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This works deals with one dimensional infinite perturbation - namely line defects - in periodic media. In optics, such defects are created to construct an (open) waveguide that concentrates light. The existence and the computation of the…

Spectral Theory · Mathematics 2013-01-31 Sonia Fliss

We present our deep learning framework to solve and accelerate the Time-Dependent partial differential equation's solution of one and two spatial dimensions. We demonstrate DiffusionNet solver by solving the 2D transient heat conduction…

Machine Learning · Computer Science 2020-11-20 Mahmoud Asem

Quantification of the number of variables needed to locally explain complex data is often the first step to better understanding it. Existing techniques from intrinsic dimension estimation leverage statistical models to glean this…

Machine Learning · Computer Science 2023-12-13 Eric Yeats , Cameron Darwin , Frank Liu , Hai Li

This paper is concerned with a new type of inverse obstacle problem governed by a variable-order time-fraction diffusion equation in a bounded domain. The unknown obstacle is a region where the space dependent variable-order of fractional…

Analysis of PDEs · Mathematics 2022-02-18 Masaru Ikehata , Yavar Kian

Undoing the image formation process and therefore decomposing appearance into its intrinsic properties is a challenging task due to the under-constraint nature of this inverse problem. While significant progress has been made on inferring…

Computer Vision and Pattern Recognition · Computer Science 2015-11-16 Konstantinos Rematas , Tobias Ritschel , Mario Fritz , Efstratios Gavves , Tinne Tuytelaars

In this paper we introduce a method for solving linear and nonlinear scattering problems for wave equations using a new hybrid approach. This new approach consists of a reformulation of the governing equations into a form that can be solved…

Numerical Analysis · Mathematics 2018-07-04 Aihua Lin , Anastasiia Kuzmina , Per Kristen Jakobsen

We present a new algorithm for numerical computation of large eigenvalues and associated eigenfunctions of the Dirichlet Laplacian in a smooth, star-shaped domain in $\mathbb{R}^d$, $d\ge 2$. Conventional boundary-based methods require a…

Numerical Analysis · Mathematics 2011-12-30 Alex H. Barnett , Andrew Hassell

This paper introduces a boundary integral equation for time-harmonic electromagnetic scattering by composite dielectric objects. The formulation extends the classical M\"uller equation to composite structures through the global multi-trace…

Numerical Analysis · Mathematics 2026-01-21 Van Chien Le , Kristof Cools

In this paper, an efficient solver for the Helmholtz equation using a noval approximation space is developed. The ingradients of the method include the approximation space recently proposed, a discontinuous Galerkin scheme extensively used,…

Numerical Analysis · Mathematics 2025-12-11 Shuhai Zhao

Problems with localized nonhomogeneous material properties present well-known challenges for numerical simulations. In particular, such problems may feature large differences in length scales, causing difficulties with meshing and…

Numerical Analysis · Mathematics 2021-11-23 Alex Viguerie , Silvia Bertoluzza , Alessandro Veneziani , Ferdinando Auricchio

A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…

Numerical Analysis · Mathematics 2017-12-08 Brendan Keith , Socratis Petrides , Federico Fuentes , Leszek Demkowicz

Solving time-harmonic wave propagation problems by iterative methods is a difficult task, and over the last two decades, an important research effort has gone into developing preconditioners for the simplest representative of such wave…

Numerical Analysis · Mathematics 2018-02-22 Martin J. Gander , Hui Zhang

We study a discretization technique for the parabolic fractional obstacle problem in bounded domains. The fractional Laplacian is realized as the Dirichlet-to-Neumann map for a nonuniformly elliptic equation posed on a semi-infinite…

Numerical Analysis · Mathematics 2015-07-09 Enrique Otarola , Abner J. Salgado

While much attention of neural network methods is devoted to high-dimensional PDE problems, in this work we consider methods designed to work for elliptic problems on domains $\Omega \subset \mathbb{R} ^d, $ $d=1,2,3$ in association with…

Numerical Analysis · Mathematics 2025-02-06 Georgios Grekas , Charalambos G. Makridakis

The displacement field for three dimensional dynamic elasticity problems in the frequency domain can be decomposed into a sum of a longitudinal and a transversal part known as a Helmholtz decomposition. The Cartesian components of both the…

Computational Physics · Physics 2019-10-02 Evert Klaseboer , Qiang Sun , Derek Y. C. Chan

We focus here on a class of fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. We design a novel second-order fully discrete mixed finite element method to…

Numerical Analysis · Mathematics 2020-08-28 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

This paper presents smoothed combined field integral equations for the solution of Dirichlet and Neumann exterior Helmholtz problems. The integral equations introduced in this paper are smooth in the sense that they only involve…

Numerical Analysis · Mathematics 2017-01-16 Carlos Pérez-Arancibia

We use the work of Milton, Seppecher, and Bouchitt\'{e} on variational principles for waves in lossy media to formulate a finite element method for solving the complex Helmholtz equation that is based entirely on minimization. In…

Numerical Analysis · Mathematics 2010-08-02 Russell B. Richins , David C. Dobson

A new method for numerical solving of boundary problem for ordinary differential equations with slowly varying coefficients which is aimed at better representation of solutions in the regions of their rapid oscillations or exponential…

Computational Physics · Physics 2007-05-23 V. E. Moiseenko , V. V. Pilipenko

A core problem in machine learning is to learn expressive latent variables for model prediction on complex data that involves multiple sub-components in a flexible and interpretable fashion. Here, we develop an approach that improves…

Machine Learning · Computer Science 2024-02-13 Yi-Lin Tuan , Zih-Yun Chiu , William Yang Wang