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A nonlinear Helmholtz (NLH) equation with high frequencies and corner singularities is discretized by the linear finite element method (FEM). After deriving some wave-number-explicit stability estimates and the singularity decomposition for…

Numerical Analysis · Mathematics 2024-05-28 Run Jiang , Haijun Wu , Yifeng Xu , Jun Zou

We present a novel computational methodology for solving the scalar nonlinear Helmholtz equation (NLH) that governs the propagation of laser light in Kerr dielectrics. The methodology addresses two well-known challenges in nonlinear optics:…

Mathematical Physics · Physics 2009-12-07 Guy Baruch , Gadi Fibich , Semyon V. Tsynkov

This paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear…

Numerical Analysis · Mathematics 2025-06-06 Daozhe Lin , Qiang Du

Partial differential equations (PDEs) with near singular solutions pose significant challenges for traditional numerical methods, particularly in complex geometries where mesh generation and adaptive refinement become computationally…

Numerical Analysis · Mathematics 2025-07-24 Yangtao Deng , Qiaolin He , Xiaoping Wang

Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving convergence is relatively difficult and requires small load…

Numerical Analysis · Mathematics 2018-05-01 Yue Mei , Daniel E. Hurtado , Sanjay Pant , Ankush Aggarwal

Non-Markovian stochastic Schr\"odinger equations (NMSSE) are important tools in quantum mechanics, from the theory of open systems to foundations. Yet, in general, they are but formal objects: their solution can be computed numerically only…

Quantum Physics · Physics 2017-09-20 Antoine Tilloy

We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety of applications in machine learning and engineering, ranging from constrained deep neural networks, to…

Optimization and Control · Mathematics 2023-05-31 Ilgee Hong , Sen Na , Michael W. Mahoney , Mladen Kolar

We present a novel shape-approximating anisotropic re-meshing algorithm as a geometric generalization of the adaptive moving mesh method. Conventional moving mesh methods reduce the interpolation error of a mesh that discretizes a given…

Computational Geometry · Computer Science 2023-06-21 Nicolas Nebel , Albert Chern

The nonlinear Sch\"{o}dinger equation (NLSE) with a non-Hermitian term is the model for various phenomena in nonlinear open quantum systems. We deal with the Cauchy problem for the nonlocal generalization of multidimensional NLSE with a…

Mathematical Physics · Physics 2024-03-08 A. E. Kulagin , A. V. Shapovalov

We describe a grid-based numerical method for 3D hydrodynamic cosmological simulations which is adaptive in space and time and combines the best features of higher order--accurate Godunov schemes for Eulerian hydrodynamics with adaptive…

Astrophysics · Physics 2016-01-27 Michael L. Norman , Greg L. Bryan

The problem of developing an adaptive isogeometric method (AIGM) for solving elliptic second-order partial differential equations with truncated hierarchical B-splines of arbitrary degree and different order of continuity is addressed. The…

Numerical Analysis · Mathematics 2015-04-21 Annalisa Buffa , Carlotta Giannelli

Kernel methods approximate nonlinear maps in a data-driven manner by projecting the target map onto a finite-dimensional Hilbert space called the solution space. Traditionally, this space is a subspace of a fixed ambient reproducing kernel…

Numerical Analysis · Mathematics 2026-01-30 Tamás Dózsa , Andrea Angino , Zoltán Szabó , József Bokor , Matthias Voigt

This article initiates the study of space-time adaptive mesh refinements for time-dependent boundary element formulations of wave equations. Based on error indicators of residual type, we formulate an adaptive boundary element procedure for…

Numerical Analysis · Mathematics 2025-11-07 Alessandra Aimi , Giulia Di Credico , Heiko Gimperlein , Chiara Guardasoni

Solving inverse and optimization problems over solutions of nonlinear partial differential equations (PDEs) on complex spatial domains is a long-standing challenge. Here we introduce a method that parameterizes the solution using spectral…

Numerical Analysis · Mathematics 2025-10-30 James V. Roggeveen , Michael P. Brenner

Using canonical transformations we obtain localized (in space) exact solutions of the nonlinear Schr\"odinger equation (NLSE) with space and time modulated nonlinearity and in the presence of an external potential depending on space and…

Pattern Formation and Solitons · Physics 2013-07-30 L. E. Arroyo Meza , M. B. Hott , A. de Souza Dutra , P. Roy

We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase flow in porous media. The proposed…

Machine Learning · Computer Science 2025-04-28 Vinicius L S Silva , Pablo Salinas , Claire E Heaney , Matthew Jackson , Christopher C Pain

It is shown that using the similarity transformations, a set of three-dimensional p-q nonlinear Schrodinger (NLS) equations with inhomogeneous coefficients can be reduced to one-dimensional stationary NLS equation with constant or varying…

Pattern Formation and Solitons · Physics 2017-04-19 Zhenya Yan , V. V. Konotop

We consider multiple solutions to the nonlinear Schr\"odinger equation (NLS) with a partial confinement, which is physically relevant to dynamics of the Bose-Einstein condensate. Our study not only verifies the existence of positive ground…

Analysis of PDEs · Mathematics 2025-10-01 Liying Shan , Wei Shuai , Leyun Wu

A classic approach for solving differential equations with neural networks builds upon neural forms, which employ the differential equation with a discretisation of the solution domain. Making use of neural forms for time-dependent…

Neural and Evolutionary Computing · Computer Science 2022-09-02 Toni Schneidereit , Michael Breuß

A method is developed for solving quasilinear convection diffusion problems starting on a coarse mesh where the data and solution-dependent coefficients are unresolved, the problem is unstable and approximation properties do not hold. The…

Numerical Analysis · Mathematics 2015-02-10 Sara Pollock