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In this paper, two novel classes of implicit exponential Runge-Kutta (ERK) methods are studied for solving highly oscillatory systems. First of all, we analyze the symplectic conditions of two kinds of exponential integrators, and present a…

Numerical Analysis · Mathematics 2023-12-05 Xianfa Hu , Wansheng Wang , Bin Wang , Yonglei Fang

This paper continues to study the explicit two-stage fourth-order accurate time discretiza- tions [5, 7]. By introducing variable weights, we propose a class of more general explicit one-step two-stage time discretizations, which are…

Numerical Analysis · Mathematics 2020-07-07 Yuhuan Yuan , Huazhong Tang

In this paper we present a general procedure for designing higher strong order methods for It\^o stochastic differential equations on matrix Lie groups and illustrate this strategy with two novel schemes that have a strong convergence order…

Numerical Analysis · Mathematics 2021-02-09 Michelle Muniz , Matthias Ehrhardt , Michael Günther , Renate Winkler

This paper considers a two-step fourth-order modified explicit Euler/Crank-Nicolson numerical method for solving the time-variable fractional mobile-immobile advection-dispersion model subjects to suitable initial and boundary conditions.…

Numerical Analysis · Mathematics 2022-05-12 Eric Ngondiep

The pressure-correction method is a well established approach for simulating unsteady, incompressible fluids. It is well-known that implicit discretization of the time derivative in the momentum equation e.g. using a backward…

Numerical Analysis · Mathematics 2024-07-17 Utku Kaya , Thomas Richter

The problem of solving stochastic differential-algebraic equations (SDAEs) of index one with a scalar driving Brownian motion is considered. Recently, the authors proposed a class of stiffly accurate stochastic Runge-Kutta (SRK) methods…

Numerical Analysis · Mathematics 2013-11-07 Dominique Küpper , Anne Kværnø , Andreas Rößler

We develop and analyze a highly efficient, second-order time-marching scheme for infinite-dimensional nonlinear geophysical fluid models, designed to accurately approximate invariant measures-that is, the stationary statistical properties…

Numerical Analysis · Mathematics 2025-10-08 Daozhi Han , Xiaoming Wang

In this paper we present and analyze a general framework for constructing high order explicit local time stepping (LTS) methods for hyperbolic conservation laws. In particular, we consider the model problem discretized by Runge-Kutta…

Numerical Analysis · Mathematics 2019-05-24 Thi-Thao-Phuong Hoang , Lili Ju , Wei Leng , Zhu Wang

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig

We study unconstrained smooth convex optimization under stochastic first- and zeroth-order oracles subject only to finite-moment bounds, naturally admitting persistent bias and heavy-tailed noise. In this hostile environment, integrating…

Optimization and Control · Mathematics 2026-04-20 Shunzhi Zhang , Shichen Liao , Congying Han , Tiande Guo

The space nonlocal Allen-Cahn equation is a famous example of fractional reaction-diffusion equations. It is also an extension of the classical Allen-Cahn equation, which is widely used in physics to describe the phenomenon of two-phase…

Numerical Analysis · Mathematics 2025-02-05 Yuxin Zhang , Hengfei Ding

This paper introduces a new class of numerical methods for the time integration of evolution equations set as Cauchy problems of ODEs or PDEs. The systematic design of these methods mixes the Runge-Kutta collocation formalism with…

Analysis of PDEs · Mathematics 2021-11-19 Guillaume Dujardin , Ingrid Lacroix-Violet

In this paper we consider an approach to improve the performance of exponential Runge--Kutta integrators and Lawson schemes} in cases where the solution of a related, but usually much simpler, problem can be computed efficiently. While for…

Numerical Analysis · Mathematics 2023-10-20 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

This work focuses on the construction of a new class of fourth-order accurate methods for multirate time evolution of systems of ordinary differential equations. We base our work on the Recursive Flux Splitting Multirate (RFSMR) version of…

Numerical Analysis · Mathematics 2019-08-26 Jean M. Sexton , Daniel R. Reynolds

We propose two new classes of time integrators for stiff DEs: the implicit-explicit exponential (IMEXP) and the hybrid exponential methods. In contrast to the existing exponential schemes, the new methods offer significant computational…

Numerical Analysis · Mathematics 2016-05-11 Vu Thai Luan , Mayya Tokman , Greg Rainwater

This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady…

Numerical Analysis · Mathematics 2012-04-10 Stéphane Descombes , Max Duarte , Thierry Dumont , Violaine Louvet , Marc Massot

For the simulations of unsteady flow, the global time step becomes really small with a large variation of local cell size. In this paper, an implicit high-order gas-kinetic scheme (HGKS) is developed to remove the restrictions on the time…

Numerical Analysis · Mathematics 2024-03-04 Yaqing Yang , Liang Pan , Kun Xu

We explore the performance and advantages/disadvantages of using unconditionally stable explicit super time-stepping (STS) algorithms versus implicit schemes with Krylov solvers for integrating parabolic operators in thermodynamic MHD…

Computational Engineering, Finance, and Science · Computer Science 2017-06-28 Ronald M. Caplan , Zoran Mikic , Jon A. Linker , Roberto Lionello

A preceding paper demonstrated that explicit asymptotic methods generally work much better for extremely stiff reaction networks than has previously been shown in the literature. There we showed that for systems well removed from…

Solar and Stellar Astrophysics · Physics 2022-10-19 M. W. Guidry , J. A. Harris

Many control, optimization, and learning algorithms rely on discretizations of continuous-time contracting systems, where preservation of contractivity under numerical integration is key for stability, robustness, and reliable fixed-point…

Systems and Control · Electrical Eng. & Systems 2026-03-13 Yu Kawano , Francesco Bullo