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Many important applications are modelled by differential equations with positive solutions. However, it remains an outstanding open problem to develop numerical methods that are both (i) of a high order of accuracy and (ii) capable of…

Numerical Analysis · Mathematics 2022-05-03 Sergio Blanes , Arieh Iserles , Shev Macnamara

A wide range of physical phenomena exhibit auxiliary admissibility criteria, such as conservation of entropy or various energies, which arise implicitly under exact solution of their governing PDEs. However, standard temporal schemes, such…

Numerical Analysis · Mathematics 2025-03-27 Mohammad R. Najafian , Brian C. Vermeire

Different families of Runge-Kutta-Nystr\"om (RKN) symplectic splitting methods of order 8 are presented for second-order systems of ordinary differential equations and are tested on numerical examples. They show a better efficiency than…

Numerical Analysis · Mathematics 2022-07-26 F. Casas , S. Blanes , A. Escorihuela-Tomàs

In this work we present a class of high order unconditionally strong stability preserving (SSP) implicit multi-derivative Runge--Kutta schemes, and SSP implicit-explicit (IMEX) multi-derivative Runge--Kutta schemes where the time-step…

Numerical Analysis · Mathematics 2021-08-10 Sigal Gottlieb , Zachary J. Grant , Jingwei Hu , Ruiwen Shu

In this work, we present approaches to rigorously certify $A$- and $A(\alpha)$-stability in Runge-Kutta methods through the solution of convex feasibility problems defined by linear matrix inequalities. We adopt two approaches. The first is…

Numerical Analysis · Mathematics 2024-05-24 Austin Juhl , David Shirokoff

Runge-Kutta time-stepping methods in general suffer from order reduction: the observed order of convergence may be less than the formal order when applied to certain stiff problems. Order reduction can be avoided by using methods with high…

Numerical Analysis · Mathematics 2023-08-17 David Ketcheson , Benjamin Seibold , David Shirokoff , Dong Zhou

Implicit-explicit (IMEX) Runge-Kutta methods play a major rule in the numerical treatment of differential systems governed by stiff and non-stiff terms. This paper discusses order conditions and symplecticity properties of a class of IMEX…

Numerical Analysis · Mathematics 2012-02-07 Michael Herty , Lorenzo Pareschi , Sonja Steffensen

Strong stability preserving (SSP) Runge-Kutta methods are often desired when evolving in time problems that have two components that have very different time scales. Where the SSP property is needed, it has been shown that implicit and…

Numerical Analysis · Mathematics 2018-08-15 Sigal Gottlieb , Zachary J. Grant , Leah Isherwood

In this paper, a class of arbitrarily high-order linear momentum-preserving and energy-preserving schemes are proposed, respectively, for solving the regularized long-wave equation. For the momentum-preserving scheme, the key idea is based…

Numerical Analysis · Mathematics 2021-12-07 Chaolong Jiang , Xu Qian , Songhe Song , Jin Cui

In a previous paper, a technique was suggested to avoid order reduction with any explicit exponential Runge-Kutta method when integrating initial boundary value nonlinear problems with time-dependent boundary conditions. In this paper, we…

Numerical Analysis · Mathematics 2023-07-18 Begoña Cano , María Jesús Moreta

Nonlinear parabolic equations are central to numerous applications in science and engineering, posing significant challenges for analytical solutions and necessitating efficient numerical methods. Exponential integrators have recently…

Numerical Analysis · Mathematics 2024-12-24 Trung Hau Hoang

A novel optimization procedure for the generation of stability polynomials of stabilized explicit Runge-Kutta methods is devised. Intended for semidiscretizations of hyperbolic partial differential equations, the herein developed approach…

Numerical Analysis · Mathematics 2024-03-19 Daniel Doehring , Gregor J. Gassner , Manuel Torrilhon

We introduce a new class of parametricization structure-preserving partitioned Runge-Kutta ($\alpha$-PRK) methods for Hamiltonian systems with holonomic constraints. When the scalar parameter $\alpha=0$, the methods are reduced to the usual…

Numerical Analysis · Mathematics 2020-07-14 Lei Li , Dongling Wang

We have shown previously that functionally fitted Runge-Kutta (FRK) methods can be studied using a convenient collocation framework. Here, we extend that framework to functionally fitted Runge-Kutta-Nystr\"om (FRKN) methods, shedding…

Numerical Analysis · Mathematics 2014-10-17 N. S. Hoang , R. B. Sidje

In this work we present a new class of Runge-Kutta (RK) methods for solving systems of hyperbolic equations with a particular structure, generalization of a wave-equation. The new methods are {\it partially implicit} in the sense that a…

Mathematical Physics · Physics 2016-11-10 Isabel Cordero-Carrión , Pablo Cerdá-Durán

We present novel entropy-conservative and entropy-stable multirate Runge-Kutta methods based on Paired Explicit Runge-Kutta (P-ERK) schemes with relaxation for conservation laws and related systems of partial differential equations.…

Numerical Analysis · Mathematics 2025-07-09 Daniel Doehring , Hendrik Ranocha , Manuel Torrilhon

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

Modified Patankar-Runge-Kutta (MPRK) methods preserve the positivity as well as conservativity of a production-destruction system (PDS) of ordinary differential equations for all time step sizes. As a result, higher order MPRK schemes do…

Numerical Analysis · Mathematics 2022-10-31 Thomas Izgin , Stefan Kopecz , Andreas Meister

Fully implicit Runge-Kutta (IRK) methods have many desirable properties as time integration schemes in terms of accuracy and stability, but high-order IRK methods are not commonly used in practice with numerical PDEs due to the difficulty…

Numerical Analysis · Mathematics 2021-10-07 Ben S. Southworth , Oliver Krzysik , Will Pazner , Hans De Sterck

For the approximation of solutions for stochastic partial differential equations, numerical methods that obtain a high order of convergence and at the same time involve reasonable computational cost are of particular interest. We therefore…

Numerical Analysis · Mathematics 2024-12-12 Claudine von Hallern , Ricarda Mißfeldt , Andreas Rößler
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