English
Related papers

Related papers: Symmetric Partitioned Runge-Kutta Methods for Diff…

200 papers

We generalize the idea of relaxation time stepping methods in order to preserve multiple nonlinear conserved quantities of a dynamical system by projecting along directions defined by multiple time stepping algorithms. Similar to the…

Numerical Analysis · Mathematics 2023-02-13 Abhijit Biswas , David I. Ketcheson

This paper is devoted to examining the stability of Runge-Kutta methods for solving nonlinear Volterra delay-integro-differential-algebraic equations (DIDAEs) with constant delay. Hybrid numerical schemes combining Runge-Kutta methods and…

Numerical Analysis · Mathematics 2025-08-19 Gehao Wang , Yuexin Yu

Simulation-based techniques such as variants of stochastic Runge-Kutta are the de facto approach for inference with stochastic differential equations (SDEs) in machine learning. These methods are general-purpose and used with parametric and…

Machine Learning · Computer Science 2021-11-01 Arno Solin , Ella Tamir , Prakhar Verma

A fourth-order exponential time differencing (ETD) Runge-Kutta scheme with dimensional splitting is developed to solve multidimensional non-linear systems of reaction-diffusion equations (RDE). By approximating the matrix exponential in the…

Numerical Analysis · Mathematics 2024-03-25 E. O. Asante-Asamani , A. Kleefeld , B. A. Wade

This paper introduces a novel paradigm for constructing linearly implicit and high-order unconditionally energy-stable schemes for general gradient flows, utilizing the scalar auxiliary variable (SAV) approach and the additive Runge-Kutta…

Numerical Analysis · Mathematics 2023-07-11 Xuelong Gu , Wenjun Cai , Yushun Wang

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

Based on the combinatory theory of rooted colored trees, we investigate the conditions for the explicit stochastic Runge-Kutta (SRK) methods to preserve quadratic invariants (QI) up to certain orders of accuracy. These conditions can supply…

Numerical Analysis · Mathematics 2014-10-24 Jialin Hong , Lijin Wang , Dongsheng Xu , Liying Zhang

Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were proposed and analyzed in 4. These specially designed methods use reduced precision for the implicit computations and full…

Numerical Analysis · Mathematics 2022-12-23 Ben Burnett , Sigal Gottlieb , Zachary J. Grant

The residual-based variational multiscale (VMS) formulation has achieved remarkable success in large-eddy simulation of turbulent flows. However, its temporal discretization has largely remained limited to second-order implicit schemes. The…

Fluid Dynamics · Physics 2025-12-09 Yujie Sun , Chi Ding , Ju Liu

A new Runge-Kutta-Nystr\"om method, with phase-lag of order infinity, for the integration of second-order periodic initial-value problems is developed in this paper. The new method is based on the Dormand and Prince Runge-Kutta-Nystr\"om…

Numerical Analysis · Mathematics 2015-05-13 D. F. Papadopoulos , Z. A. Anastassi , T. E. Simos

A high-order accurate adjoint-based optimization framework is presented for unsteady multiphysics problems. The fully discrete adjoint solver relies on the high-order, linearly stable, partitioned solver introduced in [1], where different…

Numerical Analysis · Mathematics 2019-01-01 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr

Systems driven by multiple physical processes are central to many areas of science and engineering. Time discretization of multiphysics systems is challenging, since different processes have different levels of stiffness and characteristic…

Numerical Analysis · Mathematics 2022-01-19 Adrian Sandu , Michael Günther , Steven Roberts

Ordinary differential equations (ODEs) and ordinary difference systems (O$\Delta$Ss) invariant under the actions of the Lie groups $\mathrm{SL}_x(2)$, $\mathrm{SL}_y(2)$ and $\mathrm{SL}_x(2)\times\mathrm{SL}_y(2)$ of projective…

Mathematical Physics · Physics 2016-01-20 Rutwig Campoamor-Stursberg , Miguel A. Rodríguez , Pavel Winternitz

We analyze composition methods with complex coefficients exhibiting the so-called ``symmetry-conjugate'' pattern in their distribution. In particular, we study their behavior with respect to preservation of qualitative properties when…

Numerical Analysis · Mathematics 2021-01-12 Sergio Blanes , Fernando Casas , Philippe Chartier , Alejandro Escorihuela-Tomàs

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 paper, we present a novel class of high-order Runge--Kutta (RK) discontinuous Galerkin (DG) schemes for hyperbolic conservation laws. The new method extends beyond the traditional method of lines framework and utilizes…

Numerical Analysis · Mathematics 2024-02-26 Qifan Chen , Zheng Sun , Yulong Xing

The existing discrete variational derivative method is only second-order accurate and fully implicit. In this paper, we propose a framework to construct an arbitrary high-order implicit (original) energy stable scheme and a second-order…

Numerical Analysis · Mathematics 2022-10-24 Jizu Huang

We present the formulation and optimization of a Runge-Kutta-type time-stepping scheme for solving the shallow water equations, aimed at substantially increasing the effective allowable time-step over that of comparable methods. This…

Numerical Analysis · Mathematics 2023-12-27 Jeremy R. Lilly , Darren Engwirda , Giacomo Capodaglio , Robert L. Higdon , Mark R. Petersen

In this paper we consider splitting methods for the time integration of parabolic and certain classes of hyperbolic partial differential equations, where one partial flow can not be computed exactly. Instead, we use a numerical…

Numerical Analysis · Mathematics 2017-01-06 Lukas Einkemmer , Alexander Ostermann

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
‹ Prev 1 8 9 10 Next ›