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The work deals with two major topics concerning the numerical analysis of Runge-Kutta-like (RK-like) methods, namely their stability and order of convergence. RK-like methods differ from additive RK methods in that their coefficients are…

Numerical Analysis · Mathematics 2025-06-26 Thomas Izgin

Dynamical systems with sub-processes evolving on many different time scales are ubiquitous in applications. Their efficient solution is greatly enhanced by automatic time step variation. This paper is concerned with the theory, construction…

Numerical Analysis · Mathematics 2019-02-06 Moritz Schneider , Jens Lang , Rüdiger Weiner

Adam is a popular variant of stochastic gradient descent for finding a local minimizer of a function. In the constant stepsize regime, assuming that the objective function is differentiable and non-convex, we establish the convergence in…

Machine Learning · Statistics 2020-05-15 Anas Barakat , Pascal Bianchi

This study presents an efficient, accurate, effective and unconditionally stable time stepping scheme for the Darcy-Brinkman equations in double-diffusive convection. The stabilization within the proposed method uses the idea of stabilizing…

Numerical Analysis · Mathematics 2018-04-10 Aytekin Çıbık , Medine Demir , Songul Kaya

This paper presents a class of Two-Step General Linear Methods for the numerical solution of Retarded Functional Differential Equations. Explicit methods up to order five are constructed. To avoid order reduction for mildly stiff problems…

Numerical Analysis · Mathematics 2017-04-18 Anton Tuzov

This paper presents a class of Two-Step General Linear Methods for the numerical solution of Retarded Functional Differential Equations. Explicit methods up to order five are constructed. To avoid order reduction for mildly stiff problems…

Numerical Analysis · Mathematics 2009-01-30 Anton Tuzov

In this paper, we extend the Paired-Explicit Runge-Kutta schemes by Vermeire et. al. to fourth-order of consistency. Based on the order conditions for partitioned Runge-Kutta methods we motivate a specific form of the Butcher arrays which…

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

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

We consider first-order methods with constant step size for minimizing locally Lipschitz coercive functions that are tame in an o-minimal structure on the real field. We prove that if the method is approximated by subgradient trajectories,…

Optimization and Control · Mathematics 2023-08-03 Cédric Josz , Lexiao Lai

The usual definition of the stability region of implicit multistep methods often implies that there are some isolated points of stability within the region of instability of the numerical method. These isolated stable points may appear when…

Numerical Analysis · Mathematics 2019-01-30 Lajos Lóczi

Convenient, easy to implement stochastic integration methods are developed on the basis of abstract one-step deterministic order $p$ integration techniques. The abstraction as an arbitrary one step map allows the inspection of easy to…

Numerical Analysis · Mathematics 2025-10-15 J. Woodfield , A. Lobbe

We consider the development of high order asymptotic-preserving linear multistep methods for kinetic equations and related problems. The methods are first developed for BGK-like kinetic models and then extended to the case of the full…

Numerical Analysis · Mathematics 2016-03-06 Giacomo Dimarco , Lorenzo Pareschi

In this paper, we extend the implicit-explicit (IMEX) methods of Peer type recently developed in [Lang, Hundsdorfer, J. Comp. Phys., 337:203--215, 2017] to a broader class of two-step methods that allow the construction of super-convergent…

Numerical Analysis · Mathematics 2018-06-08 Moritz Schneider , Jens Lang , Willem Hundsdorfer

In this paper we study the stability of explicit finite difference discretizations of linear advection-diffusion equations (ADE) with arbitrary order of accuracy in the context of method of lines. The analysis first focuses on the stability…

Numerical Analysis · Mathematics 2020-06-17 Xianyi Zeng , Md Mahmudul Hasan

Stiff and chaotic differential equations are challenging for time-stepping numerical methods. For explicit methods, the required time step resolution significantly exceeds the resolution associated with the smoothness of the exact solution…

Numerical Analysis · Mathematics 2024-02-28 Jan Scheffel

This paper introduces the Runge-Kutta Chebyshev descent method (RKCD) for strongly convex optimisation problems. This new algorithm is based on explicit stabilised integrators for stiff differential equations, a powerful class of numerical…

Optimization and Control · Mathematics 2020-06-30 Armin Eftekhari , Bart Vandereycken , Gilles Vilmart , Konstantinos C. Zygalakis

Second-order optimization methods exhibit fast convergence to critical points, however, in nonconvex optimization, these methods often require restrictive step-sizes to ensure a monotonically decreasing objective function. In the presence…

Optimization and Control · Mathematics 2024-10-11 Aayushya Agarwal , Larry Pileggi , Ronald Rohrer

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

In the numerical solution of partial differential equations using a method-of-lines approach, the availability of high order spatial discretization schemes motivates the development of sophisticated high order time integration methods. For…

Numerical Analysis · Computer Science 2016-11-25 Hong Zhang , Adrian Sandu , Sebastien Blaise
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