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Cell collective migration plays a crucial role in a variety of physiological processes. In this work, we propose the Runge-Kutta random feature method to solve the nonlinear and strongly coupled multiphase flow problems of cells, in which…

Numerical Analysis · Mathematics 2024-12-10 Yangtao Deng , Qiaolin He

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

We consider the efficient numerical solution of coupled dynamical systems, consisting of a small nonlinear part and a large linear time invariant part, possibly stemming from spatial discretization of an underlying partial differential…

Numerical Analysis · Mathematics 2018-11-27 Herbert Egger , Vsevolod Shashkov , Kersten Schmidt

The recently-introduced relaxation approach for Runge-Kutta methods can be used to enforce conservation of energy in the integration of Hamiltonian systems. We study the behavior of implicit and explicit relaxation Runge-Kutta methods in…

Numerical Analysis · Mathematics 2020-07-13 Hendrik Ranocha , David I. Ketcheson

Tree tensor networks (TTNs) provide a compact and structured representation of high-dimensional data, making them valuable in various areas of computational mathematics and physics. In this paper, we present a rigorous mathematical…

Numerical Analysis · Mathematics 2026-04-28 Junyuan He , Zhonghao Sun , Jizu Huang

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

Space discretization of some time-dependent partial differential equations gives rise to systems of ordinary differential equations in additive form whose terms have different stiffness properties. In these cases, implicit methods should be…

Numerical Analysis · Mathematics 2015-10-02 Inmaculada Higueras , Teo Roldán

A unified theoretical framework is suggested to examine the energy dissipation properties at all stages of additive implicit-explicit Runge-Kutta (IERK) methods up to fourth-order accuracy for gradient flow problems. We construct some…

Numerical Analysis · Mathematics 2024-10-10 Hong-lin Liao , Xuping Wang , Cao Wen

We apply the concept of effective order to strong stability preserving (SSP) explicit Runge-Kutta methods. Relative to classical Runge-Kutta methods, methods with an effective order of accuracy are designed to satisfy a relaxed set of order…

Numerical Analysis · Mathematics 2014-01-09 Yiannis Hadjimichael , Colin B. Macdonald , David I. Ketcheson , James H. Verner

We propose a new probabilistic scheme which combines deep learning techniques with high order schemes for backward stochastic differential equations belonging to the class of Runge-Kutta methods to solve high-dimensional semi-linear…

Numerical Analysis · Mathematics 2023-01-02 Jean-François Chassagneux , Junchao Chen , Noufel Frikha

Runge-Kutta methods are the classic family of solvers for ordinary differential equations (ODEs), and the basis for the state of the art. Like most numerical methods, they return point estimates. We construct a family of probabilistic…

Machine Learning · Statistics 2014-10-27 Michael Schober , David Duvenaud , Philipp Hennig

We develop Chebyshev symplectic methods based on Chebyshev orthogonal polynomials of the first and second kind separately in this paper. Such type of symplectic methods can be conveniently constructed with the newly-built theory of weighted…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

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

For the approximation of solutions for stochastic partial differential equations, numerical methods that obtain a high order of convergence and at the same time involve reasonable computational cost are of particular interest. We therefore…

Numerical Analysis · Mathematics 2024-12-12 Claudine von Hallern , Ricarda Mißfeldt , Andreas Rößler

In this paper we define an efficient implementation of Runge-Kutta methods of Radau IIA type, which are commonly used when solving stiff ODE-IVPs problems. The proposed implementation relies on an alternative low-rank formulation of the…

Numerical Analysis · Mathematics 2024-07-18 L. Brugnano , F. Iavernaro , C. Magherini

This work constructs the first-ever sixth-order exponential Runge--Kutta (ExpRK) methods for the time integration of stiff parabolic PDEs. First, we leverage the exponential B-series theory to restate the stiff order conditions for ExpRK…

Numerical Analysis · Mathematics 2024-02-28 Vu Thai Luan , Trky Alhsmy

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

This work constructs and analyzes new efficient high-order two-derivative diagonally implicit Runge--Kutta (TDDIRK) schemes with optimized phase errors. Specifically, we present a convergence result for TDDIRK methods and investigate their…

Numerical Analysis · Mathematics 2025-12-18 Julius Ehigie , Vu Thai Luan

A novel optimization procedure for the generation of stability polynomials of stabilized explicit Runge-Kutta methods is devised. Intended for semidiscretizations of hyperbolic partial differential equations, the herein developed approach…

Numerical Analysis · Mathematics 2024-03-19 Daniel Doehring , Gregor J. Gassner , Manuel Torrilhon
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