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This article explores some geometric and algebraic properties of the dynamical system which is represented by matrix differential equations arising from inertial navigation problems, such as the symplecticity and the orthogonality.…

Dynamical Systems · Mathematics 2020-02-12 Xin-Long Luo , Geng Sun

In this paper we develop an $hp$-adaptive procedure for the numerical solution of general, semilinear elliptic boundary value problems in 1d, with possible singular perturbations. Our approach combines both a prediction-type adaptive Newton…

Numerical Analysis · Mathematics 2018-03-07 Mario Amrein , Jens M. Melenk , Thomas P. Wihler

Symplectic numerical methods have become a widely-used choice for the accurate simulation of Hamiltonian systems in various fields, including celestial mechanics, molecular dynamics and robotics. Even though their characteristics are…

Numerical Analysis · Mathematics 2025-06-27 Donát M. Takács , Tamás Fülöp

We present and compare different numerical schemes for the integration of the variational equations of autonomous Hamiltonian systems whose kinetic energy is quadratic in the generalized momenta and whose potential is a function of the…

Chaotic Dynamics · Physics 2015-03-17 Ch. Skokos , E. Gerlach

While the construction of symplectic integrators for Hamiltonian dynamics is well understood, an analogous general theory for Poisson integrators is still lacking. The main challenge lies in overcoming the singular and non-linear geometric…

Numerical Analysis · Mathematics 2024-09-09 Alejandro Cabrera , David Martín de Diego , Miguel Vaquero

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, a kernel-based surrogate for integrating Hamiltonian dynamics that is symplectic by construction and tailored to large prediction horizons is proposed. The method learns a scalar potential whose gradient enters a…

Numerical Analysis · Mathematics 2026-01-27 Robin Herkert , Tobias Ehring , Bernard Haasdonk

Multi-derivative one-step methods based upon Euler-Maclaurin integration formulae are considered for the solution of canonical Hamiltonian dynamical systems. Despite the negative result that simplecticity may not be attained by any…

Numerical Analysis · Mathematics 2019-05-08 F. Iavernaro , F. Mazzia , M. S. Mukhametzhanov , Ya. D. Sergeyev

In previous papers, explicit symplectic integrators were designed for nonrotating black holes, such as a Schwarzschild black hole. However, they fail to work in the Kerr spacetime because not all variables can be separable, or not all…

General Relativity and Quantum Cosmology · Physics 2021-06-24 Xin Wu , Ying Wang , Wei Sun , Fuyao Liu

We study the discretization of (almost-)Dirac structures using the notion of retraction and discretization maps on manifolds. Additionally, we apply the proposed discretization techniques to obtain numerical integrators for port-Hamiltonian…

Numerical Analysis · Mathematics 2025-05-12 María Barbero-Liñán , Juan Manuel López Medel , David Martín de Diego

We report a few sumerical tests comparing some newly defined energy-preserving integrators and symplectic methods, using either constant and variable stepsize.

Numerical Analysis · Mathematics 2010-09-30 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

We propose a linearly implicit structure-preserving numerical method for semilinear Hamiltonian systems with polynomial nonlinearities, combining Kahan's method and exponential integrator. This approach efficiently balances computational…

Numerical Analysis · Mathematics 2026-03-03 Pan Zhang , Fengyang Xiao , Lu Li

We construct numerical integrators for Hamiltonian problems that may advantageously replace the standard Verlet time-stepper within Hybrid Monte Carlo and related simulations. Past attempts have often aimed at boosting the order of accuracy…

Numerical Analysis · Mathematics 2015-04-10 Sergio Blanes , Fernando Casas , J. M. Sanz-Serna

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

Symplectic integrators constructed from Hamiltonian and Lie formalisms are obtained as symplectic maps whose flow follows the exact solution of a "sourrounded" Hamiltonian K = H + h^k H_1. Those modified Hamiltonians depends virtually on…

Symplectic Geometry · Mathematics 2012-01-04 Hugo Jiménez-Pérez

The anisotropic and heterogeneous $N$-dimensional wave equation, controlled and observed at the boundary, is considered as a port-Hamiltonian system. A recent structure-preserving mixed Galerkin method is applied, leading directly to a…

Numerical Analysis · Mathematics 2022-06-01 Ghislain Haine , Denis Matignon , Anass Serhani

The modified Hunter--Saxton equation models the propagation of short capillary-gravity waves. As it involves a mixed derivative, its initial value problem on the periodic domain is much more complicated than the standard evolutionary…

Numerical Analysis · Mathematics 2018-02-13 Shun Sato

This paper proposes a general symplectic Euler scheme for a class of Hamiltonian stochastic differential equations driven by L$\acute{e}$vy noise in the sense of Marcus form. The convergence of the symplectic Euler scheme for this…

Numerical Analysis · Mathematics 2020-06-30 Qingyi Zhan , Jinqiao Duan , Xiaofan Li

The dynamic equation of mass point in rotating coordinates is governed by Coriolis and centrifugal force, besides a corotating potential relative to frame. Such a system is no longer a canonical Hamiltonian system so that the construction…

Instrumentation and Methods for Astrophysics · Physics 2022-02-09 Xiongbiao Tu , Qiao Wang , Yifa Tang

We introduce a recent symplectic integration scheme derived for solving physically motivated systems with non-separable Hamiltonians. We show its relevance to Riemannian manifold Hamiltonian Monte Carlo (RMHMC) and provide an alternative to…

Machine Learning · Statistics 2019-10-15 Adam D. Cobb , Atılım Güneş Baydin , Andrew Markham , Stephen J. Roberts