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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

This paper considers the numerical integration of semilinear evolution PDEs using the high order linearly implicit methods developped in a previous paper in the ODE setting. These methods use a collocation Runge--Kutta method as a basis,…

Numerical Analysis · Mathematics 2023-10-24 Guillaume Dujardin , Ingrid Lacroix-Violet

The use of high order fully implicit Runge-Kutta methods is of significant importance in the context of the numerical solution of transient partial differential equations, in particular when solving large scale problems due to fine space…

Numerical Analysis · Mathematics 2023-02-27 Ivo Dravins , Stefano Serra-Capizzano , Maya Neytcheva

The main objective of this series of papers is to explore the entire landscape of numerical methods for fast nonlinear Fourier transformation (NFT) within the class of integrators known as the exponential integrators. In this paper, we…

Numerical Analysis · Mathematics 2018-12-13 Vishal Vaibhav

Finite element discretization of time dependent problems also require effective time-stepping schemes. While implicit Runge-Kutta methods provide favorable accuracy and stability problems, they give rise to large and complicated systems of…

Numerical Analysis · Mathematics 2023-05-01 Robert C. Kirby

Extended Stability Runge-Kutta (ESRK) methods are crucial for solving large-scale computational problems in science and engineering, including weather forecasting, aerodynamic analysis, and complex biological modelling. However, balancing…

Machine Learning · Computer Science 2025-06-27 Gavin Lee Goodship , Luis Miralles-Pechuan , Stephen O'Sullivan

The Butcher theory provides a powerful tool for analyzing order conditions of Runge-Kutta schemes for ordinary differential equations (ODEs); however, such a theory has not yet been well established for backward stochastic differential…

Numerical Analysis · Mathematics 2026-05-26 Shuixin Fang , Yue Qiu , Weidong Zhao

This article extends the theory of dual-consistent summation-by-parts (SBP) and generalized SBP (GSBP) time-marching methods by showing that they are implicit Runge-Kutta schemes. Through this connection, the accuracy theory for the…

Numerical Analysis · Mathematics 2016-01-26 Pieter D. Boom , David W. Zingg

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

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

In this paper we consider an approach to improve the performance of exponential Runge--Kutta integrators and Lawson schemes} in cases where the solution of a related, but usually much simpler, problem can be computed efficiently. While for…

Numerical Analysis · Mathematics 2023-10-20 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

Rational methods are intended to time integrate linear homogeneous problems. However, their scope can be extended so as to cover linear nonhomogeneous problems. In this paper the integration of semilinear problems is considered. The…

Numerical Analysis · Mathematics 2025-09-23 Carlos Arranz-Simón , Begoña Cano , César Palencia

In this paper we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for…

Numerical Analysis · Mathematics 2014-01-31 Tomasz M. Tyranowski , Mathieu Desbrun

Many HPC applications that solve differential equations rely on the Runge-Kutta family of methods for time integration. Among these methods, the fourth-order accurate RK4 scheme is especially popular. This time integration scheme requires…

General Relativity and Quantum Cosmology · Physics 2026-03-09 Lucas Timotheo Sanches , Steven Robert Brandt , Jay Kalinani , Liwei Ji , Erik Schnetter

Using a recent characterization of energy-preserving B-series, we derive the explicit conditions on the coefficients of a Runge-Kutta method that ensure energy preservation (for Hamiltonian systems) up to a given order in the step size,…

Numerical Analysis · Mathematics 2025-01-24 Gabriel A. Barrios de León , David I. Ketcheson , Hendrik Ranocha

When a high dimension system of ordinary differential equations is solved numerically, the computer memory capacity may be compromised. Thus, for such systems, it is important to incorporate low memory usage to some other properties of the…

Numerical Analysis · Mathematics 2018-09-14 I. Higueras , T. Roldan

This work presents a new evolutionary optimization algorithm in theoretical mathematics with important applications in scientific computing. The use of the evolutionary algorithm is justified by the difficulty of the study of the…

Algebraic Geometry · Mathematics 2017-10-31 Ivan Martino , Giuseppe Nicosia

In order to solve continuous-time optimal control problems, direct methods transcribe the infinite-dimensional problem to a nonlinear program (NLP) using numerical integration methods. In cases where the integration error can be manipulated…

Optimization and Control · Mathematics 2025-03-18 Jakob Harzer , Jochem De Schutter , Moritz Diehl

Implicit Runge--Kutta (IRK) methods are highly effective for solving stiff ordinary differential equations (ODEs) but can be computationally expensive for large-scale problems due to the need of solving coupled algebraic equations at each…

Numerical Analysis · Mathematics 2025-09-18 Fabio Durastante , Mariarosa Mazza

Classical and new numerical schemes are generated using evolutionary computing. Differential Evolution is used to find the coefficients of finite difference approximations of function derivatives, and of single and multi-step integration…

Neural and Evolutionary Computing · Computer Science 2014-01-02 C. D. Erdbrink , V. V. Krzhizhanovskaya , P. M. A. Sloot
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