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Related papers: Runge-Kutta schemes for backward stochastic differ…

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The Butcher theory provides a powerful tool for analyzing order conditions of Runge-Kutta schemes for ordinary differential equations (ODEs); however, such a theory has not yet been well established for backward stochastic differential…

Numerical Analysis · Mathematics 2026-05-26 Shuixin Fang , Yue Qiu , Weidong Zhao

In this paper we propose a new kind of high order numerical scheme for backward stochastic differential equations(BSDEs). Unlike the traditional $\theta$-scheme, we reduce truncation errors by taking $\theta$ carefully for every subinterval…

Numerical Analysis · Mathematics 2018-08-08 Chol-Kyu Pak , Mun-Chol Kim , Chang-Ho Rim

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

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

We study Runge-Kutta methods for rough differential equations which can be used to calculate solutions to stochastic differential equations driven by processes that are rougher than a Brownian motion. We use a Taylor series representation…

Numerical Analysis · Mathematics 2020-03-31 Martin Redmann , Sebastian Riedel

Explicit Runge-Kutta (RK) integration of hyperbolic initial-boundary value problems with time-dependent Dirichlet data often displays order reduction: the observed convergence order falls below the nominal order because the stage structure…

Numerical Analysis · Mathematics 2026-04-13 Giorgio Maria Cavallazzi , Miguel Pérez Cuadrado , Alfredo Pinelli

For the approximation of solutions for It\^o and Stratonovich stochastic differential equations (SDEs)a new class of efficient stochastic Runge-Kutta (SRK) methods is developed. As the main novelty only two stages are necessary for the…

Numerical Analysis · Mathematics 2025-07-01 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

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

For a particular class of Stratonovich SDE problems, here denoted as single integrand SDEs, we prove that by applying a deterministic Runge-Kutta method of order $p_d$ we obtain methods converging in the mean-square and weak sense with…

Numerical Analysis · Mathematics 2017-02-23 Kristian Debrabant , Anne Kværnø

We consider high order, implicit Runge-Kutta schemes to solve time-dependent stiff PDEs on dynamically adapted grids generated by multiresolution analysis for unsteady problems disclosing localized fronts. The multiresolution finite volume…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Richard Dobbins , Mitchell Smooke

Runge-Kutta (RK) methods may exhibit order reduction when applied to certain stiff problems. While fully implicit RK schemes exist that avoid order reduction via high-stage order, DIRK (diagonally implicit Runge-Kutta) schemes are…

Numerical Analysis · Mathematics 2023-05-31 Abhijit Biswas , David Ketcheson , Benjamin Seibold , David Shirokoff

We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient…

Numerical Analysis · Mathematics 2014-01-09 David I. Ketcheson , Colin B. Macdonald , Steven J. Ruuth

Many HPC applications that solve differential equations rely on the Runge-Kutta family of methods for time integration. Among these methods, the fourth-order accurate RK4 scheme is especially popular. This time integration scheme requires…

General Relativity and Quantum Cosmology · Physics 2026-03-09 Lucas Timotheo Sanches , Steven Robert Brandt , Jay Kalinani , Liwei Ji , Erik Schnetter

In this paper, we present a framework to construct general stochastic Runge-Kutta Lawson schemes. We prove that the schemes inherit the consistency and convergence properties of the underlying Runge-Kutta scheme, and confirm this in some…

Numerical Analysis · Mathematics 2021-05-14 Kristian Debrabant , Anne Kværnø , Nicky Cordua Mattsson

In this paper a new Runge-Kutta type scheme is introduced for nonlinear stochastic partial differential equations (SPDEs) with multiplicative trace class noise. The proposed scheme converges with respect to the computational effort with a…

Numerical Analysis · Mathematics 2012-04-03 Xiaojie Wang , Siqing Gan

Classical convergence theory of Runge-Kutta methods assumes that the time step is small relative to the Lipschitz constant of the ordinary differential equation (ODE). For stiff problems, that assumption is often violated, and a problematic…

Numerical Analysis · Mathematics 2026-05-05 Steven B. Roberts , David Shirokoff , Abhijit Biswas , Benjamin Seibold

In this paper, we develop a higher order symmetric partitioned Runge-Kutta method for a coupled system of differential equations on Lie groups. We start with a discussion on partitioned Runge-Kutta methods on Lie groups of arbitrary order.…

High Energy Physics - Lattice · Physics 2011-09-15 Michèle Wandelt , Michael Günther , Francesco Knechtli , Michael Striebel

In this paper we present a general procedure for designing higher strong order methods for It\^o stochastic differential equations on matrix Lie groups and illustrate this strategy with two novel schemes that have a strong convergence order…

Numerical Analysis · Mathematics 2021-02-09 Michelle Muniz , Matthias Ehrhardt , Michael Günther , Renate Winkler

In this paper we investigate the existence, uniqueness and approximation of solutions of delay differential equations (DDEs) with the right-hand side functions $f=f(t,x,z)$ that are Lipschitz continuous with respect to $x$ but only H\"older…

Numerical Analysis · Mathematics 2024-01-23 Fabio V. Difonzo , Paweł Przybyłowicz , Yue Wu , Xinheng Xie
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