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This paper investigates the energy conservation properties of explicit Runge--Kutta (RK) time discretizations for autonomous skew-symmetric systems. For linear problems, we present a general framework for constructing RK methods in which…

Numerical Analysis · Mathematics 2026-05-12 Jinjie Liu , Moysey Brio

Numerical integrators could be used to form interpolation conditions when training neural networks to approximate the vector field of an ordinary differential equation (ODE) from data. When numerical one-step schemes such as the Runge-Kutta…

Numerical Analysis · Mathematics 2023-03-08 Håkon Noren

A novel second order family of explicit stabilized Runge-Kutta-Chebyshev methods for advection-diffusion-reaction equations is introduced. The new methods outperform existing schemes for relatively high Peclet number due to their favorable…

Numerical Analysis · Mathematics 2023-06-09 Ibrahim Almuslimani

The strong convergence of numerical methods for stochastic differential equations (SDEs) for $t\in[0,\infty)$ is proved. The result is applicable to any one-step numerical methods with Markov property that have the finite time strong…

Numerical Analysis · Mathematics 2023-07-12 Wei Liu , Yudong Wang

Semi-Lagrangian methods are numerical methods designed to find approximate solutions to particular time-dependent partial differential equations (PDEs) that describe the advection process. We propose semi-Lagrangian one-step methods for…

Numerical Analysis · Mathematics 2017-03-07 Nikolai D. Lipscomb , Daniel X. Guo

This work establishes the weak convergence of Euler-Maruyama's approximation for stochastic differential equations (SDEs) with singular drifts under the integrability condition in lieu of the widely used growth condition. This method is…

Probability · Mathematics 2018-08-23 Jinghai Shao

In this paper, we summarize the results about the strong convergence rate of the Ninomiya-Victoir scheme and the stable convergence in law of its normalized error that we obtained in previous papers. We then recall the properties of the…

Probability · Mathematics 2016-12-22 Anis Al Gerbi , Benjamin Jourdain , Emmanuelle Clément

In this paper, for solving a class of linear parabolic equations in rectangular domains, we have proposed an efficient Parareal exponential integrator finite element method. The proposed method first uses the finite element approximation…

Numerical Analysis · Mathematics 2024-12-03 Jianguo Huang , Yuejin Xu

In this work, we present a general technique for establishing the strong convergence of numerical methods for stochastic delay differential equations (SDDEs) in the infinite horizon. This technique can also be extended to analyze certain…

Numerical Analysis · Mathematics 2025-05-21 Yudong Wang , Hongjiong Tian

A linear evolving surface partial differential equation is first discretized in space by an arbitrary Lagrangian Eulerian (ALE) evolving surface finite element method, and then in time either by a Runge-Kutta method, or by a backward…

Numerical Analysis · Mathematics 2015-01-14 Balázs Kovács , Christian Andreas Power Guerra

This work investigates numerical approximations of index 1 stochastic differential algebraic equations (SDAEs) with non-constant singular matrices under non-global Lipschitz conditions. Analyzing the strong convergence rates of numerical…

Numerical Analysis · Mathematics 2025-09-16 Lin Chen , Ziheng Chen , Jing Zhao

Fully implicit Runge-Kutta (IRK) methods have many desirable accuracy and stability properties as time integration schemes, but high-order IRK methods are not commonly used in practice with large-scale numerical PDEs because of the…

Numerical Analysis · Mathematics 2021-10-07 Ben S. Southworth , Oliver Krzysik , Will Pazner

In this work we analyze the convergence properties of the Spectral Deferred Correction (SDC) method originally proposed by Dutt et al. [BIT, 40 (2000), pp. 241--266]. The framework for this high-order ordinary differential equation (ODE)…

Numerical Analysis · Mathematics 2019-07-24 Mathew F. Causley , David C. Seal

Many stochastic differential equations (SDEs) in the literature have a superlinearly growing nonlinearity in their drift or diffusion coefficient. Unfortunately, moments of the computationally efficient Euler-Maruyama approximation method…

Probability · Mathematics 2020-11-25 Martin Hutzenthaler , Arnulf Jentzen

In this article we propose a new explicit Euler-type approximation method for stochastic differential equations (SDEs). In this method, Brownian increments in the recursion of the Euler method are replaced by suitable bounded functions of…

Probability · Mathematics 2022-04-27 Martin Hutzenthaler , Kai Kisker

We propose a $\theta$-scheme to discretize the $d$-dimensional stochastic cubic Schr\"odinger equation in Stratono\-vich sense. A uniform bound for the Hamiltonian of the discrete problem is obtained, which is a crucial property to verify…

Numerical Analysis · Mathematics 2015-09-29 Chuchu Chen , Jialin Hong , Andreas Prohl

We propose a class of semi-Lagrangian methods of high approximation order in space and time, based on spectral element space discretizations and exponential integrators of Runge-Kutta type. We discuss the extension of these methods to the…

Numerical Analysis · Mathematics 2016-02-24 Elena Celledoni , Bawfeh Kingsley Kometa , Olivier Verdier

Exponential integrators are explicit methods for solving ordinary differential equations that treat linear behaviour exactly. The stiff-order conditions for exponential integrators derived in a Banach space framework by Hochbruck and…

Computational Physics · Physics 2023-03-28 Thoma Zoto , John C. Bowman

Exponential Runge-Kutta methods for semilinear ordinary differential equations can be extended to abstract differential equations, defined on Banach spaces. Thanks to the sun-star theory, both delay differential equations and renewal…

Numerical Analysis · Mathematics 2024-10-02 Alessia Ando' , Rossana Vermiglio

Stabilized methods (also called Chebyshev methods) are explicit methods with extended stability domains along the negative real axis. These methods are intended for large mildly stiff problems, originating mainly from parabolic PDEs. In…

Numerical Analysis · Mathematics 2023-03-30 Andrew Moisa , Boris Faleichik