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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

We show that symplectic Runge-Kutta methods provide effective symplectic integrators for Hamiltonian systems with index one constraints. These include the Hamiltonian description of variational problems subject to position and velocity…

Numerical Analysis · Mathematics 2014-02-28 Robert I McLachlan , Klas Modin , Olivier Verdier , Matt Wilkins

We present a method for explicit leapfrog integration of inseparable Hamiltonian systems by means of an extended phase space. A suitably defined new Hamiltonian on the extended phase space leads to equations of motion that can be…

Numerical Analysis · Mathematics 2015-06-23 Pauli Pihajoki

We extend the results of planetary formation synthesis by computing the long-term evolution of synthetic systems from the clearing of the gas disk into the dynamical evolution phase. We use the symplectic integrator SyMBA to numerically…

Earth and Planetary Astrophysics · Physics 2015-06-24 S. Pfyffer , Y. Alibert , W. Benz , D. Swoboda

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

This article considers Hamiltonian mechanical systems with potential functions admitting jump discontinuities. The focus is on accurate and efficient numerical approximations of their solutions, which will be defined via the laws of…

Numerical Analysis · Mathematics 2022-01-05 Molei Tao , Shi Jin

We investigate the performance of various methods of symplectic integration, which are based on two part splitting of the integration operator, for the numerical integration of multidimensional Hamiltonian systems. We implement these…

Dynamical Systems · Mathematics 2017-03-07 Bob Senyange

The gravitational $N$-body problem, which is fundamentally important in astrophysics to predict the motion of $N$ celestial bodies under the mutual gravity of each other, is usually solved numerically because there is no known general…

Computational Physics · Physics 2021-12-10 Maxwell X. Cai , Simon Portegies Zwart , Damian Podareanu

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

We construct a symplectic integrator for non-separable Hamiltonian systems combining an extended phase space approach of Pihajoki and the symmetric projection method. The resulting method is semiexplicit in the sense that the main time…

Numerical Analysis · Mathematics 2023-03-24 Buddhika Jayawardana , Tomoki Ohsawa

Hill's equations are an approximation that is useful in a number of areas of astrophysics including planetary rings and planetesimal disks. We derive a symplectic method for integrating Hill's equations based on a generalized leapfrog. This…

Earth and Planetary Astrophysics · Physics 2015-05-13 T. Quinn , R. P. Perrine , D. C. Richardson , R. Barnes

We study periodic orbits in the spatial rotating Kepler problem from a symplectic-topological perspective. Our first main result provides a complete classification of these orbits via a natural parametrization of the space of Kepler orbits,…

Symplectic Geometry · Mathematics 2026-03-06 Dongho Lee

We present a class of symplectic integrators adapted for the integration of perturbed Hamiltonian systems of the form $H=A+\epsilon B$. We give a constructive proof that for all integer $p$, there exists an integrator with positive steps…

Astrophysics · Physics 2023-07-19 J. Laskar , P. Robutel

Many important physical systems can be described as the evolution of a Hamiltonian system, which has the important property of being conservative, that is, energy is conserved throughout the evolution. Physics Informed Neural Networks and…

Machine Learning · Computer Science 2025-12-10 Harsh Choudhary , Chandan Gupta , Vyacheslav Kungurtsev , Melvin Leok , Georgios Korpas

We present a practical algorithm based on symplectic splitting methods to integrate numerically in time the Schr\"odinger equation. When discretized in space, the Schr\"odinger equation can be recast as a classical Hamiltonian system…

Numerical Analysis · Mathematics 2015-02-24 S. Blanes , F. Casas , A. Murua

We construct a symplectic, globally defined, minimal-coordinate, equivariant integrator on products of 2-spheres. Examples of corresponding Hamiltonian systems, called spin systems, include the reduced free rigid body, the motion of point…

Mathematical Physics · Physics 2017-05-19 Robert I. McLachlan , Klas Modin , Olivier Verdier

Symplectic mappings are discrete-time analogs of Hamiltonian systems. They appear in many areas of physics, including, for example, accelerators, plasma, and fluids. Integrable mappings, a subclass of symplectic mappings, are equivalent to…

Exactly Solvable and Integrable Systems · Physics 2017-04-12 Timofey Zolkin , Sergei Nagaitsev , Viatcheslav Danilov

In recent publications, the construction of explicit symplectic integrators for Schwarzschild and Kerr type spacetimes is based on splitting and composition methods for numerical integrations of Hamiltonians or time-transformed Hamiltonians…

General Relativity and Quantum Cosmology · Physics 2022-03-30 Naying Zhou , Hongxing Zhang , Wenfang Liu , Xin Wu

We construct an explicit reversible symplectic integrator for the planar 3-body problem with zero angular momentum. We start with a Hamiltonian of the planar 3-body problem that is globally regularised and fully symmetry reduced. This…

Computational Physics · Physics 2013-10-30 Danya Rose , Holger Dullin

Measurement data is often sampled irregularly i.e. not on equidistant time grids. This is also true for Hamiltonian systems. However, existing machine learning methods, which learn symplectic integrators, such as SympNets [20] and…

Machine Learning · Computer Science 2025-09-22 Konrad Janik , Peter Benner