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We derive computable error estimates for finite element approximations of linear elliptic partial differential equations (PDE) with rough stochastic coefficients. In this setting, the exact solutions contain high frequency content that…

Numerical Analysis · Mathematics 2018-09-18 Eric Joseph Hall , Håkon Hoel , Mattias Sandberg , Anders Szepessy , Raúl Tempone

We consider a linear elliptic partial differential equation (PDE) with a generic uniformly bounded parametric coefficient. The solution to this PDE problem is approximated in the framework of stochastic Galerkin finite element methods. We…

Numerical Analysis · Mathematics 2020-06-05 Alex Bespalov , Feng Xu

We present and analyse a new conforming space-time Galerkin discretisation of a semi-linear wave equation, based on a variational formulation derived from De Giorgi's elliptic regularisation viewpoint of the wave equation in second-order…

Numerical Analysis · Mathematics 2025-10-22 Lehel Banjai , Emmanuil H. Georgoulis , Brian Hennessy

In this paper, we propose a novel adaptive finite element method for an elliptic equation with line Dirac delta functions as a source term. We first study the well-posedness and global regularity of the solution in the whole domain. Instead…

Numerical Analysis · Mathematics 2022-07-12 Huihui Cao , Hengguang Li , Nianyu Yi , Peimeng Yin

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

We consider the initial/boundary value problem for a diffusion equation involving multiple time-fractional derivatives on a bounded convex polyhedral domain. We analyze a space semidiscrete scheme based on the standard Galerkin finite…

Numerical Analysis · Mathematics 2015-06-18 Bangti Jin , Raytcho Lazarov , Yikan Liu , Zhi Zhou

In this paper, we present a numerical scheme to solve the initial-boundary value problem for backward stochastic partial differential equations of parabolic type. Based on the Galerkin method, we approximate the original equation by a…

Optimization and Control · Mathematics 2015-07-16 Yanqing Wang

An operator-splitting finite element scheme for the time-dependent, high-dimensional radiative transfer equation is presented in this paper. The streamline upwind Petrov-Galerkin finite element method and discontinuous Galerkin finite…

Numerical Analysis · Mathematics 2022-03-22 Sashikumaar Ganesan , Maneesh Kumar Singh

We devise an a posteriori error estimator for an affine optimal control problem subject to a semilinear elliptic PDE and control constraints. To approximate the problem, we consider a semidiscrete scheme based on the variational…

Optimization and Control · Mathematics 2025-05-08 Francisco Fuica , Nicolai Jork

We study solution techniques for parabolic equations with fractional diffusion and Caputo fractional time derivative, the latter being discretized and analyzed in a general Hilbert space setting. The spatial fractional diffusion is realized…

Numerical Analysis · Mathematics 2015-03-05 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

This paper is concerned with a posteriori error bounds for linear transport equations and related questions of contriving corresponding adaptive solution strategies in the context of Discontinuous-Petrov-Galerkin schemes. After indicating…

Numerical Analysis · Mathematics 2019-02-22 W. Dahmen , R. P. Stevenson

Discrete gradient methods are a powerful tool for the time discretization of dynamical systems, since they are structure-preserving regardless of the form of the total energy. In this work, we discuss the application of discrete gradient…

Numerical Analysis · Mathematics 2026-01-06 Philipp L. Kinon , Riccardo Morandin , Philipp Schulze

This work concerns the numerical solution of a coupled system of self-consistent reaction-drift-diffusion-Poisson equations that describes the macroscopic dynamics of charge transport in photoelectrochemical (PEC) solar cells with reactive…

Numerical Analysis · Mathematics 2017-03-16 Michael Harmon , Irene M. Gamba , Kui Ren

In this paper, we investigate a sequentially decoupled numerical method for solving the fully coupled quasi-static thermo-poroelasticity problems with nonlinear convective transport. The symmetric interior penalty discontinuous Galerkin…

Numerical Analysis · Mathematics 2025-09-09 Fan Chen , Ming Cui , Chenguang Zhou

A general framework for the numerical approximation of evolution problems is presented that allows to preserve exactly an underlying Hamiltonian- or gradient structure. The approach relies on rewriting the evolution problem in a particular…

Numerical Analysis · Mathematics 2018-12-12 Herbert Egger

We introduce a multitree-based adaptive wavelet Galerkin algorithm {for} space-time discretized linear parabolic partial differential equations, focusing on time-periodic problems. It is shown that the method converges with the best…

Numerical Analysis · Mathematics 2014-01-23 Sebastian Kestler , Kristina Steih , Karsten Urban

In this paper, we introduce a numerical solution of a stochastic partial differential equation (SPDE) of elliptic type using polynomial chaos along side with polynomial approximation at Sinc points. These Sinc points are defined by a…

Numerical Analysis · Mathematics 2019-04-08 Maha Youssef , Roland Pulch

We consider a fully discretized numerical scheme for parabolic stochastic partial differential equations with multiplicative noise. Our abstract framework can be applied to formulate a non-iterative domain decomposition approach. Such…

Numerical Analysis · Mathematics 2024-12-16 Monika Eisenmann , Eskil Hansen , Marvin Jans

A discontinuous Galerkin (dG) method for the numerical solution of initial/boundary value multi-compartment partial differential equation (PDE) models, interconnected with interface conditions, is presented and analysed. The study of…

Numerical Analysis · Mathematics 2013-04-16 Andrea Cangiani , Emmanuil H. Georgoulis , Max Jensen

We present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional subspaces whose basis functions are realizations of a sequence…

Machine Learning · Computer Science 2021-06-01 Mark Ainsworth , Justin Dong