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In a recent work of Wu, Wang, Sun and Liu, a second-order explicit symplectic integrator was proposed for the integrable Kerr spacetime geometry. It is still suited for simulating the nonintegrable dynamics of charged particles moving…

General Relativity and Quantum Cosmology · Physics 2021-09-07 Wei Sun , Ying Wang , Fuyao Liu , Xin Wu

A recently proposed method for computer simulations in the isothermal-isobaric (NPT) ensemble, based on Langevin-type equations of motion for the particle coordinates and the ``piston'' degree of freedom, is re-derived by straightforward…

Soft Condensed Matter · Physics 2016-08-31 A. Kolb , B. Duenweg

The aim of this series of two papers is to discuss topological invariants for interacting topological insulators (TIs). In the first paper (I), we provide a paradigm of efficient numerical evaluation scheme for topological invariants, in…

Strongly Correlated Electrons · Physics 2016-06-08 Yuan-Yao He , Han-Qing Wu , Zi Yang Meng , Zhong-Yi Lu

An explicit second-order numerical method to integrate the isokinetic equations of motion is derived by fitting circular arcs through every three consecutive points of the discretized trajectory, so that the tangent and the curvature…

Chemical Physics · Physics 2018-11-01 Dimitri Laikov

We introduce two numerical conjugacy invariants for dynamical systems -- the complexity and weak complexity indices -- which are well-suited for the study of "completely integrable" Hamiltonian systems. These invariants can be seen as "slow…

Dynamical Systems · Mathematics 2009-07-31 Jean-Pierre Marco

Stochastic Hamiltonian partial differential equations, which possess the multi-symplectic conservation law, are an important and fairly large class of systems. The multi-symplectic methods inheriting the geometric features of stochastic…

Numerical Analysis · Mathematics 2022-08-10 Jialin Hong , Baohui Hou , Qiang Li , Liying Sun

Gaussian wavepacket dynamics has proven to be a useful semiclassical approximation for quantum simulations of high-dimensional systems with low anharmonicity. Compared to Heller's original local harmonic method, the variational Gaussian…

Numerical Analysis · Mathematics 2024-09-26 Roya Moghaddasi Fereidani , Jiří JL Vaníček

We devote our studies to the subject of weakly nonintegrable dynamics of systems with a macroscopic number of degrees of freedom. Our main points of interest are the relations between the timescales of thermalization and the timescales of…

Chaotic Dynamics · Physics 2022-11-04 Merab Malishava

We introduce a class of general purpose linear multisymplectic integrators for Hamiltonian wave equations based on a diamond-shaped mesh. On each diamond, the PDE is discretized by a symplectic Runge--Kutta method. The scheme advances in…

Numerical Analysis · Mathematics 2014-02-21 R I McLachlan , M C Wilkins

In this paper we present novel integrable symplectic maps, associated with ordinary difference equations, and show how they determine, in a remarkably diverse manner, the integrability, including Lax pairs and the explicit solutions, for…

Mathematical Physics · Physics 2020-09-22 Xiaoxue Xu , Mengmeng Jiang , Frank W Nijhoff

In this paper we propose and investigate a general approach to constructing local energy-preserving algorithms which can be of arbitrarily high order in time for solving Hamiltonian PDEs. This approach is based on the temporal…

Numerical Analysis · Mathematics 2021-03-31 Yuwen Li , Xinyuan Wu

Symplectic integrators are the established standard for long-term simulations of nearly-integrable Hamiltonian systems due to their preservation of geometric structures. However, they suffer from an inherent limitation: secular phase-shift…

Numerical Analysis · Mathematics 2026-02-19 Mingwei Fu , Bin Shi

For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-energy have seen extensive investigation. Most available methods either require the iterative solution of nonlinear algebraic equations at each…

Numerical Analysis · Mathematics 2022-07-04 Stefan Bilbao , Michele Ducceschi , Fabiana Zama

In this paper, we develop a framework to construct energy-preserving methods for multi-components Hamiltonian systems, combining the exponential integrator and the partitioned averaged vector field method. This leads to numerical schemes…

Numerical Analysis · Mathematics 2021-11-08 X. Gu , C. Jiang , Y. Wang , W. Cai

The primary focus of this thesis is the numerical investigation of chaos in Hamiltonian models describing charged particle orbits in plasma, star motions in barred galaxies, and orbits' diffusion in multidimensional maps. We systematically…

Chaotic Dynamics · Physics 2025-03-24 Henok Tenaw Moges

As originally formulated, the Generalized Alignment Index (GALI) method of chaos detection has so far been applied to distinguish quasiperiodic from chaotic motion in conservative nonlinear dynamical systems. In this paper we extend its…

Chaotic Dynamics · Physics 2013-10-17 T. Manos , Ch. Skokos , Ch. Antonopoulos

In this paper, explicit stable integrators based on symplectic and contact geometries are proposed for a non-autonomous ordinarily differential equation (ODE) found in improving convergence rate of Nesterov's accelerated gradient method.…

Numerical Analysis · Mathematics 2021-06-15 Shin-itiro Goto , Hideitsu Hino

We present a new mixed variable symplectic (MVS) integrator for planetary systems, that fully resolve close encounters. The method is based on a time regularisation that allows keeping the stability properties of the symplectic integrators,…

Earth and Planetary Astrophysics · Physics 2019-07-31 Antoine C. Petit , Jacques Laskar , Gwenaël Boué , Mickaël Gastineau

Studying single-particle dynamics over many periods of oscillations is a well-understood problem solved using symplectic integration. Such integration schemes derive their update sequence from an approximate Hamiltonian, guaranteeing that…

Computational Physics · Physics 2016-03-23 Stephen D. Webb

Accelerated gradient methods have had significant impact in machine learning -- in particular the theoretical side of machine learning -- due to their ability to achieve oracle lower bounds. But their heuristic construction has hindered…

Computation · Statistics 2018-02-16 Michael Betancourt , Michael I. Jordan , Ashia C. Wilson