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Isospectral Runge-Kutta methods are well-suited for the numerical solution of isospectral systems such as the rigid body and the Toda lattice. More recently, these integrators have been applied to geophysical fluid models, where their…

Numerical Analysis · Mathematics 2025-06-10 Clauson Carvalho da Silva , Christian Lessig , Carlos Tomei

This paper investigates the energy conservation properties of explicit Runge--Kutta (RK) time discretizations for autonomous skew-symmetric systems. For linear problems, we present a general framework for constructing RK methods in which…

Numerical Analysis · Mathematics 2026-05-12 Jinjie Liu , Moysey Brio

Low-storage explicit Runge-Kutta schemes are particularly popular for the numerical integration of time-dependent partial differential equations based on the method-of-lines due to their efficiency and their reduced memory requirements. We…

Numerical Analysis · Mathematics 2026-04-07 Sergio Blanes , Alejandro Escorihuela-Tomàs

Earth system models are complex integrated models of atmosphere, ocean, sea ice, and land surface. Coupling the components can be a significant challenge due to the difference in physics, temporal, and spatial scales. This study explores…

Numerical Analysis · Mathematics 2023-04-12 Shinhoo Kang , Alp Dener , Aidan Hamilton , Hong Zhang , Emil M. Constantinescu , Robert L. Jacob

In this work, we introduce high-order Basis-Update & Galerkin (BUG) integrators based on explicit Runge-Kutta methods for large-scale matrix differential equations. These dynamical low-rank integrators extend the BUG integrator to arbitrary…

Numerical Analysis · Mathematics 2026-01-27 Fabio Nobile , Sébastien Riffaud

In this paper, we develop new techniques for solving the large, coupled linear systems that arise from fully implicit Runge-Kutta methods. This method makes use of the iterative preconditioned GMRES algorithm for solving the linear systems,…

Numerical Analysis · Mathematics 2017-03-08 Will Pazner , Per-Olof Persson

A methodology that can generate the optimal coefficients of a numerical method with the use of an artificial neural network is presented in this work. The network can be designed to produce a finite difference algorithm that solves a…

Neural and Evolutionary Computing · Computer Science 2013-09-20 Angelos A. Anastassi

An error analysis is presented for explicit partitioned Runge-Kutta methods and multirate methods applied to conservation laws. The interfaces, across which different methods or time steps are used, lead to order reduction of the schemes.…

Numerical Analysis · Mathematics 2013-10-29 Willem Hundsdorfer , David I. Ketcheson , Igor Savostianov

Explicit Runge-Kutta schemes with large stable step sizes are developed for integration of high order spectral difference spatial discretization on quadrilateral grids. The new schemes permit an effective time step that is substantially…

Numerical Analysis · Mathematics 2013-07-16 M. Parsani , D. I. Ketcheson , W. Deconinck

We present a computational framework for obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations, using high-order implicit Runge-Kutta Physics- Informed Neural Networks (IRK-PINNs) schemes.…

Machine Learning · Computer Science 2024-09-26 Álvaro Fernández Corral , Nicolás Mendoza , Armin Iske , Andrey Yachmenev , Jochen Küpper

Maximum bound principle (MBP) is an important property for a large class of semilinear parabolic equations, in the sense that the time-dependent solution of the equation with appropriate initial and boundary conditions and nonlinear…

Numerical Analysis · Mathematics 2021-04-21 Jingwei Li , Xiao Li , Lili Ju , Xinlong Feng

Explicit Runge--Kutta (RK) methods are susceptible to a reduction in the observed order of convergence when applied to initial-boundary value problem with time-dependent boundary conditions. We study conditions on explicit RK methods that…

Numerical Analysis · Mathematics 2026-02-11 Abhijit Biswas , David I. Ketcheson , Steven Roberts , Benjamin Seibold , David Shirokoff

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

This work generalizes the additively partitioned Runge-Kutta methods by allowing for different stage values as arguments of different components of the right hand side. An order conditions theory is developed for the new family of…

Numerical Analysis · Computer Science 2013-10-22 Adrian Sandu , Michael Guenther

A novel class of explicit high-order energy-preserving methods are proposed for general Hamiltonian partial differential equations with non-canonical structure matrix. When the energy is not quadratic, it is firstly done that the original…

Numerical Analysis · Mathematics 2020-06-02 Chaolong Jiang , Yushun Wang , Yuezheng Gong

We consider high order, implicit Runge-Kutta schemes to solve time-dependent stiff PDEs on dynamically adapted grids generated by multiresolution analysis for unsteady problems disclosing localized fronts. The multiresolution finite volume…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Richard Dobbins , Mitchell Smooke

This paper develops a general methodology for a posteriori error estimation in time-dependent multiphysics numerical simulations. The methodology builds upon the generalized-structure additive Runge--Kutta (GARK) approach to time…

Numerical Analysis · Mathematics 2020-01-27 Mahesh Narayanamurthi , Ulrich Römer , Adrian Sandu

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a…

Numerical Analysis · Mathematics 2024-12-13 Hana Mizerová , Katarína Tvrdá

Dynamic systems have a fundamental relevance in the description of physical phenomena. The search for more accurate and faster numerical integration methods for the resolution of such systems is, therefore, an important topic of research.…

Computational Physics · Physics 2025-10-10 J. Avellar , L. G. S. Duarte , L. A. C. P. da Mota , L. O. Pereira

Current Python programming environment does not have any reliable and efficient multiple precision floating-point (MPF) arithmetic except ``mpmath" and ``gmpy2" packages based on GNU MP(GMP) and MPFR libraries. Although it is well known…

Mathematical Software · Computer Science 2021-07-28 Tomonori Kouya