English
Related papers

Related papers: Error analysis of randomized Runge-Kutta methods f…

200 papers

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

For a large class of fully nonlinear parabolic equations, which include gradient flows for energy functionals that depend on the solution gradient, the semidiscretization in time by implicit Runge-Kutta methods such as the Radau IIA methods…

Numerical Analysis · Mathematics 2016-06-14 Peer C. Kunstmann , Buyang Li , Christian Lubich

In this paper, we present error estimates of fully discrete Runge--Kutta discontinuous Galerkin (DG) schemes for linear time-dependent partial differential equations. The analysis applies to explicit Runge--Kutta time discretizations of any…

Numerical Analysis · Mathematics 2020-01-07 Zheng Sun , Chi-Wang Shu

The aim of this paper is to construct and analyze explicit exponential Runge-Kutta methods for the temporal discretization of linear and semilinear integro-differential equations. By expanding the errors of the numerical method in terms of…

Numerical Analysis · Mathematics 2023-01-24 Alexander Ostermann , Fardin Saedpanah , Nasrin Vaisi

We apply Runge-Kutta methods to linear partial differential-algebraic equations of the form $Au_t(t,x) + B(u_{xx}(t,x)+ru_x(t,x))+Cu(t,x) = f(t,x)$, where $A,B,C\in\R^{n,n}$ and the matrix $A$ is singular. We prove that under certain…

Numerical Analysis · Mathematics 2013-03-19 Kristian Debrabant , Karl Strehmel

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

When applied to stiff, linear differential equations with time-dependent forcing, Runge-Kutta methods can exhibit convergence rates lower than predicted by the classical order condition theory. Commonly, this order reduction phenomenon is…

Numerical Analysis · Mathematics 2022-02-15 Steven Roberts , Adrian Sandu

A coercivity property of temporal convolution operators is an essential tool in the analysis of time-dependent boundary integral equations and their space and time discretisations. It is known that this coercivity property is inherited by…

Numerical Analysis · Mathematics 2017-02-28 Lehel Banjai , Christian Lubich

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

This paper is devoted to examining the stability of Runge-Kutta methods for solving nonlinear Volterra delay-integro-differential-algebraic equations (DIDAEs) with constant delay. Hybrid numerical schemes combining Runge-Kutta methods and…

Numerical Analysis · Mathematics 2025-08-19 Gehao Wang , Yuexin Yu

There exist many Runge-Kutta methods (explicit or implicit), more or less adapted to specific problems. Some of them have interesting properties, such as stability for stiff problems or symplectic capability for problems with energy…

Numerical Analysis · Mathematics 2018-04-16 Julien Alexandre dit Sandretto

A focus of recent research in quantum computing has been on developing quantum algorithms for differential equations solving using variational methods on near-term quantum devices. A promising approach involves variational algorithms, which…

Quantum Physics · Physics 2026-02-03 David Dechant , Liubov Markovich , Vedran Dunjko , Jordi Tura

In this paper we consider time-dependent PDEs discretized by a special class of Physics Informed Neural Networks whose design is based on the framework of Runge--Kutta and related time-Galerkin discretizations. The primary motivation for…

Numerical Analysis · Mathematics 2026-02-10 Georgios Akrivis , Charalambos G. Makridakis , Costas Smaragdakis

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

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

A semi-implicit-explicit (semi-IMEX) Runge-Kutta (RK) method is proposed for the numerical integration of ordinary differential equations (ODEs) of the form $\mathbf{u}' = \mathbf{f}(t,\mathbf{u}) + G(t,\mathbf{u}) \mathbf{u}$, where…

Numerical Analysis · Mathematics 2025-04-15 Lingyun Ding

Diffusion probabilistic models generate samples by learning to reverse a noise-injection process that transforms data into noise. A key development is the reformulation of the reverse sampling process as a deterministic probability flow…

Machine Learning · Computer Science 2025-08-15 Daniel Zhengyu Huang , Jiaoyang Huang , Zhengjiang Lin

We propose a numerical scheme to solve the time dependent linear Schr\"odinger equation. The discretization is carried out by combining a Runge-Kutta time-stepping scheme with a finite element discretization in space. Since the…

Numerical Analysis · Mathematics 2018-03-07 Jens Markus Melenk , Alexander Rieder

The aim of this paper is to construct and analyze exponential Runge-Kutta methods for the temporal discretization of a class of semilinear parabolic problems with arbitrary state-dependent delay. First, the well-posedness of the problem is…

Numerical Analysis · Mathematics 2025-09-12 Qiumei Huang , Alexander Ostermann , Gangfan Zhong

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
‹ Prev 1 2 3 10 Next ›