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We study the application of the generalized convolution quadrature (gCQ) based on Runge--Kutta methods to approximate the solution of an important class of sectorial problems. The gCQ generalizes Lubich's original convolution quadrature…

Numerical Analysis · Mathematics 2025-06-27 Jing Guo , Maria Lopez-Fernandez

We propose a new Eulerian-Lagrangian Runge-Kutta finite volume method for numerically solving convection and convection-diffusion equations. Eulerian-Lagrangian and semi-Lagrangian methods have grown in popularity mostly due to their…

Numerical Analysis · Mathematics 2022-10-05 Joseph Nakao , Jiajie Chen , Jingmei Qiu

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 survey a QMC approach to integral equations and develop some new applications to risk modeling. In particular, a rigorous error bound derived from Koksma-Hlawka type inequalities is achieved for certain expectations related to the…

Probability · Mathematics 2017-07-13 Michael Preischl , Stefan Thonhauser , Robert F. Tichy

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

In this paper a new Runge-Kutta type scheme is introduced for nonlinear stochastic partial differential equations (SPDEs) with multiplicative trace class noise. The proposed scheme converges with respect to the computational effort with a…

Numerical Analysis · Mathematics 2012-04-03 Xiaojie Wang , Siqing Gan

A practical and new Runge--Kutta numerical scheme for stochastic differential equations is explored. Numerical examples demonstrate the strong convergence of the method. The first order strong convergence is then proved using Ito integrals…

Numerical Analysis · Mathematics 2012-10-04 A. J. Roberts

In this paper, authors successfully construct a new algorithm for the new higher order scheme of weak approximation of SDEs. The algorithm presented here is based on [1][2]. Although this algorithm shares some features with the algorithm…

Probability · Mathematics 2025-04-28 Mariko Ninomiya , Syoiti Ninomiya

Applied to the master equation, the usual numerical integration methods, such as Runge-Kutta, become inefficient when the rates associated with various transitions differ by several orders of magnitude. We introduce an integration scheme…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman

In this paper we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for…

Numerical Analysis · Mathematics 2014-01-31 Tomasz M. Tyranowski , Mathieu Desbrun

We analyze the probability of ruin for the {\it scaled} classical Cram\'er-Lundberg (CL) risk process and the corresponding diffusion approximation. The scaling, introduced by Iglehart \cite{I1969} to the actuarial literature, amounts to…

Optimization and Control · Mathematics 2020-06-18 Asaf Cohen , Virginia R. Young

In this paper, we investigate the ruin probabilities of non-homogeneous risk models. By employing martingale method, the Lundberg-type inequalities of ruin probabilities of non-homogeneous renewal risk models are obtained under weak…

Probability · Mathematics 2020-06-05 Qianqian Zhou , Alexander Sakhanenko , Junyi Guo

We apply Runge-Kutta methods to linear partial differential-algebraic equations of the form $Au_t(t,x) + B(u_{xx}(t,x)+ru_x(t,x))+Cu(t,x) = f(t,x)$, where $A,B,C\in\R^{n,n}$ and the matrix $A$ is singular. We prove that under certain…

Numerical Analysis · Mathematics 2013-03-19 Kristian Debrabant , Karl Strehmel

An error analysis is presented for explicit partitioned Runge-Kutta methods and multirate methods applied to conservation laws. The interfaces, across which different methods or time steps are used, lead to order reduction of the schemes.…

Numerical Analysis · Mathematics 2013-10-29 Willem Hundsdorfer , David I. Ketcheson , Igor Savostianov

Symplectic partitioned Runge--Kutta methods can be obtained from a variational formulation where all the terms in the discrete Lagrangian are treated with the same quadrature formula. We construct a family of symplectic methods allowing the…

Numerical Analysis · Mathematics 2019-09-25 Antonella Zanna

We develop continuous-stage Runge-Kutta methods based on weighted orthogonal polynomials in this paper. There are two main highlighted merits for developing such methods: Firstly, we do not need to study the tedious solution of…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

This paper studies a family of convolution quadratures, a numerical technique for efficient evaluation of convolution integrals. We employ the block generalized Adams method to discretize the underlying initial value problem, departing from…

Numerical Analysis · Mathematics 2024-07-11 Ling Liu , Junjie Ma

We present a C++ implementation of a fifth order semi-implicit Runge-Kutta algorithm for solving Ordinary Differential Equations. This algorithm can be used for studying many different problems and in particular it can be applied for…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 P. Aliani , V. Antonelli , M. Picariello , Emilio Torrente-Lujan

A semi-implicit-explicit (semi-IMEX) Runge-Kutta (RK) method is proposed for the numerical integration of ordinary differential equations (ODEs) of the form $\mathbf{u}' = \mathbf{f}(t,\mathbf{u}) + G(t,\mathbf{u}) \mathbf{u}$, where…

Numerical Analysis · Mathematics 2025-04-15 Lingyun Ding

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