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The aim of this paper is to construct and analyze explicit exponential Runge-Kutta methods for the temporal discretization of linear and semilinear integro-differential equations. By expanding the errors of the numerical method in terms of…

Numerical Analysis · Mathematics 2023-01-24 Alexander Ostermann , Fardin Saedpanah , Nasrin Vaisi

Non-conforming numerical approximations offer increased flexibility for applications that require high resolution in a localized area of the computational domain or near complex geometries. Two key properties for non-conforming methods to…

In this survey, we provide an in-depth investigation of exponential Runge-Kutta methods for the numerical integration of initial-value problems. These methods offer a valuable synthesis between classical Runge-Kutta methods, introduced more…

Numerical Analysis · Mathematics 2026-04-27 Alessia andò , Nicolò Cangiotti , Mattia Sensi

Summation-by-parts (SBP) operators are finite-difference operators that mimic integration by parts. This property can be useful in constructing energy-stable discretizations of partial differential vequations. SBP operators are defined by a…

Numerical Analysis · Mathematics 2015-05-14 Jason E. Hicken , David W. Zingg

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

We study diagonally implicit Runge-Kutta (DIRK) schemes when applied to abstract evolution problems that fit into the Gelfand-triple framework. We introduce novel stability notions that are well-suited to this setting and provide simple,…

Numerical Analysis · Mathematics 2022-05-27 Abner J. Salgado , Ignacio Tomas

This paper is concerned with the accurate, conservative, and stable imposition of boundary conditions and inter-element coupling for multi-dimensional summation-by-parts (SBP) finite-difference operators. More precisely, the focus is on…

Numerical Analysis · Mathematics 2016-08-09 David C. Del Rey Fernández , Jason E. Hicken , David W. Zingg

Geometric integration of non-autonomous classical engineering problems, such as rotor dynamics, is investigated. It is shown, both numerically and by backward error analysis, that geometric (structure preserving) integration algorithms are…

Numerical Analysis · Mathematics 2011-03-11 Klas Modin

A posteriori error estimates based on residuals can be used for reliable error control of numerical methods. Here, we consider them in the context of ordinary differential equations and Runge-Kutta methods. In particular, we take the…

Numerical Analysis · Mathematics 2024-09-25 Hendrik Ranocha , Jan Giesselmann

Linearly implicit Runge-Kutta methods with approximate matrix factorization can solve efficiently large systems of differential equations that have a stiff linear part, e.g. reaction-diffusion systems. However, the use of approximate…

Numerical Analysis · Computer Science 2014-08-19 Hong Zhang , Adrian Sandu , Paul Tranquilli

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

The generalized additive Runge-Kutta (GARK) framework provides a powerful approach for solving additively partitioned ordinary differential equations. This work combines the ideas of symplectic GARK schemes and multirate GARK schemes to…

Numerical Analysis · Mathematics 2023-12-15 Kevin Schäfers , Michael Günther , Adrian Sandu

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

In many applications, the governing PDE to be solved numerically contains a stiff component. When this component is linear, an implicit time stepping method that is unencumbered by stability restrictions is often preferred. On the other…

Numerical Analysis · Mathematics 2021-04-27 Kevin Chow , Steven J. Ruuth

Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were proposed and analyzed in 4. These specially designed methods use reduced precision for the implicit computations and full…

Numerical Analysis · Mathematics 2022-12-23 Ben Burnett , Sigal Gottlieb , Zachary J. Grant

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

Radial basis function methods are powerful tools in numerical analysis and have demonstrated good properties in many different simulations. However, for time-dependent partial differential equations, only a few stability results are known.…

Numerical Analysis · Mathematics 2022-04-08 Jan Glaubitz , Jan Nordström , Philipp Öffner

Mixed precision Runge--Kutta methods have been recently developed and used for the time-evolution of partial differential equations. Two-derivative Runge--Kutta schemes may offer enhanced stability and accuracy properties compared to…

Numerical Analysis · Mathematics 2026-02-17 Sigal Gottlieb , Zachary J. Grant , Cesar Herrera

We explore a novel way to numerically resolve the scaling behavior of finite-time singularities in solutions of nonlinear parabolic PDEs. The Runge--Kutta--Legendre (RKL) and Runge--Kutta--Gegenbauer (RKG) super-time-stepping methods were…

Numerical Analysis · Mathematics 2025-09-24 Zheng Tan , Tariq D. Aslam , Andrea L. Bertozzi

The article considers symmetric general linear methods, a class of numerical time integration methods which, like symmetric Runge--Kutta methods, are applicable to general time--reversible differential equations, not just those derived from…

Numerical Analysis · Mathematics 2015-07-07 John Butcher , Adrian Hill , Terrence Norton