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Runge-Kutta methods are the classic family of solvers for ordinary differential equations (ODEs), and the basis for the state of the art. Like most numerical methods, they return point estimates. We construct a family of probabilistic…

Machine Learning · Statistics 2014-10-27 Michael Schober , David Duvenaud , Philipp Hennig

In this article we develop a numerical scheme to deal with interfaces between touching numerical grids when solving the second-order wave equation. We show that it is possible to implement an interface scheme of "penalty" type for the…

Computational Physics · Physics 2014-06-13 F. Parisi , M. Cécere , M. Iriondo , O. Reula

This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive noise under more relaxed conditions. The SPDE is discretized…

Numerical Analysis · Mathematics 2020-01-01 Antoine Tambue , Jean Daniel Mukam

We consider a Runge--Kutta method for the numerical time integration of the nonstationary incompressible Navier--Stokes equations. This yields a sequence of nonlinear problems to be solved for the stages of the Runge--Kutta method. The…

Numerical Analysis · Mathematics 2025-06-06 Santolo Leveque , Yunhui He , Maxim Olshanskii

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

We construct a family of two new optimized explicit Runge-Kutta methods with zero phase-lag and derivatives for the numerical solution of the time-independent radial Schr\"odinger equation and related ordinary differential equations with…

Numerical Analysis · Mathematics 2008-11-18 Z. A. Anastassi , D. S. Vlachos , T. E. Simos

We develop a fully discrete, semi-implicit mixed finite element method for approximating solutions to a class of fourth-order stochastic partial differential equations (SPDEs) with non-globally Lipschitz and non-monotone nonlinearities,…

Numerical Analysis · Mathematics 2026-02-17 Beniamin Goldys , Agus L. Soenjaya , Thanh Tran

In this paper, we construct stochastic symplectic Runge--Kutta (SSRK) methods of high strong order for Hamiltonian systems with additive noise. By means of colored rooted tree theory, we combine conditions of mean-square order 1.5 and…

Numerical Analysis · Mathematics 2017-05-24 Weien Zhou , Jingjing Zhang , Jialin Hong , Songhe Song

Neural networks have proven to be efficient surrogate models for tackling partial differential equations (PDEs). However, their applicability is often confined to specific PDEs under certain constraints, in contrast to classical PDE solvers…

Machine Learning · Computer Science 2023-10-03 Hoyun Choi , Sungyeop Lee , B. Kahng , Junghyo Jo

The use of high order fully implicit Runge-Kutta methods is of significant importance in the context of the numerical solution of transient partial differential equations, in particular when solving large scale problems due to fine space…

Numerical Analysis · Mathematics 2023-02-27 Ivo Dravins , Stefano Serra-Capizzano , Maya Neytcheva

This paper contains an error analysis of two randomized explicit Runge-Kutta schemes for ordinary differential equations (ODEs) with time-irregular coefficient functions. In particular, the methods are applicable to ODEs of Carath\'eodory…

Numerical Analysis · Mathematics 2017-07-13 Raphael Kruse , Yue Wu

A mixed accuracy framework for Runge--Kutta methods presented in Grant [JSC 2022] and applied to diagonally implicit Runge--Kutta (DIRK) methods can significantly speed up the computation by replacing the implicit solver by less expensive…

New time integration methods are proposed for simulating incompressible multiphase flow in pipelines described by the one-dimensional two-fluid model. The methodology is based on 'half-explicit' Runge-Kutta methods, being explicit for the…

Numerical Analysis · Mathematics 2019-02-19 Benjamin Sanderse , Arthur E. P. Veldman

In this master thesis we have compared different second order stabilized explicit Runge-Kutta methods when applied to the incompressible Navier-Stokes equations by means of a projection method and a differential algebraic approach. We…

Numerical Analysis · Mathematics 2022-03-30 Giacomo Rosilho de Souza

Gamma distributed delay differential equations (DDEs) arise naturally in many modelling applications. However, appropriate numerical methods for generic Gamma distributed DDEs are not currently available. Accordingly, modellers often resort…

Numerical Analysis · Mathematics 2021-04-09 Tyler Cassidy , Peter Gillich , Antony R. Humphries , Christiaan H. van Dorp

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

Next-generation exascale machines with extreme levels of parallelism will provide massive computing resources for large scale numerical simulations of complex physical systems at unprecedented parameter ranges. However, novel numerical…

Computational Physics · Physics 2023-02-08 Komal Kumari , Emmet Cleary , Swapnil Desai , Diego A. Donzis , Jacqueline H. Chen , Konduri Aditya

In this paper, we consider the numerical approximation of a general second order semilinear stochastic partial differential equation (SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the nonlinear…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

In this note we discuss the construction of high order asymptotic preserving numerical schemes for the Boltzmann equation. The methods are based on the use of Implicit-Explicit (IMEX) Runge-Kutta methods combined with a penalization…

Numerical Analysis · Mathematics 2012-02-24 Giacomo Dimarco , Lorenzo Pareschi

This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems…

Probability · Mathematics 2015-09-21 Achref Bachouch , Mohamed Anis Ben Lasmar , Anis Matoussi , Mohamed Mnif