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This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. The proposed methods are based on a specific subset of explicit one-step…

Numerical Analysis · Mathematics 2019-04-16 Vu Thai Luan , Rujeko Chinomona , Daniel R. Reynolds

The problem of solving stochastic differential-algebraic equations (SDAEs) of index one with a scalar driving Brownian motion is considered. Recently, the authors proposed a class of stiffly accurate stochastic Runge-Kutta (SRK) methods…

Numerical Analysis · Mathematics 2013-11-07 Dominique Küpper , Anne Kværnø , Andreas Rößler

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

A new method for the numerical solution of ODEs is presented. This approach is based on an approximate formulation of the Taylor methods that has a much easier implementation than the original Taylor methods, since only the functions in the…

Numerical Analysis · Mathematics 2025-01-30 Antonio Baeza , Sebastiano Boscarino , Pep Mulet , Giovanni Russo , David Zorío

Runge-Kutta methods are a popular class of numerical methods for solving ordinary differential equations. Every Runge-Kutta method is characterized by two basic parameters: its order, which measures the accuracy of the solution it produces,…

Numerical Analysis · Mathematics 2019-11-04 David K. Zhang

An additive Runge-Kutta method is used for the time stepping, which integrates the linear stiff terms by an explicit singly diagonally implicit Runge-Kutta (ESDIRK) method and the nonlinear terms by an explicit Runge-Kutta (ERK) method. In…

Numerical Analysis · Mathematics 2024-05-08 Ke Chen , Daniel Appelö , Tracy Babb , Per-Gunnar Martinsson

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 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

In the present paper, a class of stochastic Runge-Kutta methods containing the second order stochastic Runge-Kutta scheme due to E. Platen for the weak approximation of It\^o stochastic differential equation systems with a multi-dimensional…

Numerical Analysis · Mathematics 2013-03-20 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

High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The…

Numerical Analysis · Mathematics 2014-03-27 Sigal Gottlieb , Zachary J. Grant , Daniel Higgs

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

Based on a variational principle with a stochastic forcing, we indicate that the stochastic Schr\"odinger equation in Stratonovich sense is an infinite-dimensional stochastic Hamiltonian system, whose phase flow preserves symplecticity. We…

Numerical Analysis · Mathematics 2016-05-05 Chuchu Chen , Jialin Hong

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

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 this paper a set of previous general results for the development of B--series for a broad class of stochastic differential equations has been collected. The applicability of these results is demonstrated by the derivation of B--series…

Numerical Analysis · Mathematics 2025-01-08 Alemayehu Adugna Arara , Kristian Debrabant , Anne Kværnø

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

Explicit Runge--Kutta (RK) methods are susceptible to a reduction in the observed order of convergence when applied to initial-boundary value problem with time-dependent boundary conditions. We study conditions on explicit RK methods that…

Numerical Analysis · Mathematics 2026-02-11 Abhijit Biswas , David I. Ketcheson , Steven Roberts , Benjamin Seibold , David Shirokoff

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 propose a new probabilistic scheme which combines deep learning techniques with high order schemes for backward stochastic differential equations belonging to the class of Runge-Kutta methods to solve high-dimensional semi-linear…

Numerical Analysis · Mathematics 2023-01-02 Jean-François Chassagneux , Junchao Chen , Noufel Frikha