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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

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the…

Numerical Analysis · Computer Science 2012-04-25 Dohy Hong

Splitting methods for the numerical integration of differential equations of order greater than two involve necessarily negative coefficients. This order barrier can be overcome by considering complex coefficients with positive real part.…

Numerical Analysis · Mathematics 2015-04-10 Sergio Blanes , Fernando Casas , Ander Murua

In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational…

Numerical Analysis · Mathematics 2021-10-12 Christian Beck , Sebastian Becker , Patrick Cheridito , Arnulf Jentzen , Ariel Neufeld

Operator splitting methods tailored to coupled linear port-Hamiltonian systems are developed. We present algorithms that are able to exploit scalar coupling, as well as multirate potential of these coupled systems. The obtained algorithms…

Numerical Analysis · Mathematics 2025-01-14 Jan Lorenz , Tom Zwerschke , Michael Günther , Kevin Schäfers

Treating diffusion and advection/reaction separately is an effective strategy for solving semilinear advection-diffusion-reaction equations. However, such an approach is prone to suffer from order reduction, especially in the presence of…

Numerical Analysis · Mathematics 2025-11-12 Thi Tam Dang , Lukas Einkemmer , Alexander Ostermann

It is well known that using high-order numerical algorithms to solve fractional differential equations leads to almost the same computational cost with low-order ones but the accuracy (or convergence order) is greatly improved, due to the…

Numerical Analysis · Mathematics 2017-05-25 Hengfei Ding , Changpin Li

This work introduces a methodology to solve ordinary differential equations using the Schur decomposition of the linear representation of the differential equation. This is done by first transforming the system into an upper triangular…

Dynamical Systems · Mathematics 2021-11-16 David Arnas

We provide of a method to integrate first order non-linear systems of differential equations with variable coefficients. It determines approximate solutions given initial or boundary conditions or even for Sturm-Liouville problems. This…

Classical Analysis and ODEs · Mathematics 2025-03-05 Manuel Gadella , Luis P. Lara

Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For solving these problems, one often uses coarse spatial grid…

Numerical Analysis · Mathematics 2022-07-13 Wenyuan Li , Anatoly Alikhanov , Yalchin Efendiev , Wing Tat Leung

A second-order accurate in time, positivity-preserving, and unconditionally energy stable operator splitting numerical scheme is proposed and analyzed for the system of reaction-diffusion equations with detailed balance. The scheme is…

Numerical Analysis · Mathematics 2021-09-08 Chun Liu , Cheng Wang , Yiwei Wang

We construct splitting methods suitable for the solution of the equations of magnetohydrodynamics (MHD). Due to the physical significance of the involved operators, splittings into three or even four operators with positive coefficients are…

Numerical Analysis · Mathematics 2025-03-12 Othmar Koch , Koray Acar , Winfried Auzinger , Daniel Hoffmann , Friedrich Kupka , Benedikt Moser

We describe an algorithm for the numerical solution of second order linear differential equations in the highly-oscillatory regime. It is founded on the recent observation that the solutions of equations of this type can be accurately…

Numerical Analysis · Mathematics 2015-06-23 James Bremer

This paper deals with numerical solutions to a partial differential equation of fractional order. Generally this type of equation describes a transition from anomalous diffusion to transport processes. From a phenomenological point of view,…

Numerical Analysis · Mathematics 2007-05-23 Mariusz Ciesielski , Jacek Leszczynski

The study of fractional order differential operators is receiving renewed attention in many scientific fields. In order to accommodate researchers doing work in these areas, there is a need for highly scalable numerical methods for solving…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-28 Max Carlson , Robert M. Kirby , Hari Sundar

A probabilistic method is derived for solution of ohmic circuit problems. It is compared to the standard approach, which is construction and solution of a set of coupled, linear equations manifesting Kirchhoff's laws. An example is made of…

Statistical Mechanics · Physics 2019-06-26 Clinton DeW. Van Siclen

In view of the usefulness and importance of the kinetic equation in certain physical problems, the authors derive the explicit solution of a fractional kinetic equation of general character, that unifies and extends earlier results.…

Classical Analysis and ODEs · Mathematics 2015-05-13 R. K. Saxena , A. M. Mathai , H. J. Haubold

In this paper we present iterative and noniterative splitting methods, which are used to solve stochastic Burgers' equations. The non-iterative splitting methods are based on Lie-Trotter and Strang-splitting methods, while the iterative…

Numerical Analysis · Mathematics 2021-02-03 Jürgen Geiser , Karsten Bartecki

The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent…

Numerical Analysis · Computer Science 2015-06-15 Andreas Hellander , Michael Lawson , Brian Drawert , Linda Petzold

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