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One of main obstacles in verifying the energy dissipation laws of implicit-explicit Runge-Kutta (IERK) methods for phase field equations is to establish the uniform boundedness of stage solutions without the global Lipschitz continuity…

Numerical Analysis · Mathematics 2024-12-11 Hong-lin Liao , Tao Tang , Xuping Wang , Tao Zhou

A unified theoretical framework is suggested to examine the energy dissipation properties at all stages of additive implicit-explicit Runge-Kutta (IERK) methods up to fourth-order accuracy for gradient flow problems. We construct some…

Numerical Analysis · Mathematics 2024-10-10 Hong-lin Liao , Xuping Wang , Cao Wen

We develop a family of second-order implicit-explicit (IMEX) schemes for the stiff BGK kinetic equation. The method is asymptotic-preserving (can capture the Euler limit without numerically resolving the small Knudsen number) as well as…

Numerical Analysis · Mathematics 2018-02-23 Jingwei Hu , Ruiwen Shu , Xiangxiong Zhang

In this paper we discuss the use of implicit Runge-Kutta schemes for the time discretization of optimal control problems with evolution equations. The specialty of the considered discretizations is that the discretizations schemes for the…

Numerical Analysis · Mathematics 2013-11-05 Thomas G. Flaig

This work gives the asymptotic error distribution of the stochastic Runge--Kutta (SRK) method of strong order $1$ applied to Stratonovich-type stochastic differential equations. For dealing with the implicitness introduced in the diffusion…

Numerical Analysis · Mathematics 2025-08-05 Diancong Jin

This article is devoted to the construction of a new class of semi-Lagrangian (SL) schemes with implicit-explicit (IMEX) Runge-Kutta (RK) time stepping for PDEs involving multiple space-time scales. The semi-Lagrangian (SL) approach fully…

Numerical Analysis · Mathematics 2021-07-16 Walter Boscheri , Maurizio Tavelli , Lorenzo Pareschi

High-order adaptive time-stepping algorithms are of significant practical value and theoretical interest for accelerating long-time fluid-flow simulations and resolving complex dynamical behaviors. While several high-order implicit-explicit…

Numerical Analysis · Mathematics 2026-05-08 Hong-lin Liao , Xiaoming Wang , Xuping Wang , Cao Wen

In this work, an approximate family of implicit multiderivative Runge-Kutta (MDRK) time integrators for stiff initial value problems is presented. The approximation procedure is based on the recent Approximate Implicit Taylor method (Baeza…

Numerical Analysis · Mathematics 2023-02-07 Jeremy Chouchoulis , Jochen Schütz

The paper investigates a variant of semi-implicit spectral deferred corrections (SISDC) in which the stiff, fast dynamics correspond to fast propagating waves ("fast-wave slow-wave problem"). We show that for a scalar test problem with two…

Numerical Analysis · Mathematics 2016-08-18 Daniel Ruprecht , Robert Speck

Semi-Lagrangian schemes with various splitting methods, and with different reconstruction/interpolation strategies have been applied to kinetic simulations. For example, the order of spatial accuracy of the algorithms proposed in {[Qiu and…

Numerical Analysis · Mathematics 2015-06-17 Andrew Christlieb , Wei Guo , Maureen Morton , Jing-Mei Qiu

We consider quadrature formulas of high order in time based on Radau-type, L-stable implicit Runge-Kutta schemes to solve time dependent stiff PDEs. Instead of solving a large nonlinear system of equations, we develop a method that performs…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Matthew Emmett

In this work, we introduce a self-adaptive implicit-explicit (IMEX) time integration scheme, named IMEX-RB, for the numerical integration of systems of ordinary differential equations (ODEs), arising from spatial discretizations of partial…

Numerical Analysis · Mathematics 2025-07-28 Micol Bassanini , Simone Deparis , Francesco Sala , Riccardo Tenderini

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a…

Numerical Analysis · Mathematics 2024-12-13 Hana Mizerová , Katarína Tvrdá

The ability to accurately approximate trajectories of dynamical systems enables their analysis, prediction, and control. Neural network (NN)-based approximations have attracted significant interest due to fast evaluation with good accuracy…

Computational Physics · Physics 2024-01-11 Jochen Stiasny , Spyros Chatzivasileiadis

In this paper we generalize the polynomial time integration framework to additively partitioned initial value problems. The framework we present is general and enables the construction of many new families of additive integrators with…

Numerical Analysis · Mathematics 2023-01-02 Tommaso Buvoli , Ben S. Southworth

For turbulent problems of industrial scale, computational cost may become prohibitive due to the stability constraints associated with explicit time discretization of the underlying conservation laws. On the other hand, implicit methods…

Numerical Analysis · Mathematics 2024-01-31 Carlos A. Pereira , Brian C. Vermeire

We present a parallel implicit-explicit time integration scheme for the advection-diffusion-reaction systems arising from the equations governing low-Mach number combustion with complex chemistry. Our strategy employs parallelization across…

Numerical Analysis · Mathematics 2018-10-03 Francois Hamon , Marcus Day , Michael Minion

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. Unlike other recent work in this area, the proposed methods support mixed…

Numerical Analysis · Mathematics 2023-01-04 Rujeko Chinomona , Daniel R. Reynolds

We present a quantitative comparison between two different Implicit-Explicit Runge-Kutta (IMEX-RK) approaches for the Euler equations of gas dynamics, specifically tailored for the low Mach limit. In this regime, a classical IMEX-RK…

Numerical Analysis · Mathematics 2025-10-23 Giuseppe Orlando , Sebastiano Boscarino , Giovanni Russo

When simulating partial differential equations, hybrid solvers combine coarse numerical solvers with learned correctors. They promise accelerated simulations while adhering to physical constraints. However, as shown in our theoretical…

Machine Learning · Computer Science 2025-11-19 Hao Wei , Aleksandra Franz , Bjoern List , Nils Thuerey
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