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We introduce the concept of data-driven finite element methods. These are finite-element discretizations of partial differential equations (PDEs) that resolve quantities of interest with striking accuracy, regardless of the underlying mesh…

Numerical Analysis · Mathematics 2022-11-15 Ignacio Brevis , Ignacio Muga , Kristoffer G. van der Zee

The semilinear stochastic wave equation on the sphere driven by multiplicative Gaussian noise is discretized by a stochastic trigonometric integrator in time and a spectral Galerkin approximation in space based on the spherical harmonic…

Numerical Analysis · Mathematics 2026-02-03 David Cohen , Stefano Di Giovacchino , Annika Lang

In this paper, we propose a linearized finite element method (FEM) for solving the cubic nonlinear Schr\"{o}dinger equation with wave operator. In this method, a modified leap-frog scheme is applied for time discretization and a Galerkin…

Numerical Analysis · Mathematics 2019-02-25 Wentao Cai , Dongdong He , Kejia Pan

This paper applies a discontinuous Galerkin finite element method to the Kelvin-Voigt viscoelastic fluid motion equations when the forcing function is in $L^\infty({\bf L}^2)$-space. Optimal a priori error estimates in $L^\infty({\bf…

Numerical Analysis · Mathematics 2022-02-10 Saumya Bajpai , Deepjyoti Goswami , Kallol Ray

We introduce a general framework for approximating parabolic Stochastic Partial Differential Equations (SPDEs) based on fluctuation-dissipation balance. Using this approach we formulate Stochastic Discontinuous Galerkin Methods (SDGM). We…

Numerical Analysis · Mathematics 2023-02-28 Will Pazner , Nathaniel Trask , Paul J. Atzberger

Explicit, unconditionally stable, high-order schemes for the approximation of some first- andsecond-order linear, time-dependent partial differential equations (PDEs) are proposed.The schemes are based on a weak formulation of a…

Numerical Analysis · Mathematics 2017-11-15 Olivier Bokanowski , Giorevinus Simarmata

We study the numerical approximation of stochastic evolution equations with a monotone drift driven by an infinite-dimensional Wiener process. To discretize the equation, we combine a drift-implicit two-step BDF method for the temporal…

Numerical Analysis · Mathematics 2021-05-20 Raphael Kruse , Rico Weiske

In this paper a finite difference/local discontinuous Galerkin method for the fractional diffusion-wave equation is presented and analyzed. We first propose a new finite difference method to approximate the time fractional derivatives, and…

Numerical Analysis · Mathematics 2015-07-29 Leilei Wei

In this paper, the finite element Galerkin method is applied to the equations of motion arising in the Kelvin-Voigt viscoelastic fluid flow model, when the forcing function is in $L^{\infty}(L^2)$. Some a priori estimates for the exact…

Numerical Analysis · Mathematics 2015-12-01 Ambit K. Pany , Saumya Bajpai , Amiya K. Pani

Error estimates are proved for finite element approximations to the solution of second-order hyperbolic partial differential equations with coefficients varying in both space and time. Optimal rates of convergence in the energy norm are…

Numerical Analysis · Mathematics 2026-03-17 Oussama Al Jarroudi , Marcus J. Grote

This paper is concerned with fully discrete mixed finite element approximations of the time-dependent stochastic Stokes equations with multiplicative noise. A prototypical method, which comprises of the Euler-Maruyama scheme for time…

Numerical Analysis · Mathematics 2020-04-28 Xiaobing Feng , Hailong Qiu

The numerical solution of time-dependent radiative transfer problems is challenging, both, due to the high dimension as well as the anisotropic structure of the underlying integro-partial differential equation. In this paper we propose a…

Numerical Analysis · Mathematics 2015-12-04 Herbert Egger , Matthias Schlottbom

Stochastic differential equations are an important modeling class in many disciplines. Consequently, there exist many methods relying on various discretization and numerical integration schemes. In this paper, we propose a novel,…

Machine Learning · Computer Science 2019-05-29 Gabriele Abbati , Philippe Wenk , Michael A Osborne , Andreas Krause , Bernhard Schölkopf , Stefan Bauer

The purpose of the research is to find the numerical solutions to the system of time dependent nonlinear parabolic partial differential equations (PDEs) utilizing the Modified Galerkin Weighted Residual Method (MGWRM) with the help of…

Numerical Analysis · Mathematics 2023-07-11 Hazrat Ali , Nilormy Gupta Trisha , Md. Shafiqul Islam

In this article, we have analyzed the full discretization of the Stochastic semilinear Schr\"{o}dinger equation in a bounded convex polygonal domain driven by multiplicative Wiener noise. We use the finite element method for spatial…

Numerical Analysis · Mathematics 2025-04-22 Suprio Bhar , Mrinmay Biswas , Mangala Prasad

A novel discontinuous Galerkin (DG) method is developed to solve time-dependent bi-harmonic type equations involving fourth derivatives in one and multiple space dimensions. We present the spatial DG discretization based on a mixed…

Numerical Analysis · Mathematics 2019-10-02 Hailiang Liu , Peimeng Yin

This paper is concerned with finite element approximations of $W^{2,p}$ strong solutions of second-order linear elliptic partial differential equations (PDEs) in non-divergence form with continuous coefficients. A nonstandard (primal)…

Numerical Analysis · Mathematics 2015-05-13 Xiaobing Feng , Lauren Hennings , Michael Neilan

Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions…

Numerical Analysis · Mathematics 2025-03-25 Markus Bachmayr , Henrik Eisenmann , Igor Voulis

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces.…

Numerical Analysis · Mathematics 2024-12-18 Brendan Keith , Thomas M. Surowiec

We propose a new tamed Milstein-type scheme for stochastic differential equation with Markovian switching when drift coefficient is assumed to grow super-linearly. The strong rate of convergence is shown to be equal to $1.0$ under mild…

Probability · Mathematics 2019-09-18 Chaman Kumar , Tejinder Kumar