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We investigate the computational performance of various numerical methods for the integration of the equations of motion and the variational equations for some typical classical many-body models of condensed matter physics: the…

Computational Physics · Physics 2019-05-07 Carlo Danieli , Bertin Many Manda , Mithun Thudiyangal , Charalampos Skokos

In this work, we introduce high-order Basis-Update & Galerkin (BUG) integrators based on explicit Runge-Kutta methods for large-scale matrix differential equations. These dynamical low-rank integrators extend the BUG integrator to arbitrary…

Numerical Analysis · Mathematics 2026-01-27 Fabio Nobile , Sébastien Riffaud

High order energy-preserving methods for Hamiltonian systems are presented. For this aim, an energy-preserving condition of continuous stage Runge--Kutta methods is proved. Order conditions are simplified and parallelizable conditions are…

Numerical Analysis · Mathematics 2016-11-08 Yuto Miyatake , John C. Butcher

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

This paper studies the Craig variant of the Golub-Kahan bidiagonalization algorithm as an iterative solver for linear systems with saddle point structure. Such symmetric indefinite systems in 2x2 block form arise in many applications, but…

Computational Engineering, Finance, and Science · Computer Science 2018-08-24 Mario Arioli , Carola Kruse , Ulrich Ruede , Nicolas Tardieu

We introduce a class of fourth order symplectic algorithms that are ideal for doing long time integration of gravitational few-body problems. These algorithms have only positive time steps, but require computing the force gradient in…

Astrophysics · Physics 2007-05-23 Siu A. Chin , C. R. Chen

In the numerical solution of partial differential equations using a method-of-lines approach, the availability of high order spatial discretization schemes motivates the development of sophisticated high order time integration methods. For…

Numerical Analysis · Computer Science 2016-11-25 Hong Zhang , Adrian Sandu , Sebastien Blaise

Optimization tasks are crucial in statistical machine learning. Recently, there has been great interest in leveraging tools from dynamical systems to derive accelerated and robust optimization methods via suitable discretizations of…

Statistical Mechanics · Physics 2023-07-06 Guilherme França , Alessandro Barp , Mark Girolami , Michael I. Jordan

Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustness and stability of computational methods in such systems is…

Quantum Physics · Physics 2025-02-25 Hsuan-Cheng Wu , Xiantao Li

A novel class of Runge-Kutta discontinuous Galerkin schemes for coupled systems of conservation laws in multiple space dimensions that are separated by a fixed sharp interface is introduced. The schemes are derived from a relaxation…

Numerical Analysis · Mathematics 2026-01-19 Niklas Kolbe , Siegfried Müller , Aleksey Sikstel

Symplectic integration methods based on operator splitting are well established in many branches of science. For Hamiltonian systems which split in more than two parts, symplectic methods of higher order have been studied in detail only for…

A standard approach to solve ordinary differential equations, when they describe dynamical systems, is to adopt a Runge-Kutta or related scheme. Such schemes, however, are not applicable to the large class of equations which do not…

Fluid Dynamics · Physics 2024-04-11 Divya Jaganathan , Rama Govindarajan , Vishal Vasan

In this paper, we study symplectic integration of canonical Hamiltonian systems with Jacobi polynomials. The relevant theoretical results of continuous-stage Runge-Kutta methods are revisited firstly and then symplectic methods with Jacobi…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

Finite element methods provide accurate and efficient methods for the numerical solution of partial differential equations by means of restricting variational problems to finite-dimensional approximating spaces. However, they do not…

Numerical Analysis · Mathematics 2025-06-24 Robert C. Kirby , John D. Stephens

This letter studies symmetric and symplectic exponential integrators when applied to numerically computing nonlinear Hamiltonian systems. We first establish the symmetry and symplecticity conditions of exponential integrators and then show…

Numerical Analysis · Mathematics 2018-12-11 Yajun Wu , Bin Wang

We have shown previously that functionally fitted Runge-Kutta (FRK) methods can be studied using a convenient collocation framework. Here, we extend that framework to functionally fitted Runge-Kutta-Nystr\"om (FRKN) methods, shedding…

Numerical Analysis · Mathematics 2014-10-17 N. S. Hoang , R. B. Sidje

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

In this article, a unified approach to obtain symplectic integrators on T*G from Lie group integrators on a Lie group G is presented. The approach is worked out in detail for symplectic integrators based on Runge--Kutta--Munthe-Kaas methods…

Numerical Analysis · Mathematics 2014-04-24 Geir Bogfjellmo , Håkon Marthinsen

Extended Stability Runge-Kutta (ESRK) methods are crucial for solving large-scale computational problems in science and engineering, including weather forecasting, aerodynamic analysis, and complex biological modelling. However, balancing…

Machine Learning · Computer Science 2025-06-27 Gavin Lee Goodship , Luis Miralles-Pechuan , Stephen O'Sullivan

Constructing explicit Runge--Kutta (ERK) methods with as few stages as possible for a given order is a classical problem in numerical analysis. In this work, we introduce a $Q$/$D$-space framework of sufficient order conditions for ERK…

Numerical Analysis · Mathematics 2026-05-19 Junyuan He , Jizu Huang
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