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Symplectic integration methods based on operator splitting are well established in many branches of science. For Hamiltonian systems which split in more than two parts, symplectic methods of higher order have been studied in detail only for…

We consider a class of linear Vlasov partial differential equations driven by Wiener noise. Different types of stochastic perturbations are treated: additive noise, multiplicative It\^o and Stratonovich noise, and transport noise. We…

Numerical Analysis · Mathematics 2024-03-01 Charles-Edouard Bréhier , David Cohen

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

We present a hierarchical computation approach for solving finite-time optimal control problems using operator splitting methods. The first split is performed over the time index and leads to as many subproblems as the length of the…

Optimization and Control · Mathematics 2013-04-09 Georgios Stathopoulos , Tamás Keviczky , Yang Wang

In this work, we explore the use of operator splitting algorithms for solving regularized structural topology optimization problems. The context is the classical structural design problems (e.g., compliance minimization and compliant…

Optimization and Control · Mathematics 2013-07-22 Cameron Talischi , Glaucio H. Paulino

Stochastic domain decomposition is proposed as a novel method for solving the two-dimensional Maxwell's equations as used in the magnetotelluric method. The stochastic form of the exact solution of Maxwell's equations is evaluated using…

The use of operator-splitting methods to solve differential equations is widespread, but the methods are generally only defined for a given number of operators, most commonly two. Most operator-splitting methods are not generalizable to…

Numerical Analysis · Mathematics 2024-07-04 Raymond J. Spiteri , Siqi Wei

In this paper, we provide different splitting methods for solving distributionally robust optimization problems in cases where the uncertainties are described by discrete distributions. The first method involves computing the proximity…

Optimization and Control · Mathematics 2024-10-30 Luis Briceño-Arias , Sergio López-Rivera , Emilio Vilches

This article presents explicit exponential integrators for stochastic Maxwell's equations driven by both multiplicative and additive noises. By utilizing the regularity estimate of the mild solution, we first prove that the strong order of…

Numerical Analysis · Mathematics 2020-04-22 David Cohen , Jianbo Cui , Jialin Hong , Liying Sun

We present a higher-order extension of the dual cell method for the time-domain Maxwell equations in three spatial dimensions. The approach builds upon a variational reinterpretation of the Finite Integration Technique on dual meshes and…

Numerical Analysis · Mathematics 2026-04-16 Lorenzo Codecasa , Bernard Kapidani , Joachim Schöberl , Markus Wess

We present a method for constructing numerical schemes with up to 3rd strong convergence order for solution of a class of stochastic differential equations, including equations of the Langevin type. The construction proceeds in two stages.…

High Energy Physics - Lattice · Physics 2025-04-08 Andrey Shkerin , Sergey Sibiryakov

In this paper, we discuss the different splitting approaches to solve the Gross-Pitaevskii equation numerically. We consider conservative finite-difference schemes and spectral methods for the spatial discretisation. Further, we apply…

Numerical Analysis · Mathematics 2019-02-18 Juergen Geiser , Amirbahador Nasari

The splitting method is a powerful method for solving partial differential equations. Various splitting methods have been designed to separate different physics, nonlinearities, and so on. Recently, a new splitting approach has been…

Numerical Analysis · Mathematics 2023-03-22 Yalchin Efendiev , Wing Tat Leung , Wenyuan Li , Zecheng Zhang

This article introduces the splitting method to systems responding to rough paths as external stimuli. The focus is on nonlinear partial differential equations with rough noise but we also cover rough differential equations. Applications to…

Probability · Mathematics 2010-08-04 Peter Friz , Harald Oberhauser

In this paper, we present splitting algorithms to solve multicomponent transport models with Maxwell-Stefan-diffusion approaches. The multicomponent models are related to transport problems, while we consider plasma processes, in which the…

Numerical Analysis · Mathematics 2023-06-27 Juergen Geiser

This work is concerned with existence of weak solutions to discon- tinuous stochastic differential equations driven by multiplicative Gaus- sian noise and sliding mode control dynamics generated by stochastic differential equations with…

Optimization and Control · Mathematics 2015-04-27 Viorel Barbu , Stefano Bonaccorsi , Luciano Tubaro

In this paper we focus on the stochastic Euler-Poincar\'{e} equations with pseudo-differential/multiplicative noise. We first establish two new cancellation properties on pseudo-differential operators, which play a key role in energy…

Analysis of PDEs · Mathematics 2022-09-16 Hao Tang

Calculating cost-effective solutions to particle dynamics in viscous flows is an important problem in many areas of industry and nature. We implement a second-order symmetric splitting method on the governing equations for a rigid…

Computational Physics · Physics 2018-04-09 Benjamin Tapley , Elena Celledoni , Brynjulf Owren , Helge I. Andersson

We present several methods, which utilize symplectic integration techniques based on two and three part operator splitting, for numerically solving the equations of motion of the disordered, discrete nonlinear Schr\"odinger (DDNLS)…

Computational Physics · Physics 2016-04-11 Enrico Gerlach , Jan Meichsner , Charalampos Skokos

We consider the linear Schr\"odinger equation and its discretization by split-step methods where the part corresponding to the Laplace operator is approximated by the midpoint rule. We show that the numerical solution coincides with the…

Numerical Analysis · Mathematics 2009-01-12 Arnaud Debussche , Erwan Faou