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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 provide a framework for high-order discretizations of nonlinear scalar convection-diffusion equations that satisfy a discrete maximum principle. The resulting schemes can have arbitrarily high order accuracy in time and space, and can be…

Numerical Analysis · Mathematics 2021-09-20 Manuel Quezada de Luna , David I. Ketcheson

Radiation hydrodynamics are a challenging multiscale and multiphysics set of equations. To capture the relevant physics of interest, one typically must time step on the hydrodynamics timescale, making explicit integration the obvious…

Numerical Analysis · Mathematics 2024-08-14 Ben S. Southworth , HyeongKae Park , Svetlana Tokareva , Marc Charest

The non-differentiability of the singular nonlinearity (such as $f=\ln|u|^2$) at $u=0$ presents significant challenges in devising accurate and efficient numerical schemes for the logarithmic Schr\"{o}dinger equation (LogSE). To address…

Numerical Analysis · Mathematics 2024-11-14 Jingye Yan , Hong Zhang , Yabing Wei , Xu Qian

This work focuses on the numerical study of a recently published class of Runge-Kutta methods designed for mixed-precision arithmetic. We employ the methods in solving partial differential equations on modern hardware. In particular we…

Numerical Analysis · Mathematics 2024-12-24 Ivo Dravins , Marcel Koch , Victoria Griehl , Katharina Kormann

In this paper, we develop new techniques for solving the large, coupled linear systems that arise from fully implicit Runge-Kutta methods. This method makes use of the iterative preconditioned GMRES algorithm for solving the linear systems,…

Numerical Analysis · Mathematics 2017-03-08 Will Pazner , Per-Olof Persson

Diffusion models play a pivotal role in contemporary generative modeling, claiming state-of-the-art performance across various domains. Despite their superior sample quality, mainstream diffusion-based stochastic samplers like DDPM often…

Machine Learning · Statistics 2024-10-08 Yuchen Wu , Yuxin Chen , Yuting Wei

In order to solve continuous-time optimal control problems, direct methods transcribe the infinite-dimensional problem to a nonlinear program (NLP) using numerical integration methods. In cases where the integration error can be manipulated…

Optimization and Control · Mathematics 2025-03-18 Jakob Harzer , Jochem De Schutter , Moritz Diehl

In this paper we discuss energy conservation issues related to the numerical solution of the nonlinear wave equation, when a Fourier expansion is considered for the space discretization. The obtained semi-discrete problem is then solved in…

Numerical Analysis · Mathematics 2014-10-28 Luigi Brugnano , Gianluca Frasca Caccia , Felice Iavernaro

Semi-discrete Runge-Kutta schemes for nonlinear diffusion equations of parabolic type are analyzed. Conditions are determined under which the schemes dissipate the discrete entropy locally. The dissipation property is a consequence of the…

Numerical Analysis · Mathematics 2015-06-24 Ansgar Jüngel , Stefan Schuchnigg

We introduce a class of exponential Runge-Kutta integration methods for kinetic equations. The methods are based on a decomposition of the collision operator into an equilibrium and a non equilibrium part and are exact for relaxation…

Numerical Analysis · Mathematics 2010-10-08 Giacomo Dimarco , Lorenzo Pareschi

In this paper, exponential Runge-Kutta methods of collocation type (ERKC) which were originally proposed in (Appl Numer Math 53:323-339, 2005) are extended to semilinear parabolic problems with time-dependent delay. Two classes of the ERKC…

Numerical Analysis · Mathematics 2025-12-30 Qiumei Huang , Alexander Ostermann , Gangfan Zhong

With the increasing industrial demands, two families of high-order numerical schemes are widely used within the computational fluid dynamics community. One is the method of line, which relies on Runge-Kutta (RK) time-stepping applied to a…

Mathematical Physics · Physics 2026-01-27 Qihui Gao , Xing Ji , Zhifang Du , Shiyi Li , Yibing Chen , Kun Xu

Cloud and precipitation microphysics packages in atmospheric general circulation models typically use first-order time integration methods with a large time step, requiring ad hoc limiters and substepping of the sedimentation scheme to…

Atmospheric and Oceanic Physics · Physics 2026-03-13 Justin Dong , Sean P. Santos , Steven B. Roberts , Christopher J. Vogl , Carol S. Woodward

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

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

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

We present a strategy to speed up Runge-Kutta-based ODE simulations of large systems with nearest-neighbor coupling. We identify the cache/memory bandwidth as the crucial performance bottleneck. To reduce the required bandwidth, we…

Computational Physics · Physics 2014-12-02 Mario Mulansky

Implicit Runge--Kutta (IRK) methods are highly effective for solving stiff ordinary differential equations (ODEs) but can be computationally expensive for large-scale problems due to the need of solving coupled algebraic equations at each…

Numerical Analysis · Mathematics 2025-09-18 Fabio Durastante , Mariarosa Mazza

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

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
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