English
Related papers

Related papers: Many-Stage Optimal Stabilized Runge-Kutta Methods …

200 papers

In practical computation with Runge--Kutta methods, the stage equations are not satisfied exactly, due to roundoff errors, algebraic solver errors, and so forth. We show by example that propagation of such errors within a single step can…

Numerical Analysis · Mathematics 2014-11-25 David I. Ketcheson , Lajos Lóczi , Matteo Parsani

We deal with optimal approximation of solutions of ODEs under local Lipschitz condition and inexact discrete information about the right-hand side functions. We show that the randomized two-stage Runge-Kutta scheme is the optimal method…

Numerical Analysis · Mathematics 2021-03-23 Tomasz Bochacik , Maciej Goćwin , Paweł M. Morkisz , Paweł Przybyłowicz

A new approach for the construction of high order A-stable explicit integrators for ordinary differential equations (ODEs) is theoretically studied. Basically, the integrators are obtained by splitting, at each time step, the solution of…

Numerical Analysis · Mathematics 2012-08-24 H. de la Cruz , R. J. Biscay , J. C. Jimenez , F. Carbonell

We develop Chebyshev symplectic methods based on Chebyshev orthogonal polynomials of the first and second kind separately in this paper. Such type of symplectic methods can be conveniently constructed with the newly-built theory of weighted…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

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

We introduce a family of stochastic optimization methods based on the Runge-Kutta-Chebyshev (RKC) schemes. The RKC methods are explicit methods originally designed for solving stiff ordinary differential equations by ensuring that their…

Optimization and Control · Mathematics 2022-02-01 Tony Stillfjord , Måns Williamson

In this work we consider a mixed precision approach to accelerate the implemetation of multi-stage methods. We show that Runge-Kutta methods can be designed so that certain costly intermediate computations can be performed as a…

Numerical Analysis · Mathematics 2020-12-25 Zachary J. Grant

Strong stability preserving (SSP) integrators for initial value ODEs preserve temporal monotonicity solution properties in arbitrary norms. All existing SSP methods, including implicit methods, either require small step sizes or achieve…

Numerical Analysis · Mathematics 2012-03-27 David I. Ketcheson

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

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

We show that existing Runge-Kutta methods for ordinary differential equations (odes) can be modified to solve stochastic differential equations (sdes) with strong solutions provided that appropriate changes are made to the way stepsizes are…

Quantum Physics · Physics 2007-09-30 Joshua Wilkie , Murat Cetinbas

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

An explicit stabilized additive Runge-Kutta scheme is proposed. The method is based on a splitting of the problem in severely stiff and mildly stiff subproblems, which are then independently solved using a Runge-Kutta-Chebyshev scheme. The…

Numerical Analysis · Mathematics 2020-03-09 Assyr Abdulle , Giacomo Rosilho de Souza

It is well-known that a numerical method which is at the same time geometric structure-preserving and physical property-preserving cannot exist in general for Hamiltonian partial differential equations. In this paper, we present a novel…

Numerical Analysis · Mathematics 2019-07-25 Chuchu Chen , Jialin Hong , Chol Sim , Kwang Sonwu

The analytic form of a new class of factorized Runge-Kutta-Chebyshev (FRKC) stability polynomials of arbitrary order $N$ is presented. Roots of FRKC stability polynomials of degree $L=MN$ are used to construct explicit schemes comprising…

Computational Physics · Physics 2015-08-11 Stephen O'Sullivan

We investigate a high-order, fully explicit, asymptotic-preserving scheme for a kinetic equation with linear relaxation, both in the hydrodynamic and diffusive scalings in which a hyperbolic, resp. parabolic, limiting equation exists. The…

Numerical Analysis · Mathematics 2014-05-21 Pauline Lafitte , Annelies Lejon , Giovanni Samaey

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

We randomize the implicit two-stage Runge-Kutta scheme in order to improve the rate of convergence (with respect to a deterministic scheme) and stability of the approximate solution (with respect to the solution generated by the explicit…

Numerical Analysis · Mathematics 2025-01-17 Tomasz Bochacik , Paweł Przybyłowicz

In this paper, we extend the Paired-Explicit Runge-Kutta schemes by Vermeire et. al. to fourth-order of consistency. Based on the order conditions for partitioned Runge-Kutta methods we motivate a specific form of the Butcher arrays which…

Many time-dependent differential equations are equipped with invariants. Preserving such invariants under discretization can be important, e.g., to improve the qualitative and quantitative properties of numerical solutions. Recently,…

Numerical Analysis · Mathematics 2023-11-27 Sebastian Bleecke , Hendrik Ranocha