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A space-time fully adaptive multiresolution method for evolutionary non-linear partial differential equations is presented introducing an improved local time-stepping method. The space discretisation is based on classical finite volumes,…

Numerical Analysis · Mathematics 2019-05-22 Müller Moreira Lopes , Margarete Oliveira Domingues , Kai Schneider , Odim Mendes

A novel class of high-order linearly implicit energy-preserving integrating factor Runge-Kutta methods are proposed for the nonlinear Schr\"odinger equation. Based on the idea of the scalar auxiliary variable approach, the original equation…

Numerical Analysis · Mathematics 2021-12-07 Chaolong Jiang , Jin Cui , Xu Qian , Songhe Song

In this article, a family of two- and three-stage explicit multiquadric (MQ) and inverse multiquadric (IMQ) radial basis functions (RBFs) Runge-Kutta methods are introduced for solving ordinary differential equations. These methods are…

Numerical Analysis · Mathematics 2025-09-23 Shipra Mahata , Samala Rathan

We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient…

Numerical Analysis · Mathematics 2014-01-09 David I. Ketcheson , Colin B. Macdonald , Steven J. Ruuth

We apply the concept of effective order to strong stability preserving (SSP) explicit Runge-Kutta methods. Relative to classical Runge-Kutta methods, methods with an effective order of accuracy are designed to satisfy a relaxed set of order…

Numerical Analysis · Mathematics 2014-01-09 Yiannis Hadjimichael , Colin B. Macdonald , David I. Ketcheson , James H. Verner

The work deals with two major topics concerning the numerical analysis of Runge-Kutta-like (RK-like) methods, namely their stability and order of convergence. RK-like methods differ from additive RK methods in that their coefficients are…

Numerical Analysis · Mathematics 2025-06-26 Thomas Izgin

Recently, in a paper by Jentzen and Kloeden [Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 465 (2009) 649-667], a new method for simulating nearly linear stochastic partial differential equations (SPDEs) with additive noise has been…

Probability · Mathematics 2012-11-01 Arnulf Jentzen , Peter Kloeden , Georg Winkel

Implicit-explicit (IMEX) Runge-Kutta methods play a major rule in the numerical treatment of differential systems governed by stiff and non-stiff terms. This paper discusses order conditions and symplecticity properties of a class of IMEX…

Numerical Analysis · Mathematics 2012-02-07 Michael Herty , Lorenzo Pareschi , Sonja Steffensen

This manuscript introduces a fourth-order Runge-Kutta based implicit-explicit scheme in time along with compact fourth-order finite difference scheme in space for the solution of one-dimensional Kuramoto-Sivashinsky equation with periodic…

Numerical Analysis · Mathematics 2019-11-28 Harish Bhatt , Abhinandan Chowdhury

Statistical regression models whose mean functions are represented by ordinary differential equations (ODEs) can be used to describe phenomenons dynamical in nature, which are abundant in areas such as biology, climatology and genetics. The…

Methodology · Statistics 2017-05-15 Kyoungjae Lee , Jaeyong Lee , Sarat C. Dass

With this short note, we close a gap in the linear stability theory of block predictor-corrector Runge-Kutta schemes originally proposed for the parallel solution of ODEs.

Numerical Analysis · Mathematics 2023-06-02 Friedemann Kemm

We further develop a simple modification of Runge--Kutta methods that guarantees conservation or stability with respect to any inner-product norm. The modified methods can be explicit and retain the accuracy and stability properties of the…

Numerical Analysis · Mathematics 2019-05-27 David I. Ketcheson

We consider the efficient numerical solution of coupled dynamical systems, consisting of a small nonlinear part and a large linear time invariant part, possibly stemming from spatial discretization of an underlying partial differential…

Numerical Analysis · Mathematics 2018-11-27 Herbert Egger , Vsevolod Shashkov , Kersten Schmidt

In recent years, many positivity-preserving schemes for initial value problems have been constructed by modifying a Runge--Kutta (RK) method by weighting the right-hand side of the system of differential equations with solution-dependent…

Numerical Analysis · Mathematics 2025-02-26 Thomas Izgin , David I. Ketcheson , Andreas Meister

Stochastic Hamiltonian partial differential equations, which possess the multi-symplectic conservation law, are an important and fairly large class of systems. The multi-symplectic methods inheriting the geometric features of stochastic…

Numerical Analysis · Mathematics 2022-08-10 Jialin Hong , Baohui Hou , Qiang Li , Liying Sun

We present a novel and general methodology for building second-order finite volume implicit-explicit Runge-Kutta numerical schemes for solving two-dimensional financial parabolic PDEs with mixed derivatives. The methods achieve second-order…

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate…

Numerical Analysis · Computer Science 2014-08-19 Hong Zhang , Adrian Sandu , Paul Tranquilli

Recently a new class of nonlinearly partitioned Runge--Kutta (NPRK) methods was proposed for nonlinearly partitioned systems of autonomous ordinary differential equations, $y' = F(y,y)$. The target class of problems are ones in which…

Numerical Analysis · Mathematics 2025-04-10 Brian K. Tran , Ben S. Southworth , Tommaso Buvoli

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

For a large class of fully nonlinear parabolic equations, which include gradient flows for energy functionals that depend on the solution gradient, the semidiscretization in time by implicit Runge-Kutta methods such as the Radau IIA methods…

Numerical Analysis · Mathematics 2016-06-14 Peer C. Kunstmann , Buyang Li , Christian Lubich