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We introduce a novel spatial discretization technique for the reliable and efficient simulation of magnetization dynamics governed by the Landau-Lifshitz (LL) equation. The overall discretization error is systematically decomposed into…

Numerical Analysis · Mathematics 2026-01-21 Zetao Ma , Rui Du , Lei Zhang

In the present contribution we establish quantitative results on the periodic approximation of the corrector equation for the stochastic homogenization of linear elliptic equations in divergence form, when the diffusion coefficients satisfy…

Numerical Analysis · Mathematics 2014-09-04 Antoine Gloria , Felix Otto

In this paper, we propose and analyze a multiscale method for a class of quasilinear elliptic problems of nonmonotone type with spatially multiscale coefficient. The numerical approach is inspired by the Localized Orthogonal Decomposition…

Numerical Analysis · Mathematics 2025-07-28 Maher Khrais , Barbara Verfürth

This article is concerned with numerical methods to approximate effective coefficients in stochastic homogenization of discrete linear elliptic equations, and their numerical analysis --- which has been made possible by recent contributions…

Numerical Analysis · Mathematics 2012-11-09 A. -C. Egloffe , A. Gloria , J. -C. Mourrat , T. N. Nguyen

We derive optimal estimates in stochastic homogenization of linear elliptic equations in divergence form in dimensions $d\ge 2$. In previous works we studied the model problem of a discrete elliptic equation on $\mathbb{Z}^d$. Under the…

Analysis of PDEs · Mathematics 2014-09-03 Antoine Gloria , Felix Otto

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth

In this paper, we propose a computationally efficient iterative algorithm for proper orthogonal decomposition (POD) using random sampling based techniques. In this algorithm, additional rows and columns are sampled and a merging technique…

Numerical Analysis · Mathematics 2020-11-23 Charumathi V , M. Ramakrishna , Vinita Vasudevan

In this paper, we propose a computationally efficient iterative algorithm for proper orthogonal decomposition (POD) using random sampling based techniques. In this algorithm, additional rows and columns are sampled and a merging technique…

Numerical Analysis · Computer Science 2021-07-07 V. Charumathi , M. Ramakrishna , Vinita Vasudevan

This paper is about the homogenization of linear elliptic operators in divergence form with stationary random coefficients that have only slowly decaying correlations. It deduces optimal estimates of the homogenization error from optimal…

Analysis of PDEs · Mathematics 2022-02-09 Antoine Gloria , Stefan Neukamm , Felix Otto

We introduce a new method for studying stochastic homogenization of elliptic equations in nondivergence form. The main application is an algebraic error estimate, asserting that deviations from the homogenized limit are at most proportional…

Analysis of PDEs · Mathematics 2019-12-10 Scott N. Armstrong , Charles K. Smart

This paper proposes a novel collocation-type numerical stochastic homogenization method for prototypical stochastic homogenization problems with random coefficient fields of small correlation lengths. The presented method is based on a…

Numerical Analysis · Mathematics 2024-11-05 Moritz Hauck , Hannah Mohr , Daniel Peterseim

In this paper, we consider an elliptic eigenvalue problem with multiscale, randomly perturbed coefficients. For an efficient and accurate approximation of the solutions for many different realizations of the coefficient, we propose a…

Numerical Analysis · Mathematics 2025-07-08 Dilini Kolombage , Barbara Verfürth

We consider a sequence of elliptic partial differential equations (PDEs) with different but similar rapidly varying coefficients. Such sequences appear, for example, in splitting schemes for time-dependent problems (with one coefficient per…

Numerical Analysis · Mathematics 2018-06-05 Fredrik Hellman , Axel Målqvist

Numerical multiscale methods usually rely on some coupling between a macroscopic and a microscopic model. The macroscopic model is incomplete as effective quantities, such as the homogenized material coefficients or fluxes, are missing in…

Numerical Analysis · Mathematics 2021-03-23 Assyr Abdulle , Doghonay Arjmand , Edoardo Paganoni

This paper studies quantitative homogenization of elliptic equations with random, uniformly elliptic coefficients that vanish in a union of random holes. Assuming an upper bound on the size of the holes and a separation condition between…

Analysis of PDEs · Mathematics 2025-06-03 Peter Bella , Matteo Capoferri , Mikhail Cherdantsev , Igor Velčić

In this work we combine the framework of the Reduced Basis method (RB) with the framework of the Localized Orthogonal Decomposition (LOD) in order to solve parametrized elliptic multiscale problems. The idea of the LOD is to split a high…

Numerical Analysis · Mathematics 2015-05-20 Assyr Abdulle , Patrick Henning

This paper is the companion article of [Gloria, M3AS, 21 (2011), No. 3, pp 1601-1630]. One common drawback among numerical homogenization methods is the presence of the so-called resonance error, which roughly speaking is a function of the…

Numerical Analysis · Mathematics 2014-09-04 Antoine Gloria , Zakaria Habibi

In this paper we study elliptic partial differential equations with rapidly varying diffusion coefficient that can be represented as a perturbation of a reference coefficient. We develop a numerical method for efficiently solving multiple…

Numerical Analysis · Mathematics 2020-12-21 Fredrik Hellman , Tim Keil , Axel Målqvist

We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients. The methods are of Galerkin type and follow the…

Numerical Analysis · Mathematics 2025-05-20 Alexandre L. Madureira , Marcus Sarkis

We introduce a new variational method for the numerical homogenization of divergence form elliptic, parabolic and hyperbolic equations with arbitrary rough ($L^\infty$) coefficients. Our method does not rely on concepts of ergodicity or…

Numerical Analysis · Mathematics 2019-02-20 Houman Owhadi , Lei Zhang , Leonid Berlyand