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The Runge--Kutta (RK) discontinuous Galerkin (DG) method is a mainstream numerical algorithm for solving hyperbolic equations. In this paper, we use the linear advection equation in one and two dimensions as a model problem to prove the…

Numerical Analysis · Mathematics 2024-10-02 Zheng Sun

We propose an efficient algorithm for the approximation of fractional integrals by using Runge--Kutta based convolution quadrature. The algorithm is based on a novel integral representation of the convolution weights and a special…

Numerical Analysis · Mathematics 2019-07-29 Lehel Banjai , María López-Fernández

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

Multiphysics systems are driven by multiple processes acting simultaneously, and their simulation leads to partitioned systems of differential equations. This paper studies the solution of partitioned systems of differential equations using…

Numerical Analysis · Mathematics 2019-12-04 Mahesh Narayanamurthi , Adrian Sandu

In this work, we aim at constructing numerical schemes, that are as efficient as possible in terms of cost and conservation of invariants, for the Vlasov--Fokker--Planck system coupled with Poisson or Amp\`ere equation. Splitting methods…

Numerical Analysis · Mathematics 2023-06-13 Ibrahim Almuslimani , Nicolas Crouseilles

The class of stochastic Runge-Kutta methods for stochastic differential equations due to R\"o{\ss}ler is considered. Coefficient families of diagonally drift-implicit stochastic Runge-Kutta (DDISRK) methods of weak order one and two are…

Numerical Analysis · Mathematics 2016-05-10 Kristian Debrabant , Andreas Rößler

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

Neural networks have proven to be efficient surrogate models for tackling partial differential equations (PDEs). However, their applicability is often confined to specific PDEs under certain constraints, in contrast to classical PDE solvers…

Machine Learning · Computer Science 2023-10-03 Hoyun Choi , Sungyeop Lee , B. Kahng , Junghyo Jo

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

Multirate integration is an increasingly relevant tool that enables scientists to simulate multiphysics systems. Existing multirate methods are designed for equations whose fast and slow variables can be linearly separated using additive or…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Brian K. Tran , Ben S. Southworth

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

Applied to the master equation, the usual numerical integration methods, such as Runge-Kutta, become inefficient when the rates associated with various transitions differ by several orders of magnitude. We introduce an integration scheme…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman

This work constructs a new class of multirate schemes based on the recently developed generalized additive Runge-Kutta (GARK) methods (Sandu and Guenther, 2013). Multirate schemes use different step sizes for different components and for…

Numerical Analysis · Computer Science 2013-10-24 Michael Guenther , Adrian Sandu

Based on reasonable testing model problems, we study the preservation by symplectic Runge-Kutta method (SRK) and symplectic partitioned Runge-Kutta method (SPRK) of structures for fixed points of linear Hamiltonian systems. The…

Numerical Analysis · Mathematics 2008-02-18 Xiaohua Ding , Hongyu Liu , Zaijiu Shang , Geng Sun , Lingshu Wang

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

We study Runge-Kutta methods for rough differential equations which can be used to calculate solutions to stochastic differential equations driven by processes that are rougher than a Brownian motion. We use a Taylor series representation…

Numerical Analysis · Mathematics 2020-03-31 Martin Redmann , Sebastian Riedel

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

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

Variational space-time formulations for Partial Differential Equations have been of great interest in the last decades. While it is known that implicit time marching schemes have variational structure, the Galerkin formulation of explicit…

Numerical Analysis · Mathematics 2018-06-21 Judit Muñoz-Matute , David Pardo , Victor M. Calo , Elisabete Alberdi

Constructing explicit Runge--Kutta (ERK) methods with as few stages as possible for a given order is a classical problem in numerical analysis. In this work, we introduce a $Q$/$D$-space framework of sufficient order conditions for ERK…

Numerical Analysis · Mathematics 2026-05-19 Junyuan He , Jizu Huang