English
Related papers

Related papers: Modified Singly-Runge-Kutta-TASE methods for the n…

200 papers

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

The aim of this paper is to design the explicit radial basis function (RBF) Runge-Kutta methods for the initial value problem. We construct the two-, three- and four-stage RBF Runge-Kutta methods based on the Gaussian RBF Euler method with…

Numerical Analysis · Mathematics 2024-03-14 Jiaxi Gu , Xinjuan Chen , Jae-Hun Jung

This paper investigates the performance of a subclass of exponential integrators, specifically explicit exponential Runge--Kutta methods. It is well known that third-order methods can suffer from order reduction when applied to linearized…

Numerical Analysis · Mathematics 2024-12-30 Thi Tam Dang , Trung Hau Hoang

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

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

We study gradient-based optimization methods obtained by directly discretizing a second-order ordinary differential equation (ODE) related to the continuous limit of Nesterov's accelerated gradient method. When the function is smooth…

Optimization and Control · Mathematics 2018-11-29 Jingzhao Zhang , Aryan Mokhtari , Suvrit Sra , Ali Jadbabaie

In this paper we define an efficient implementation of Runge-Kutta methods of Radau IIA type, which are commonly used when solving stiff ODE-IVPs problems. The proposed implementation relies on an alternative low-rank formulation of the…

Numerical Analysis · Mathematics 2024-07-18 L. Brugnano , F. Iavernaro , C. Magherini

Explicit integrating factor Runge-Kutta methods are attractive and popular in developing high-order maximum bound principle preserving time-stepping schemes for Allen-Cahn type gradient flows. However, they always suffer from the…

Numerical Analysis · Mathematics 2024-10-10 Hong-lin Liao , Xuping Wang , Cao Wen

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

A wide range of physical phenomena exhibit auxiliary admissibility criteria, such as conservation of entropy or various energies, which arise implicitly under exact solution of their governing PDEs. However, standard temporal schemes, such…

Numerical Analysis · Mathematics 2025-03-27 Mohammad R. Najafian , Brian C. Vermeire

This paper introduces the Runge-Kutta Chebyshev descent method (RKCD) for strongly convex optimisation problems. This new algorithm is based on explicit stabilised integrators for stiff differential equations, a powerful class of numerical…

Optimization and Control · Mathematics 2020-06-30 Armin Eftekhari , Bart Vandereycken , Gilles Vilmart , Konstantinos C. Zygalakis

In this paper, we consider stochastic Runge-Kutta methods for stochastic Hamiltonian partial differential equations and present some sufficient conditions for multisymplecticity of stochastic Runge-Kutta methods of stochastic Hamiltonian…

Symplectic Geometry · Mathematics 2018-03-02 Liying Zhang , Lihai Ji

Differential equations arise in mathematics, physics,medicine, pharmacology, communications, image processing and animation, etc. An Ordinary Differential Equation (ODE) is a differential equation if it involves derivatives with respect to…

Mathematical Software · Computer Science 2015-12-31 A. O. Anidu , S. A. Arekete , A. O. Adedayo , A. O. Adekoya

We present the Minimally-Implicit Runge-Kutta (MIRK) methods for the numerical evolution of the resistive relativistic magnetohydrodynamic (RRMHD) equations, following the approach proposed by Komissarov (2007) of an augmented system of…

Computational Physics · Physics 2025-02-04 Isabel Cordero-Carrión , Samuel Santos-Pérez , Clara Martínez-Vidallach

While implicit Runge--Kutta methods possess high order accuracy and important stability properties, implementation difficulties and the high expense of solving the coupled algebraic system at each time step are frequently cited as…

Numerical Analysis · Mathematics 2020-07-01 Patrick E. Farrell , Robert C. Kirby , Jorge Marchena-Menendez

The simulation of chemical kinetics involving multiple scales constitutes a modeling challenge (from ordinary differential equations to Markov chain) and a computational challenge (multiple scales, large dynamical systems, time step…

Numerical Analysis · Mathematics 2021-06-18 Assyr Abdulle , Lia Gander , Giacomo Rosilho de Souza

A numerical search approach is used to design high-order diagonally implicit Runge-Kutta (DIRK) schemes equipped with embedded error estimators, some of which have identical diagonal elements (SDIRK) and explicit first stage (ESDIRK). In…

Numerical Analysis · Mathematics 2023-09-12 Yousef Alamri , David I. Ketcheson

The recently-introduced relaxation approach for Runge-Kutta methods can be used to enforce conservation of energy in the integration of Hamiltonian systems. We study the behavior of implicit and explicit relaxation Runge-Kutta methods in…

Numerical Analysis · Mathematics 2020-07-13 Hendrik Ranocha , David I. Ketcheson

In research problems that involve the use of numerical methods for solving systems of ordinary differential equations (ODEs), it is often required to select the most efficient method for a particular problem. To solve a Cauchy problem for a…

Numerical Analysis · Mathematics 2021-07-16 Migran N. Gevorkyan , Anna V. Korolkova , Dmitry S. Kulyabov

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