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Sampling with Markov chain Monte Carlo methods often amounts to discretizing some continuous-time dynamics with numerical integration. In this paper, we establish the convergence rate of sampling algorithms obtained by discretizing smooth…

Machine Learning · Statistics 2020-02-04 Xuechen Li , Denny Wu , Lester Mackey , Murat A. Erdogdu

This paper contains an error analysis of two randomized explicit Runge-Kutta schemes for ordinary differential equations (ODEs) with time-irregular coefficient functions. In particular, the methods are applicable to ODEs of Carath\'eodory…

Numerical Analysis · Mathematics 2017-07-13 Raphael Kruse , Yue Wu

Isospectral Runge-Kutta methods are well-suited for the numerical solution of isospectral systems such as the rigid body and the Toda lattice. More recently, these integrators have been applied to geophysical fluid models, where their…

Numerical Analysis · Mathematics 2025-06-10 Clauson Carvalho da Silva , Christian Lessig , Carlos Tomei

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. The proposed methods are based on a specific subset of explicit one-step…

Numerical Analysis · Mathematics 2019-04-16 Vu Thai Luan , Rujeko Chinomona , Daniel R. Reynolds

We consider one-step methods for integrating stochastic differential equations and prove pathwise convergence using ideas from rough path theory. In contrast to alternative theories of pathwise convergence, no knowledge is required of…

Numerical Analysis · Mathematics 2015-02-24 Tony Shardlow , Phillip Taylor

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

Many important differential equations model quantities whose value must remain positive or stay in some bounded interval. These bounds may not be preserved when the model is solved numerically. We propose to ensure positivity or other…

Numerical Analysis · Mathematics 2021-11-10 Stephan Nüßlein , Hendrik Ranocha , David I Ketcheson

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

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 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

We show that the probability of the exceptional set decays exponentially for a broad class of randomized algorithms approximating solutions of ODEs, admitting a certain error decomposition. This class includes randomized explicit and…

Numerical Analysis · Mathematics 2022-02-04 Tomasz Bochacik

We are studying Runge-Kutta methods along complex paths of integration from a geometric point of view. Thereby we derive special complex time grids, which applied to the problem of integrating a linear autonomous system of ordinary…

Numerical Analysis · Mathematics 2009-03-10 Thorsten Orendt , Jürgen Richter-Gebert , Michael Schmid

We reconsider the variational derivation of symplectic partitioned Runge-Kutta schemes. Such type of variational integrators are of great importance since they integrate mechanical systems with high order accuracy while preserving the…

Numerical Analysis · Mathematics 2015-05-08 Cédric M. Campos

In this article, a family of two- and three-stage explicit multiquadric (MQ) and inverse multiquadric (IMQ) radial basis functions (RBFs) Runge-Kutta methods are introduced for solving ordinary differential equations. These methods are…

Numerical Analysis · Mathematics 2025-09-23 Shipra Mahata , Samala Rathan

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

Classical and new numerical schemes are generated using evolutionary computing. Differential Evolution is used to find the coefficients of finite difference approximations of function derivatives, and of single and multi-step integration…

Neural and Evolutionary Computing · Computer Science 2014-01-02 C. D. Erdbrink , V. V. Krzhizhanovskaya , P. M. A. Sloot

We demonstrate the effectiveness of a novel scheme for numerically solving linear differential equations whose solutions exhibit extreme oscillation. We take a standard Runge-Kutta approach, but replace the Taylor expansion formula with a…

Computational Physics · Physics 2016-12-12 W. J. Handley , A. N. Lasenby , M. P. Hobson

In this survey, we provide an in-depth investigation of exponential Runge-Kutta methods for the numerical integration of initial-value problems. These methods offer a valuable synthesis between classical Runge-Kutta methods, introduced more…

Numerical Analysis · Mathematics 2026-04-27 Alessia andò , Nicolò Cangiotti , Mattia Sensi

Many problems in science and engineering require an efficient numerical approximation of integrals or solutions to differential equations. For systems with rapidly changing dynamics, an equidistant discretization is often inadvisable as it…

Nonlinear parabolic equations are central to numerous applications in science and engineering, posing significant challenges for analytical solutions and necessitating efficient numerical methods. Exponential integrators have recently…

Numerical Analysis · Mathematics 2024-12-24 Trung Hau Hoang