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The modeling of electric machines and power transformers typically involves systems of nonlinear magnetostatics or -quasistatics, and their efficient and accurate simulation is required for the reliable design, control, and optimization of…

Numerical Analysis · Mathematics 2024-08-23 Herbert Egger , Felix Engertsberger , Bogdan Radu

Due to its highly oscillating solution, the Helmholtz equation is numerically challenging to solve. To obtain a reasonable solution, a mesh size that is much smaller than the reciprocal of the wavenumber is typically required (known as the…

Numerical Analysis · Mathematics 2023-02-21 Qiwei Feng , Bin Han , Michelle Michelle

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of…

Functional Analysis · Mathematics 2023-04-13 F. Dai , E. Kosov , V. Temlyakov

We study a two-grid strategy for decoupling the time-dependent Poisson-Nernst-Planck equations describing the mass concentration of ions and the electrostatic potential. The computational system is decoupled to smaller systems by using…

Numerical Analysis · Mathematics 2018-08-01 Ruigang Shen , Shi Shu , Ying Yang , Benzhuo Lu

Variational regularization of ill-posed inverse problems is based on minimizing the sum of a data fidelity term and a regularization term. The balance between them is tuned using a positive regularization parameter, whose automatic choice…

Numerical Analysis · Mathematics 2025-11-12 Markus Juvonen , Bjørn Jensen , Ilmari Pohjola , Yiqiu Dong , Samuli Siltanen

This paper proposes a new hybrid high-order discretization for the biharmonic problem and the corresponding eigenvalue problem. The discrete ansatz space includes degrees of freedom in $n-2$ dimensional submanifolds (e.g., nodal values in…

Numerical Analysis · Mathematics 2026-04-06 Yizhou Liang , Ngoc Tien Tran

Motivated by the paraxial narrow-angle approximation of the Helmholtz equation in domains of variable topography that appears as an important application in Underwater Acoustics, we analyze a general Schr\"odinger-type equation posed on…

Numerical Analysis · Mathematics 2011-10-19 D. C. Antonopoulou , G. D. Karali , M. Plexousakis , G. E. Zouraris

Equations of Hammerstein type cover large variety of areas and are of much interest to a wide audience due to the fact that they have applications in numerous areas. Suitable conditions are imposed to obtain a strong convergence result for…

Functional Analysis · Mathematics 2021-12-15 M. O. Aibinu , S. C. Thakur , S. Moyo

Superpositions of plane waves are known to approximate well the solutions of the Helmholtz equation. Their use in discretizations is typical of Trefftz methods for Helmholtz problems, aiming to achieve high accuracy with a small number of…

Numerical Analysis · Mathematics 2023-12-21 Emile Parolin , Daan Huybrechs , Andrea Moiola

We analyse the nematic Helmholtz-Korteweg equation, a variant of the classical Helmholtz equation that describes time-harmonic wave propagation in calamitic fluids in the presence of nematic order. A prominent example is given by nematic…

Numerical Analysis · Mathematics 2026-05-27 Patrick E. Farrell , Tim van Beeck , Umberto Zerbinati

The Sinkhorn "distance", a variant of the Wasserstein distance with entropic regularization, is an increasingly popular tool in machine learning and statistical inference. However, the time and memory requirements of standard algorithms for…

Machine Learning · Statistics 2021-11-16 Jason Altschuler , Francis Bach , Alessandro Rudi , Jonathan Niles-Weed

The Nystr\"om method is a popular choice for finding a low-rank approximation to a symmetric positive semi-definite matrix. The method can fail when applied to symmetric indefinite matrices, for which the error can be unboundedly large. In…

Numerical Analysis · Mathematics 2023-10-10 Taejun Park , Yuji Nakatsukasa

In this paper, we propose a unified framework, the Hessian discretisation method (HDM), which is based on four discrete elements (called altogether a Hessian discretisation) and a few intrinsic indicators of accuracy, independent of the…

Numerical Analysis · Mathematics 2018-08-28 Jérôme Droniou , Bishnu P. Lamichhane , Devika Shylaja

This paper is concerned with finite element error estimates for Neumann boundary control problems posed on convex and polyhedral domains. Different discretization concepts are considered and for each optimal discretization error estimates…

Numerical Analysis · Mathematics 2024-09-18 Johannes Pfefferer , Boris Vexler

Regularization techniques are necessary to compute meaningful solutions to discrete ill-posed inverse problems. The well-known 2-norm Tikhonov regularization method equipped with a discretization of the gradient operator as regularization…

Numerical Analysis · Mathematics 2024-06-05 Silvia Gazzola , Ali Gholami

We consider solving the surface Helmholtz equation on a smooth two dimensional surface embedded into a three dimensional space meshed with tetrahedra. The mesh does not respect the surface and thus the surface cuts through the elements. We…

Numerical Analysis · Mathematics 2018-10-11 Erik Burman , Peter Hansbo , Mats G. Larson , Andre Massing

The paper addresses the problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under two standard kinds of assumptions --…

Numerical Analysis · Mathematics 2021-09-21 F. Dai , V. Temlyakov

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

The recent results presented in arXiv:2202.05608 have led to significant developments in achieving stable approximations of Helmholtz solutions by plane wave superposition. The study shows that the numerical instability and ill-conditioning…

Numerical Analysis · Mathematics 2023-05-04 Nicola Galante

Minimizing a convex function of a measure with a sparsity-inducing penalty is a typical problem arising, e.g., in sparse spikes deconvolution or two-layer neural networks training. We show that this problem can be solved by discretizing the…

Optimization and Control · Mathematics 2020-11-04 Lenaic Chizat
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