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Related papers: Computation of eigenvalues by numerical upscaling

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In this paper, we discuss the solution of certain matrix-valued partial differential equations. Such PDEs arise, for example, when constructing a Riemannian contraction metric for a dynamical system given by an autonomous ODE. We develop…

Numerical Analysis · Mathematics 2017-06-29 Peter Giesl , Holger Wendland

In this article we prove convergence of adaptive finite element methods for second order elliptic eigenvalue problems. We consider Lagrange finite elements of any degree and prove convergence for simple as well as multiple eigenvalues under…

Numerical Analysis · Mathematics 2008-03-05 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

The numerical solution of eigenvalue problems is essential in various application areas of scientific and engineering domains. In many problem classes, the practical interest is only a small subset of eigenvalues so it is unnecessary to…

Numerical Analysis · Mathematics 2023-11-16 M. Ridwan Apriansyah , Rio Yokota

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou

Second-order partial differential equations in non-divergence form are considered. Equations of this kind typically arise as subproblems for the solution of Hamilton-Jacobi-Bellman equations in the context of stochastic optimal control, or…

Numerical Analysis · Mathematics 2020-08-13 Jan Blechschmidt , Roland Herzog , Max Winkler

M-eigenvalues of fourth order hierarchically symmetric tensors play a significant role in nonlinear elastic material analysis and quantum entanglement problems. This paper focuses on computing extreme M-eigenvalues for such tensors. To…

Optimization and Control · Mathematics 2026-02-03 Zhuolin Du , Yisheng Song

Subspace methods are commonly used for finding approximate eigenvalues and singular values of large-scale matrices. Once a subspace is found, the Rayleigh-Ritz method (for symmetric eigenvalue problems) and Petrov-Galerkin projection (for…

Numerical Analysis · Mathematics 2025-10-07 Irina-Beatrice Haas , Yuji Nakatsukasa

It is well known that the usual mixed method for solving the biharmonic eigenvalue problem by decomposing the operator into two Laplacians may generate spurious eigenvalues on non-convex domains. To overcome this difficulty, we adopt a…

Numerical Analysis · Mathematics 2021-07-27 Baiju Zhang , Hengguang Li , Zhimin Zhang

For a class of non-selfadjoint $h$--pseudodifferential operators with double characteristics, we give a precise description of the spectrum and establish accurate semiclassical resolvent estimates in a neighborhood of the origin.…

Analysis of PDEs · Mathematics 2011-05-25 Michael Hitrik , Karel Pravda-Starov

The aim of the paper is to introduce a new systematic method that can produce lower bounds for eigenvalues. The main idea is to use nonconforming finite element methods. The general conclusion herein is that if local approximation…

Numerical Analysis · Mathematics 2013-04-22 Jun Hu , Yunqing Huang , Qun Lin

This paper is concerned with the approximation of tensors using tree-based tensor formats, which are tensor networks whose graphs are dimension partition trees. We consider Hilbert tensor spaces of multivariate functions defined on a…

Numerical Analysis · Mathematics 2019-09-11 Anthony Nouy

Joint diagonalization, the process of finding a shared set of approximate eigenvectors for a collection of matrices, arises in diverse applications such as multidimensional harmonic analysis or quantum information theory. This task is…

Optimization and Control · Mathematics 2025-02-12 Erik Troedsson , Marcus Carlsson , Herwig Wendt

Eigenvalue problems are fundamental to mathematics and science. We present a simple algorithm for determining eigenvalues and eigenfunctions of the Laplace--Beltrami operator on rather general curved surfaces. Our algorithm, which is based…

Numerical Analysis · Mathematics 2011-09-13 Colin B. Macdonald , Jeremy Brandman , Steven J. Ruuth

In this work we study the homogenization problem for (nonlinear) eigenvalues of quasilinear elliptic operators. We prove convergence of the first and second eigenvalues and, in the case where the operator is independent of $\varepsilon$,…

Analysis of PDEs · Mathematics 2012-11-20 Julian Fernandez Bonder , Juan P. Pinasco , Ariel M. Salort

We discuss the $p$- and the $hp$-versions of the virtual element method for the approximation of eigenpairs of elliptic operators with a potential term on polygonal meshes. An application of this model is provided by the Schr\"odinger…

Numerical Analysis · Mathematics 2018-12-24 O. Certik , F. Gardini , G. Manzini , L. Mascotto , G. Vacca

An unsteady problem is considered for a space-fractional equation in a bounded domain. A first-order evolutionary equation involves a fractional power of an elliptic operator of second order. Finite element approximation in space is…

Numerical Analysis · Computer Science 2018-05-09 Petr N. Vabishchevich

Recently, there has been interest in high-precision approximations of the first eigenvalue of the Laplace-Beltrami operator on spherical triangles for combinatorial purposes. We compute improved and certified enclosures to these…

Numerical Analysis · Mathematics 2020-11-19 Joel Dahne , Bruno Salvy

In this paper, both semidiscrete and completely discrete finite volume element methods (FVEMs) are analyzed for approximating solutions of a class of linear hyperbolic integro- differential equations in a two-dimensional convex polygonal…

Numerical Analysis · Mathematics 2014-01-22 Samir Karaa , Amiya K. Pani

We calculate eigenvalues of one-dimensional quantum-systems by the exact numerical solution of the Lippmann-Schwinger equation, analogous to the scattering problem. To illustrate our method, we treat elementary problems: the harmonic and…

Quantum Physics · Physics 2019-12-04 Alexander Jurisch

This work investigates finite differences and the use of interpolation models to obtain approximations to the first and second derivatives of a function. Here, it is shown that if a particular set of points is used in the interpolation…

Optimization and Control · Mathematics 2020-01-24 Ian D. Coope , Rachael Tappenden
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