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Different families of Runge-Kutta-Nystr\"om (RKN) symplectic splitting methods of order 8 are presented for second-order systems of ordinary differential equations and are tested on numerical examples. They show a better efficiency than…

Numerical Analysis · Mathematics 2022-07-26 F. Casas , S. Blanes , A. Escorihuela-Tomàs

This paper concerns the convergence of an iterative scheme for 2D stochastic primitive equations on a bounded domain. The stochastic system is split into two equations: a deterministic 2D primitive equations with random initial value and a…

Probability · Mathematics 2019-07-09 Xuhui Peng , Rangrang Zhang

In view of the existing limitations of sequential computing, parallelization has emerged as an alternative in order to improve the speedup of numerical simulations. In the framework of evolutionary problems, space-time parallel methods…

Numerical Analysis · Mathematics 2025-02-13 Andrés Arrarás , Francisco J. Gaspar , Iñigo Jimenez-Ciga , Laura Portero

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 develop a novel stochastic primal dual splitting method with Bregman distances for solving a structured composite problems involving infimal convolutions in non-Euclidean spaces. The sublinear convergence in expectation of the…

Optimization and Control · Mathematics 2021-03-17 Nguyen Van Dung , Băng Công Vũ

The factorisation method commonly used in linear supersymmetric quantum mechanics is extended, such that it can be applied to nonlinear quantum mechanical systems. The new method is distinguishable from the linear formalism, as the…

Mathematical Physics · Physics 2017-08-25 Rosie Hayward , Fabio Biancalana

In contrast with the diffusion equation which smoothens the initial data to $C^\infty$ for $t>0$ (away from the corners/edges of the domain), the subdiffusion equation only exhibits limited spatial regularity. As a result, one generally…

Numerical Analysis · Mathematics 2023-07-17 Buyang Li , Zongze Yang , Zhi Zhou

We provide a systematic comparison of two numerical methods to solve the widely used nonlinear Schr\"odinger equation. The first one is the standard second order split-step (SS2) method based on operator splitting approach. The second one…

Computational Physics · Physics 2021-09-28 Anastassiya Semenova , Sergey A. Dyachenko , Alexander O. Korotkevich , Pavel M. Lushnikov

This paper studies bulk-surface splitting methods of first order for (semi-linear) parabolic partial differential equations with dynamic boundary conditions. The proposed Lie splitting scheme is based on a reformulation of the problem as a…

Numerical Analysis · Mathematics 2021-08-19 Robert Altmann , Balázs Kovács , Christoph Zimmer

This paper considers computational methods that split a vector field into three components in the case when both the vector field and the split components might be unbounded. We first employ classical Taylor expansion which, after some…

Numerical Analysis · Mathematics 2024-03-25 Arieh Iserles , Karolina Kropielnicka

Simulation of many-particle system evolution by molecular dynamics takes to decrease integration step to provide numerical scheme stability on the sufficiently large time interval. It leads to a significant increase of the volume of…

Numerical Analysis · Mathematics 2016-05-19 Eduard G. Nikonov

The numerical solution of a linear Schr\"odinger equation in the semiclassical regime is very well understood in a torus $\mathbb{T}^d$. A raft of modern computational methods are precise and affordable, while conserving energy and…

Numerical Analysis · Mathematics 2022-01-17 Arieh Iserles , Karolina Kropielnicka , Katharina Schratz , Marcus Webb

We consider an implicit finite difference scheme on uniform grids in time and space for the Cauchy problem for a second order parabolic stochastic partial differential equation where the parabolicity condition is allowed to degenerate. Such…

Numerical Analysis · Mathematics 2016-08-29 Eric Joseph Hall

This paper deals with the numerical integration of well-posed multiscale systems of ODEs or evolutionary PDEs. As these systems appear naturally in engineering problems, time-subcycling techniques are widely used every day to improve…

Analysis of PDEs · Mathematics 2015-10-07 Guillaume Dujardin , Pauline Lafitte

We study a numerical approximation for a nonlinear variable-order fractional differential equation via an integral equation method. Due to the lack of the monotonicity of the discretization coefficients of the variable-order fractional…

Numerical Analysis · Mathematics 2021-10-12 Xiangcheng Zheng

Recently proposed quasi-classical DBAR-dressing method provides a systematic approach to study the weakly dispersive limit of integrable systems. We apply the quasi-classical DBAR-dressing method to describe dispersive corrections of any…

Exactly Solvable and Integrable Systems · Physics 2009-11-10 Boris Konopelchenko , Antonio Moro

Variational methods based on optimization strategies are proposed to numerically solve a large family of nonlinear partial differential equations. They are all particular instances of gradient flows with general costs, including the…

Numerical Analysis · Mathematics 2026-04-23 Luis M. Briceño-Arias , José A. Carrillo , Dante Kalise , Francisco J. Silva , Li Wang

We establish error bounds of the Lie-Trotter splitting ($S_1$) and Strang splitting ($S_2$) for the Dirac equation in the nonrelativistic limit regime in the absence of external magnetic potentials, with a small parameter $0<\varepsilon\leq…

Numerical Analysis · Mathematics 2021-10-26 Weizhu Bao , Yongyong Cai , Jia Yin

We show how the standard (St{\"o}rmer-Verlet) splitting method for differential equations of Hamiltonian mechanics (with accuracy of order $\tau^2$ for a timestep of length $\tau$) can be improved in a systematic manner without using the…

Numerical Analysis · Mathematics 2012-05-15 Asif Mushtaq , Anne Kværnø , Kåre Olaussen

Several structure-learning algorithms for staged trees, asymmetric extensions of Bayesian networks, have been proposed. However, these either do not scale efficiently as the number of variables considered increases, a priori restrict the…

Methodology · Statistics 2022-11-15 Peter Strong , Jim Q. Smith