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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

This article is devoted to the construction of new numerical methods for the semiclassical Schr\"odinger equation. A phase-amplitude reformulation of the equation is described where the Planck constant epsilon is not a singular parameter.…

Analysis of PDEs · Mathematics 2018-10-15 Philippe Chartier , Loïc Le Treust , Florian Méhats

We consider an initial/boundary value problem for one-dimensional fractional-order parabolic equations with a space fractional derivative of Riemann-Liouville type and order $\alpha\in (1,2)$. We study a spatial semidiscrete scheme with the…

Numerical Analysis · Mathematics 2013-10-02 Bangti Jin , Raytcho Lazarov , Joseph Pasciak , Zhi Zhou

A common strategy in the numerical solution of partial differential equations is to define a uniform discretization of a tensor-product multi-dimensional logical domain, which is mapped to a physical domain through a given coordinate…

Computational Physics · Physics 2019-09-13 Edoardo Zoni , Yaman Güçlü

In this paper, we present a splitting algorithm to solve multicomponent transport models. These models are related to plasma simulations, in which we consider the local thermodynamic equilibrium and weakly ionised plasma-mixture models that…

Analysis of PDEs · Mathematics 2019-10-09 Juergen Geiser

In this paper we construct a third order method for solving additively split autonomous stiff systems of ordinary differential equations. The constructed additive method is L-stable with respect to the implicit part and allows to use an…

Numerical Analysis · Mathematics 2009-02-24 Evgeny Novikov , Anton Tuzov

In this paper, we combine the operator splitting methodology for abstract evolution equations with that of stochastic methods for large-scale optimization problems. The combination results in a randomized splitting scheme, which in a given…

Numerical Analysis · Mathematics 2022-10-12 Monika Eisenmann , Tony Stillfjord

We discuss a spectral method for the numerical solution of the Vlasov-Poisson system where the velocity space is decomposed by means of an Hermite basis. We describe a semi-implicit time discretization that extends the range of numerical…

Plasma Physics · Physics 2013-12-19 Enrico Camporeale , Gian Luca Delzanno , Benjamin K. Bergen , J. David Moulton

We introduce an algebraic multiscale method for two--dimensional problems. The method uses the generalized multiscale finite element method based on the quadrilateral nonconforming finite element spaces. Differently from the…

Numerical Analysis · Mathematics 2022-01-27 Kanghun Cho , Imbunm Kim , Raehyun Kim , Dongwoo Sheen

Recently Ahmadi et al. (2021) and Tagliaferro (2022) proposed some iterative methods for the numerical solution of linear systems which, under the classical hypothesis of strict diagonal dominance, typically converge faster than the Jacobi…

Numerical Analysis · Mathematics 2024-04-11 Paolo Novati , Fulvio Tagliaferro , Marino Zennaro

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

Operator-splitting methods are widely used to solve differential equations, especially those that arise from multi-scale or multi-physics models, because a monolithic (single-method) approach may be inefficient or even infeasible. The most…

Numerical Analysis · Mathematics 2025-01-07 Siqi Wei , Victoria Guenter , Raymond J. Spiteri

A parallel splitting method is proposed for solving systems of coupled monotone inclusions in Hilbert spaces. Convergence is established for a wide class of coupling schemes. Unlike classical alternating algorithms, which are limited to two…

Optimization and Control · Mathematics 2009-02-26 H. Attouch , L. M. Briceno-Arias , P. L. Combettes

In this paper, a nonlinear system of fractional ordinary differential equations with multiple scales in time is investigated. We are interested in the effective long-term computation of the solution. The main challenge is how to obtain the…

Numerical Analysis · Mathematics 2022-01-07 Zhaoyang Wang , Ping Lin

The alternating direction method of multipliers (ADMM) is a widely used method for solving many convex minimization models arising in signal and image processing. In this paper, we propose an inertial ADMM for solving a two-block separable…

Optimization and Control · Mathematics 2021-04-02 Yang Yang , Yuchao Tang

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

In this work we study arbitrary-order hybrid discretizations of Friedrichs systems. Friedrichs systems provide a framework that goes beyond the standard classification of partial differential equations into hyperbolic or elliptic, and are…

Numerical Analysis · Mathematics 2026-02-12 Daniele Di Pietro , Aurelio Spadotto

In this paper, we study the numerical solutions of the multi-dimensional spatial fractional Allen-Cahn equations. After semi-discretization for the spatial fractional Riesz derivative, a system of nonlinear ordinary differential equations…

Numerical Analysis · Mathematics 2022-09-20 Yao-Yuan Cai , Zhi-Wei Fang , Hao Chen , Hai-Wei Sun

We analyze several generic proximal splitting algorithms well suited for large-scale convex nonsmooth optimization. We derive sublinear and linear convergence results with new rates on the function value suboptimality or distance to the…

Optimization and Control · Mathematics 2022-01-28 Laurent Condat , Grigory Malinovsky , Peter Richtárik

This paper is about how to partition decision variables while decomposing a large-scale optimization problem for the best performance of distributed solution methods. Solving a large-scale optimization problem sequen- tially can be…

Optimization and Control · Mathematics 2017-10-26 Yuchen Zheng , Ilbin Lee , Nicoleta Serban