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A mixed accuracy framework for Runge--Kutta methods presented in [Grant, JSC 2022] has been shown to speed up the computation in diagonally implicit Runge--Kutta (DIRK) methods by using less expensive low accuracy approaches for the…

Numerical Analysis · Mathematics 2026-04-29 John Driscoll , Sigal Gottlieb , Zachary J. Grant , César Herrera , Tej Sai Kakumanu , Monica Stephens

In this note we discuss the construction of high order asymptotic preserving numerical schemes for the Boltzmann equation. The methods are based on the use of Implicit-Explicit (IMEX) Runge-Kutta methods combined with a penalization…

Numerical Analysis · Mathematics 2012-02-24 Giacomo Dimarco , Lorenzo Pareschi

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

A class of explicit pseudo two-step Runge-Kutta-Nystr\"{o}m (GEPTRKN) methods for solving second-order initial value problems $y'' = f(t,y,y')$, $y(t_0) = y_0$, $y'(t_0)=y'_0$ has been studied. This new class of methods can be considered a…

Numerical Analysis · Mathematics 2022-07-19 Nguyen S. Hoang

In this paper we consider splitting methods for nonlinear ordinary differential equations in which one of the (partial) flows that results from the splitting procedure can not be computed exactly. Instead, we insert a well-chosen state…

Numerical Analysis · Mathematics 2014-05-27 Lukas Einkemmer , Alexander Ostermann

Two fluid configurations along a flow are conjugate if there is a one parameter family of geodesics (fluid flows) joining them to infinitesimal order. Geometrically, they can be seen as a consequence of the (infinite dimensional) group of…

Analysis of PDEs · Mathematics 2021-05-26 Theodore D. Drivas , Gerard Misiołek , Bin Shi , Tsuyoshi Yoneda

Optimal Strong Stability Preserving (SSP) Runge--Kutta methods has been widely investegated in the last decade and many open conjectures have been formulated. The iterated implicit midpoint rule has been observed numerically optimal in…

Numerical Analysis · Mathematics 2014-10-01 Tihamér A. Kocsis , Adrián Németh

The theory of persistence modules is an emerging field of algebraic topology which originated in topological data analysis. In these notes we provide a concise introduction into this field and give an account on some of its interactions…

Algebraic Topology · Mathematics 2021-01-26 Leonid Polterovich , Daniel Rosen , Karina Samvelyan , Jun Zhang

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

Semi-discrete Runge-Kutta schemes for nonlinear diffusion equations of parabolic type are analyzed. Conditions are determined under which the schemes dissipate the discrete entropy locally. The dissipation property is a consequence of the…

Numerical Analysis · Mathematics 2015-06-24 Ansgar Jüngel , Stefan Schuchnigg

Symplectic quantization is a functional approach to quantum field theory that allows sampling of quantum fluctuations directly in Minkowski space-time by means of a generalized microcanonical ensemble similar to the one of the standard…

High Energy Physics - Theory · Physics 2026-05-26 Martina Giachello , Francesco Scardino , Giacomo Gradenigo

A universal symplectic structure for a Newtonian system including nonconservative cases can be constructed in the framework of Birkhoffian generalization of Hamiltonian mechanics. In this paper the symplectic geometry structure of…

Mathematical Physics · Physics 2018-01-17 Hongling Su , Mengzhao Qin

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

In this paper, inspired by the idea that the hub nodes of a highly heterogeneous network are not only the bottlenecks, but also effective controllers in the network synchronizing process, we bring forward an asymmetrical coupling method…

Statistical Mechanics · Physics 2009-11-11 Ming Zhao , Tao Zhou , Bing-Hong Wang , Qing Ou , Jie Ren

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 compare the performances of symplectic and non-symplectic integrators for the computation of normal geodesics and conjugate points in sub-Riemannian geometry at the example of the Martinet case. For this case study we consider first the…

Numerical Analysis · Mathematics 2007-05-23 Monique Chyba , Ernst Hairer , Gilles Vilmart

This paper is devoted to the numerical symplectic approximation of the charged-particle dynamics (CPD) with arbitrary electromagnetic fields. By utilizing continuous-stage methods and exponential integrators, a general class of symplectic…

Numerical Analysis · Mathematics 2022-07-05 Ting Li , Bin Wang

Hamilton's equations of motion form a fundamental framework in various branches of physics, including astronomy, quantum mechanics, particle physics, and climate science. Classical numerical solvers are typically employed to compute the…

Machine Learning · Computer Science 2024-10-25 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

In this paper, we investigate the asymptotic error distributions of symplectic methods for stochastic Hamiltonian systems and further provide Hamiltonian-specific analysis that clarifies the superiority of symplectic methods. Our…

Numerical Analysis · Mathematics 2025-12-04 Chuchu Chen , Xinyu Chen , Jialin Hong , Yuqian Miao

In this paper, we consider the asymptotical regularization with convex constraints for nonlinear ill-posed problems. The method allows to use non-smooth penalty terms, including the L1-like and the total variation-like penalty functionals,…

Numerical Analysis · Mathematics 2022-03-23 Min Zhong , Wei Wang
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