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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

Dynamic systems have a fundamental relevance in the description of physical phenomena. The search for more accurate and faster numerical integration methods for the resolution of such systems is, therefore, an important topic of research.…

Computational Physics · Physics 2025-10-10 J. Avellar , L. G. S. Duarte , L. A. C. P. da Mota , L. O. Pereira

Explicit stabilized methods are an efficient alternative to implicit schemes for the time integration of stiff systems of differential equations in large dimension. In this paper, we derive explicit stabilized integrators of orders one and…

Numerical Analysis · Mathematics 2023-06-09 Ibrahim Almuslimani , Gilles Vilmart

In this paper we present a novel randomized block coordinate descent method for the minimization of a convex composite objective function. The method uses (approximate) partial second-order (curvature) information, so that the algorithm…

Optimization and Control · Mathematics 2015-05-11 Kimon Fountoulakis , Rachael Tappenden

This paper illuminates the derivation, the applicability, and the efficiency of the Multiplicative Runge-Kutta Method, derived in the frame- work of geometric multiplicative calculus. The removal of the restrictions of geometric…

Numerical Analysis · Mathematics 2019-02-20 Mustafa Riza , Hatice Aktöre

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

We consider Implicit-Explicit (IMEX) Runge-Kutta (R-K) schemes for hyperbolic systems with stiff relaxation in the so-called diffusion limit. In such regime the system relaxes towards a convection-diffusion equation. The first objective of…

Numerical Analysis · Mathematics 2015-05-30 S. Boscarino , L. Pareschi , G. Russo

Solving the reactive low-Mach Navier-Stokes equations with high-order adaptive methods in time is still a challenging problem, in particular due to the handling of the algebraic variables involved in the mass constraint. We focus on the…

Analysis of PDEs · Mathematics 2025-10-02 Laurent François , Joël Dupays , Dmitry Davidenko , Marc Massot

We deal with optimal approximation of solutions of ODEs under local Lipschitz condition and inexact discrete information about the right-hand side functions. We show that the randomized two-stage Runge-Kutta scheme is the optimal method…

Numerical Analysis · Mathematics 2021-03-23 Tomasz Bochacik , Maciej Goćwin , Paweł M. Morkisz , Paweł Przybyłowicz

The conditioning of implicit Runge-Kutta (RK) integration for linear finite element approximation of diffusion equations on general anisotropic meshes is investigated. Bounds are established for the condition number of the resulting linear…

Numerical Analysis · Mathematics 2021-01-13 Weizhang Huang , Lennard Kamenski , Jens Lang

We note a fact that stiff systems or differential equations that have highly oscillatory solutions cannot be solved efficiently using conventional methods. In this paper, we study two new classes of exponential Runge-Kutta (ERK) integrators…

Numerical Analysis · Mathematics 2023-12-06 Bin Wang , Xianfa Hu , Xinyuan Wu

In this paper, we propose a class of high-order and energy-stable implicit-explicit relaxation Runge-Kutta (IMEX RRK) schemes for solving the phase-field gradient flow models. By incorporating the scalar auxiliary variable (SAV) method, the…

Numerical Analysis · Mathematics 2025-03-26 Yuxiu Cheng , Kun Wang , Kai Yang

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

With the rise of deep learning technology in practical applications, Convolutional Neural Networks (CNNs) have been able to assist humans in solving many real-world problems. To enhance the performance of CNNs, numerous network…

Machine Learning · Computer Science 2024-09-10 Qi Wang , Zijun Gao , Mingxiu Sui , Taiyuan Mei , Xiaohan Cheng , Iris Li

In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and…

Optimization and Control · Mathematics 2026-05-12 Po-Wei Wang , Wei-Cheng Chang , J. Zico Kolter

Robust model predictive control algorithms are essential for addressing unavoidable errors due to the uncertainty in predicting real-world systems. However, the formulation of such algorithms typically results in a trade-off between…

Systems and Control · Electrical Eng. & Systems 2025-04-25 Moritz Heinlein , Sankaranarayanan Subramanian , Sergio Lucia

We propose entropy-preserving and entropy-stable partitioned Runge--Kutta (RK) methods. In particular, we extend the explicit relaxation Runge--Kutta methods to IMEX--RK methods and a class of explicit second-order multirate methods for…

Numerical Analysis · Mathematics 2022-07-21 Shinhoo Kang , Emil M. Constantinescu

A new approach for the construction of high order A-stable explicit integrators for ordinary differential equations (ODEs) is theoretically studied. Basically, the integrators are obtained by splitting, at each time step, the solution of…

Numerical Analysis · Mathematics 2012-08-24 H. de la Cruz , R. J. Biscay , J. C. Jimenez , F. Carbonell

With this short note, we close a gap in the linear stability theory of block predictor-corrector Runge-Kutta schemes originally proposed for the parallel solution of ODEs.

Numerical Analysis · Mathematics 2023-06-02 Friedemann Kemm

The parametric instability arising when ordinary differential equations (ODEs) are numerically integrated with Runge-Kutta-Nystr\"om (RKN) methods with varying step sizes is investigated. It is shown that when linear constant coefficient…

Numerical Analysis · Mathematics 2012-09-25 Robert Piché
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