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In this master thesis we have compared different second order stabilized explicit Runge-Kutta methods when applied to the incompressible Navier-Stokes equations by means of a projection method and a differential algebraic approach. We…

Numerical Analysis · Mathematics 2022-03-30 Giacomo Rosilho de Souza

In the last few decades, numerical simulation for nonlinear oscillators has received a great deal of attention, and many researchers have been concerned with the design and analysis of numerical methods for solving oscillatory problems. In…

Numerical Analysis · Mathematics 2020-12-25 Yu-Wen Li , Xinyuan Wu

We introduce a class of explicit exponential Rosenbrock methods for the time integration of large systems of stiff differential equations. Their application with respect to simulation tasks in the field of visual computing is discussed…

Numerical Analysis · Mathematics 2018-05-23 Vu Thai Luan , Dominik L. Michels

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 paper a technique is given to recover the classical order of the method when explicit exponential Runge-Kutta methods integrate reaction-diffusion problems. Although methods of high stiff order for problems with vanishing boundary…

Numerical Analysis · Mathematics 2022-11-22 Begoña Cano , Marí a Jesús Moreta

Recently, a new class of second order Runge-Kutta methods for It\^o stochastic differential equations with a multidimensional Wiener process was introduced by R\"o{\ss}ler. In contrast to second order methods earlier proposed by other…

Numerical Analysis · Mathematics 2013-03-22 Kristian Debrabant , Andreas Rößler

Explicit stabilized methods are highly efficient time integrators for large and stiff systems of ordinary differential equations especially when applied to semi-discrete parabolic problems. However, when local spatial mesh refinement is…

Numerical Analysis · Mathematics 2025-10-20 Mathieu Benninghoff , Gilles Vilmart

A practical and new Runge--Kutta numerical scheme for stochastic differential equations is explored. Numerical examples demonstrate the strong convergence of the method. The first order strong convergence is then proved using Ito integrals…

Numerical Analysis · Mathematics 2012-10-04 A. J. Roberts

Modern deep learning algorithms use variations of gradient descent as their main learning methods. Gradient descent can be understood as the simplest Ordinary Differential Equation (ODE) solver; namely, the Euler method applied to the…

Machine Learning · Computer Science 2025-05-20 Benoit Dherin , Michael Munn , Hanna Mazzawi , Michael Wunder , Sourabh Medapati , Javier Gonzalvo

We present MDIRK: a Multifluid second-order Diagonally-Implicit Runge-Kutta method to study momentum transfer between gas and an arbitrary number ($N$) of dust species. The method integrates the equations of hydrodynamics with an Implicit…

Computational Physics · Physics 2024-02-27 Leonardo Krapp , Juan Garrido-Deutelmoser , Pablo Benítez-Llambay , Kaitlin M. Kratter

In this paper, we study symmetric integrators for solving second-order ordinary differential equations on the basis of the notion of continuous-stage Runge-Kutta-Nystrom methods. The construction of such methods heavily relies on the…

Numerical Analysis · Mathematics 2024-12-20 Wensheng Tang , Jingjing Zhang

An additive Runge-Kutta method is used for the time stepping, which integrates the linear stiff terms by an explicit singly diagonally implicit Runge-Kutta (ESDIRK) method and the nonlinear terms by an explicit Runge-Kutta (ERK) method. In…

Numerical Analysis · Mathematics 2024-05-08 Ke Chen , Daniel Appelö , Tracy Babb , Per-Gunnar Martinsson

Matrix differential Riccati equation (DRE) typically exhibits transient and steady-state phases, posing challenges for fixed-step time integration methods, which may lack accuracy during transients or oversample in steady regimes. In this…

Numerical Analysis · Mathematics 2026-03-30 Jinyi Li , Dongping Li , Hua Yang

We analyze the stability and accuracy (up to third order) of a new family of implicit-explicit Runge-Kutta (IMEX RK) methods. This analysis expedites development of methods with various balances in the number of explicit stages and implicit…

Numerical Analysis · Mathematics 2019-06-19 Andrew Steyer , Christopher J. Vogl , Mark Taylor , Oksana Guba

This paper introduces a novel paradigm for constructing linearly implicit and high-order unconditionally energy-stable schemes for general gradient flows, utilizing the scalar auxiliary variable (SAV) approach and the additive Runge-Kutta…

Numerical Analysis · Mathematics 2023-07-11 Xuelong Gu , Wenjun Cai , Yushun Wang

This work constructs and analyzes new efficient high-order two-derivative diagonally implicit Runge--Kutta (TDDIRK) schemes with optimized phase errors. Specifically, we present a convergence result for TDDIRK methods and investigate their…

Numerical Analysis · Mathematics 2025-12-18 Julius Ehigie , Vu Thai Luan

The design of numerical integrators for solving stochastic dynamics with high weak order relies on tedious calculations and is subject to a high number of order conditions. The original approaches from the literature consider strong…

Numerical Analysis · Mathematics 2026-03-26 Adrien Busnot Laurent , Kristian Debrabant , Anne Kværnø

Stiff systems of ordinary differential equations (ODEs) arise in a wide range of scientific and engineering disciplines and are traditionally solved using implicit integration methods due to their stability and efficiency. However, these…

Numerical Analysis · Mathematics 2024-12-02 Colby Fronk , Linda Petzold

We construct eight implicit-explicit (IMEX) Runge-Kutta (RK) schemes up to third order of the type in which all stages are implicit so that they can be used in the zero relaxation limit in a unified and convenient manner. These…

Numerical Analysis · Mathematics 2016-06-08 Shu-Chao Duan

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
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