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Runge-Kutta methods are a popular class of numerical methods for solving ordinary differential equations. Every Runge-Kutta method is characterized by two basic parameters: its order, which measures the accuracy of the solution it produces,…

Numerical Analysis · Mathematics 2019-11-04 David K. Zhang

This paper investigates the competitiveness of semi-implicit Runge-Kutta (RK) and spectral deferred correction (SDC) time-integration methods up to order six for incompressible Navier-Stokes problems in conjunction with a high-order…

Numerical Analysis · Mathematics 2022-10-03 Montadhar Guesmi , Martina Grotteschi , Jörg Stiller

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

High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The…

Numerical Analysis · Mathematics 2014-03-27 Sigal Gottlieb , Zachary J. Grant , Daniel Higgs

The Butcher theory provides a powerful tool for analyzing order conditions of Runge-Kutta schemes for ordinary differential equations (ODEs); however, such a theory has not yet been well established for backward stochastic differential…

Numerical Analysis · Mathematics 2026-05-26 Shuixin Fang , Yue Qiu , Weidong Zhao

CholeskyQR2 and shifted CholeskyQR3 are two state-of-the-art algorithms for computing tall-and-skinny QR factorizations since they attain high performance on current computer architectures. However, to guarantee stability, for some…

Numerical Analysis · Mathematics 2025-09-17 Andrew J. Higgins , Daniel B. Szyld , Erik G. Boman , Ichitaro Yamazaki

We present a new method for developing time step controllers based on a technique from the field of machine learning. This method is applicable to stable time integrators that have an embedded scheme, i.e., that have local error estimation…

Numerical Analysis · Mathematics 2025-12-23 Thomas Izgin , Hendrik Ranocha

Integration of Ordinary Differential Equations (ODEs) using Backward Difference formula (BDF) methods with p backward steps achieves order p accuracy if specific conditions are met. This work extends the composition technique with complex…

Numerical Analysis · Mathematics 2026-05-11 Ahmad Deeb , Denys Dutykh , Maryam Al Zohbi

Runge-Kutta (RK) methods may exhibit order reduction when applied to certain stiff problems. While fully implicit RK schemes exist that avoid order reduction via high-stage order, DIRK (diagonally implicit Runge-Kutta) schemes are…

Numerical Analysis · Mathematics 2023-05-31 Abhijit Biswas , David Ketcheson , Benjamin Seibold , David Shirokoff

In this paper, we construct explicit nonstandard Runge-Kutta (ENRK) methods which have higher accuracy order and preserve two important properties of autonomous dynamical systems, namely, the positivity and linear stability. These methods…

Numerical Analysis · Mathematics 2017-10-05 Quang A Dang , Manh Tuan Hoang

Floquet multipliers (characteristic multipliers) play significant role in the stability of the periodic equations. Based on the iterative method, we provide a unified algorithm to compute the Floquet multipliers (characteristic multipliers)…

Classical Analysis and ODEs · Mathematics 2022-11-03 Mengda Wu , Yonghui Xia , Ziyi Xu

In this work modified Patankar-Runge-Kutta (MPRK) schemes up to order four are considered and equipped with a dense output formula of appropriate accuracy. Since these time integrators are conservative and positivity preserving for any time…

Numerical Analysis · Mathematics 2025-01-24 Thomas Izgin

This paper proposes a new second-order symmetric algorithm for solving decoupled forward-backward stochastic differential equations. Inspired by the alternating direction implicit splitting method for partial differential equations, we…

Numerical Analysis · Mathematics 2026-01-16 Wenbo Wang , Guangyan Jia

We study the convergence of a class of Runge-Kutta type schemes for backward stochastic differential equations (BSDEs) in a Markovian framework. The schemes belonging to the class under consideration benefit from a certain stability…

Probability · Mathematics 2014-03-24 Jean-François Chassagneux , Dan Crisan

In this paper, we introduce second order and fourth order space discretization via finite difference implementation of the finite element method for solving Fokker-Planck equations associated with irreversible processes. The proposed…

Numerical Analysis · Mathematics 2023-10-12 Chen Liu , Yuan Gao , Xiangxiong Zhang

Our main objective in this paper is to develop a second-order stochastic numerical method which generalizes the well-known deterministic TR-BDF2 scheme. Since most stochastic techniques used for approximating the solution of a stochastic…

Numerical Analysis · Mathematics 2026-02-12 Tomás Caraballo , Macarena Gómez-Mármol , Ignacio Roldán

In this paper, exponential Runge-Kutta methods of collocation type (ERKC) which were originally proposed in (Appl Numer Math 53:323-339, 2005) are extended to semilinear parabolic problems with time-dependent delay. Two classes of the ERKC…

Numerical Analysis · Mathematics 2025-12-30 Qiumei Huang , Alexander Ostermann , Gangfan Zhong

We provide a new theoretical framework for the variable-step deferred correction (DC) methods based on the well-known BDF2 formula. By using the discrete orthogonal convolution kernels, some high-order BDF2-DC methods are proven to be…

Numerical Analysis · Mathematics 2024-02-12 Jiahe Yue , Hong-lin Liao , Nan Liu

Multirate integration is an increasingly relevant tool that enables scientists to simulate multiphysics systems. Existing multirate methods are designed for equations whose fast and slow variables can be linearly separated using additive or…

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

The Kubo formula is a cornerstone in our understanding of near-equilibrium transport phenomena. While conceptually elegant, the application of Kubo's linear-response theory to interesting problems is hindered by the need for algorithms that…

Mesoscale and Nanoscale Physics · Physics 2024-02-20 Santiago Giménez de Castro , João M. Viana Parente Lopes , Aires Ferreira , D. A. Bahamon