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In this work, an approximate family of implicit multiderivative Runge-Kutta (MDRK) time integrators for stiff initial value problems is presented. The approximation procedure is based on the recent Approximate Implicit Taylor method (Baeza…

Numerical Analysis · Mathematics 2023-02-07 Jeremy Chouchoulis , Jochen Schütz

We develop two new sets of stable, rank-adaptive Dynamically Orthogonal Runge-Kutta (DORK) schemes that capture the high-order curvature of the nonlinear low-rank manifold. The DORK schemes asymptotically approximate the truncated singular…

Numerical Analysis · Mathematics 2023-08-08 Aaron Charous , Pierre F. J. Lermusiaux

We put forward the use of total-variation-diminishing (or more generally, strong stability preserving) implicit-explicit Runge-Kutta methods for the time integration of the equations of motion associated with the semiconvection problem in…

Numerical Analysis · Mathematics 2012-03-09 Friedrich Kupka , Natalie Happenhofer , Inmaculada Higueras , Othmar Koch

Splitting the exponential-like $\varphi$ functions, which typically appear in exponential integrators, is attractive in many situations since it can dramatically reduce the computational cost of the procedure. However, depending on the…

Numerical Analysis · Mathematics 2025-03-21 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

Traditional time discretization methods use a single timestep for the entire system of interest and can perform poorly when the dynamics of the system exhibits a wide range of time scales. Multirate infinitesimal step (MIS) methods (Knoth…

Numerical Analysis · Mathematics 2022-02-03 Steven Roberts , Arash Sarshar , Adrian Sandu

We propose two new classes of time integrators for stiff DEs: the implicit-explicit exponential (IMEXP) and the hybrid exponential methods. In contrast to the existing exponential schemes, the new methods offer significant computational…

Numerical Analysis · Mathematics 2016-05-11 Vu Thai Luan , Mayya Tokman , Greg Rainwater

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

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. Unlike other recent work in this area, the proposed methods support mixed…

Numerical Analysis · Mathematics 2023-01-04 Rujeko Chinomona , Daniel R. Reynolds

This work generalizes the additively partitioned Runge-Kutta methods by allowing for different stage values as arguments of different components of the right hand side. An order conditions theory is developed for the new family of…

Numerical Analysis · Computer Science 2013-10-22 Adrian Sandu , Michael Guenther

This paper studies diagonal implicit symplectic extended Runge--Kutta--Nystr\"{o}m (ERKN) methods for solving the oscillatory Hamiltonian system $H(q,p)=\dfrac{1}{2}p^{T}p+\dfrac{1}{2}q^{T}Mq+U(q)$. Based on symplectic conditions and order…

Numerical Analysis · Mathematics 2017-12-04 Mingxue Shi , Hao Zhang , Bin Wang

The primary objective of this paper is to present a long-term numerical energy-preserving analysis of one-stage explicit symmetric and/or symplectic extended Runge--Kutta--Nystr\"{o}m (ERKN) integrators for highly oscillatory Hamiltonian…

Numerical Analysis · Mathematics 2018-06-26 Bin Wang , Xinyuan Wu

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 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

In this paper, Runge-Kutta-Gegenbauer (RKG) stability polynomials of arbitrarily high order of accuracy are introduced in closed form. The stability domain of RKG polynomials extends in the the real direction with the square of polynomial…

Numerical Analysis · Mathematics 2019-04-22 Stephen O'Sullivan

We introduce a new technique for the simulation of dissipative quantum systems. This method is composed of an approximate decomposition of the Lindblad equation into a Kraus map, from which one can define an ensemble of wavefunctions. Using…

Quantum Physics · Physics 2021-01-13 Gerard McCaul , Kurt Jacobs , Denys I. Bondar

The numerical integration of stiff equations is a challenging problem that needs to be approached by specialized numerical methods. Exponential integrators form a popular class of such methods since they are provably robust to stiffness and…

Numerical Analysis · Mathematics 2024-05-15 Benjamin Carrel , Bart Vandereycken

We present a novel numerical routine (oscode) with a C++ and Python interface for the efficient solution of one-dimensional, second-order, ordinary differential equations with rapidly oscillating solutions. The method is based on a…

Computational Physics · Physics 2020-01-10 F. J. Agocs , W. J. Handley , A. N. Lasenby , M. P. Hobson

Runge--Kutta (RK) methods are widely used techniques for solving a class of initial value problems. In this article, we introduce an adaptive multiquadratic (MQ) radial basis function (RBF)-based method to develop enhanced explicit RK…

Numerical Analysis · Mathematics 2025-07-08 Rajesh Yadav , Deepak Kumar Yadav , Alpesh Kumar

In this paper, we propose a $\mu$-mode integrator for computing the solution of stiff evolution equations. The integrator is based on a $d$-dimensional splitting approach and uses exact (usually precomputed) one-dimensional matrix…

Numerical Analysis · Mathematics 2022-02-09 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann , Franco Zivcovich

Probabilistic solvers provide a flexible and efficient framework for simulation, uncertainty quantification, and inference in dynamical systems. However, like standard solvers, they suffer performance penalties for certain stiff systems,…

Numerical Analysis · Mathematics 2023-12-20 Nathanael Bosch , Philipp Hennig , Filip Tronarp