Miller

This article introduces a new primal-dual weak Galerkin (PDWG) finite element method for second order elliptic interface problems with ultra-low regularity assumptions on the exact solution and the interface and boundary data. It is proved…

Numerical Analysis · Mathematics 2020-10-29 Waixiang Cao , Chunmei Wang , Junping Wang

Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding critical points of a quadratic function…

Machine Learning · Computer Science 2015-03-17 Matthias Hein , Thomas Bühler