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We study the A-stability and accuracy characteristics of Clenshaw-Curtis collocation. We present closed-form expressions to evaluate the Runge-Kutta coefficients of these methods. From the A-stability study, Clenshaw-Curtis methods are…

Numerical Analysis · Mathematics 2022-11-29 Ahmed Atallah , Ahmad Bani Younes

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

This paper focuses on the strong convergence rate of both Runge--Kutta methods and simplified step-$N$ Euler schemes for stochastic differential equations driven by multi-dimensional fractional Brownian motions with $H\in(\frac12,1)$. Based…

Numerical Analysis · Mathematics 2021-04-23 Jialin Hong , Chuying Huang , Xu Wang

We propose a new method to solve the relativistic hydrodynamic equations based on implicit Runge-Kutta methods with a locally optimized fixed-point iterative solver. For numerical demonstration, we implement our idea for ideal hydrodynamics…

Nuclear Theory · Physics 2024-04-16 Nathan Touroux , Masakiyo Kitazawa , Koichi Murase , Marlene Nahrgang

We interpret a wide range of flavors of Spectral Deferred Corrections (SDC) as Runge-Kutta methods (RKM). Using Butcher series, we show that the considered class of SDC methods achieve at least order p after p iterations compared to the…

Numerical Analysis · Mathematics 2026-04-06 Eugen Bronasco , Joscha Fregin , Daniel Ruprecht , Gilles Vilmart

The analysis of strong-stability-preserving (SSP) linear multistep methods is extended to semi-discretized problems for which different terms on the right-hand side satisfy different forward Euler (or circle) conditions. Optimal additive…

Numerical Analysis · Mathematics 2022-04-05 Yiannis Hadjimichael , David I. Ketcheson

Multiphysics systems are driven by multiple processes acting simultaneously, and their simulation leads to partitioned systems of differential equations. This paper studies the solution of partitioned systems of differential equations using…

Numerical Analysis · Mathematics 2019-12-04 Mahesh Narayanamurthi , Adrian Sandu

This work introduces a new class of Runge-Kutta methods for solving nonlinearly partitioned initial value problems. These new methods, named nonlinearly partitioned Runge-Kutta (NPRK), generalize existing additive and component-partitioned…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Ben S. Southworth

We consider Hamiltonian systems driven by multi-dimensional Gaussian processes in rough path sense, which include fractional Brownian motions with Hurst parameter $H\in(1/4,1/2]$. We indicate that the phase flow preserves the symplectic…

Numerical Analysis · Mathematics 2018-03-20 Jialin Hong , Chuying Huang , Xu Wang

For a particular class of Stratonovich SDE problems, here denoted as single integrand SDEs, we prove that by applying a deterministic Runge-Kutta method of order $p_d$ we obtain methods converging in the mean-square and weak sense with…

Numerical Analysis · Mathematics 2017-02-23 Kristian Debrabant , Anne Kværnø

In this paper, a family of arbitrarily high-order structure-preserving exponential Runge-Kutta methods are developed for the nonlinear Schr\"odinger equation by combining the scalar auxiliary variable approach with the exponential…

Numerical Analysis · Mathematics 2020-09-15 Jin Cui , Zhuangzhi Xu , Yushun Wang , Chaolong Jiang

We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient…

Numerical Analysis · Mathematics 2014-01-09 David I. Ketcheson , Colin B. Macdonald , Steven J. Ruuth

The main goal of this paper is to investigate the order reduction phenomenon that appears in the integral deferred correction (InDC) methods based on implicit-explicit (IMEX) Runge-Kutta (R-K) schemes when applied to a class of stiff…

Numerical Analysis · Mathematics 2017-01-18 S. Boscarino , J. Qiu , G. Russo

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

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

In this paper, Runge-Kutta-Gegenbauer (RKG) stability polynomials of arbitrarily high order of accuracy are introduced in closed form. The stability domain of RKG polynomials extends in the the real direction with the square of polynomial…

Numerical Analysis · Mathematics 2019-04-22 Stephen O'Sullivan

This paper explores the problem of selecting sensor nodes for a general class of nonlinear dynamical networks. In particular, we study the problem by utilizing altered definitions of observability and open-loop lifted observers. The…

Systems and Control · Electrical Eng. & Systems 2023-07-17 Mohamad H. Kazma , Sebastian A. Nugroho , Aleksandar Haber , Ahmad F. Taha

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

Maximum bound principle (MBP) is an important property for a large class of semilinear parabolic equations, in the sense that the time-dependent solution of the equation with appropriate initial and boundary conditions and nonlinear…

Numerical Analysis · Mathematics 2021-04-21 Jingwei Li , Xiao Li , Lili Ju , Xinlong Feng

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