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This paper investigates the performance of a subclass of exponential integrators, specifically explicit exponential Runge--Kutta methods. It is well known that third-order methods can suffer from order reduction when applied to linearized…

Numerical Analysis · Mathematics 2024-12-30 Thi Tam Dang , Trung Hau Hoang

This article extends the theory of dual-consistent summation-by-parts (SBP) and generalized SBP (GSBP) time-marching methods by showing that they are implicit Runge-Kutta schemes. Through this connection, the accuracy theory for the…

Numerical Analysis · Mathematics 2016-01-26 Pieter D. Boom , David W. Zingg

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

We consider quadrature formulas of high order in time based on Radau-type, L-stable implicit Runge-Kutta schemes to solve time dependent stiff PDEs. Instead of solving a large nonlinear system of equations, we develop a method that performs…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Matthew Emmett

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

In this paper, a class of stable explicit $\theta$-schemes are proposed for solving anticipated backward stochastic differential equations (anticipated BSDEs) which generator not only contains the present values of the solutions but also…

Numerical Analysis · Mathematics 2024-09-23 Mingshang Hu , Lianzi Jiang

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

When a high dimension system of ordinary differential equations is solved numerically, the computer memory capacity may be compromised. Thus, for such systems, it is important to incorporate low memory usage to some other properties of the…

Numerical Analysis · Mathematics 2018-09-14 I. Higueras , T. Roldan

Some properties of numerical time integration methods using summation by parts operators and simultaneous approximation terms are studied. These schemes can be interpreted as implicit Runge-Kutta methods with desirable stability properties…

Numerical Analysis · Mathematics 2024-12-20 Hendrik Ranocha

In the paper explicit functional continuous Runge-Kutta and Runge-Kutta-Nystr\"om methods for retarded functional differential equations are considered. New methods for first order equations as well as for second order equations of the…

Numerical Analysis · Mathematics 2018-06-25 Alexey S. Eremin

A new class of third order Runge-Kutta methods for stochastic differential equations with additive noise is introduced. In contrast to Platen's method, which to the knowledge of the author has been up to now the only known third order…

Numerical Analysis · Mathematics 2010-09-29 Kristian Debrabant

This paper focuses on the strong convergence rate of both Runge--Kutta methods and simplified step-$N$ Euler schemes for stochastic differential equations driven by multi-dimensional fractional Brownian motions with $H\in(\frac12,1)$. Based…

Numerical Analysis · Mathematics 2021-04-23 Jialin Hong , Chuying Huang , Xu Wang

High-order spatial discretizations with strong stability properties (such as monotonicity) are desirable for the solution of hyperbolic PDEs. Methods may be compared in terms of the strong stability preserving (SSP) time-step. We prove an…

Numerical Analysis · Mathematics 2014-01-30 Christopher Bresten , Sigal Gottlieb , Zachary Grant , Daniel Higgs , David I. Ketcheson , Adrian Németh

In current research, we analyse dissipation and dispersion characteristics of most accurate two and three stage Gauss-Legendre implicit Runge-Kutta (R-K) methods. These methods, known for their $A$-stability and immense accuracy, are…

Numerical Analysis · Mathematics 2019-06-25 Subhajit Giri , Shuvam Sen

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

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

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

We revisit the numerical stability of four well-established explicit stochastic integration schemes through a new generic benchmark stochastic differential equation designed to assess asymptotic statistical accuracy and stability…

Numerical Analysis · Mathematics 2026-05-20 Thomas Hudson , Sarah Helfert , Xingjie Helen Li

In this paper, we obtain stability results for backward stochastic differential equations with jumps (BSDEs) in a very general framework. More specifically, we consider a convergent sequence of standard data, each associated to their own…

Probability · Mathematics 2023-04-06 Antonis Papapantoleon , Dylan Possamaï , Alexandros Saplaouras

Mixed-precision algorithms combine low- and high-precision computations in order to benefit from the performance gains of reduced-precision without sacrificing accuracy. In this work, we design mixed-precision Runge-Kutta-Chebyshev (RKC)…

Numerical Analysis · Mathematics 2023-01-10 Matteo Croci , Giacomo Rosilho de Souza