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Symplectic integrators can be excellent for Hamiltonian initial value problems. Reasons for this include their preservation of invariant sets like tori, good energy behaviour, nonexistence of attractors, and good behaviour of statistical…

Numerical Analysis · Mathematics 2018-09-19 Robert I McLachlan , Christian Offen

Symplectic integration algorithms have become popular in recent years in long-term orbital integrations because these algorithms enforce certain conservation laws that are intrinsic to Hamiltonian systems. For problems with large variations…

Astrophysics · Physics 2007-05-23 Man Hoi Lee , Martin J. Duncan , Harold F. Levison

Many physically important mechanical systems may be described with a Lie group $G$ as configuration space. According to the well-known Noether's theorem, underlying symmetries of the Lie group may be used to considerably reduce the…

Mathematical Physics · Physics 2017-08-07 Joël Bensoam , Florie-Anne Baugé

In this paper, we develop a structure-preserving discretization of the Lagrangian framework for electromagnetism, combining techniques from variational integrators and discrete differential forms. This leads to a general family of…

Numerical Analysis · Mathematics 2015-11-05 Ari Stern , Yiying Tong , Mathieu Desbrun , Jerrold E. Marsden

Modified Hamiltonians are used in the field of geometric numerical integration to show that symplectic schemes for Hamiltonian systems are accurate over long times. For nonlinear systems the series defining the modified Hamiltonian usually…

Numerical Analysis · Mathematics 2018-11-14 Shami A Alsallami , Jitse Niesen , Frank W Nijhoff

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

Retraction maps have been generalized to discretization maps in (Barbero Li\~n\'an and and Mart\'{\i}n de Diego, 2022). Discretization maps are used to systematically derive numerical integrators that preserve the symplectic structure, as…

Numerical Analysis · Mathematics 2024-01-29 María Barbero-Liñán , Juan Carlos Marrero , David Martín de Diego

Variational integrators for Lagrangian dynamical systems provide a systematic way to derive geometric numerical methods. These methods preserve a discrete multisymplectic form as well as momenta associated to symmetries of the Lagrangian…

Numerical Analysis · Mathematics 2017-10-05 Michael Kraus , Omar Maj

A Lie system is the non-autonomous system of differential equations describing the integral curves of a non-autonomous vector field taking values in a finite-dimensional Lie algebra of vector fields, a so-called Vessiot--Guldberg Lie…

Mathematical Physics · Physics 2025-11-18 X. Gràcia , J. de Lucas , M. C. Muñoz-Lecanda , S. Vilariño

We consider the continuous and discrete-time Hamilton's variational principle on phase space, and characterize the exact discrete Hamiltonian which provides an exact correspondence between discrete and continuous Hamiltonian mechanics. The…

Numerical Analysis · Mathematics 2010-01-12 Melvin Leok , Jingjing Zhang

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

Hamiltonian systems are differential equations which describe systems in classical mechanics, plasma physics, and sampling problems. They exhibit many structural properties, such as a lack of attractors and the presence of conservation…

Numerical Analysis · Mathematics 2022-01-14 Christian Offen , Sina Ober-Blöbaum

The paper deals with numerical discretizations of separable nonlinear Hamiltonian systems with additive noise. For such problems, the expected value of the total energy, along the exact solution, drifts linearly with time. We present and…

Numerical Analysis · Mathematics 2023-12-06 Chuchu Chen , David Cohen , Raffaele D'Ambrosio , Annika Lang

Symplectic integrators offer many advantages for the numerical solution of Hamiltonian differential equations, including bounded energy error and the preservation of invariant sets. Two of the central Hamiltonian systems encountered in…

Plasma Physics · Physics 2018-05-23 C. Leland Ellison , John M. Finn , Joshua W. Burby , Michael Kraus , Hong Qin , William M. Tang

We construct stochastic multisymplectic systems by considering a stochastic extension to the variational formulation of multisymplectic partial differential equations proposed in [Hydon, {\it Proc. R. Soc. A}, 461, 1627--1637, 2005]. The…

Dynamical Systems · Mathematics 2025-11-19 Ruiao Hu , Linyu Peng

We introduce the Euler-Lagrange cohomology to study the symplectic and multisymplectic structures and their preserving properties in finite and infinite dimensional Lagrangian systems respectively. We also explore their certain difference…

High Energy Physics - Phenomenology · Physics 2016-09-06 H. Y. Guo , Y. Q. Li , K. Wu

Symplectic integration of autonomous Hamiltonian systems is a well-known field of study in geometric numerical integration, but for non-autonomous systems the situation is less clear, since symplectic structure requires an even number of…

Numerical Analysis · Mathematics 2014-09-18 Håkon Marthinsen , Brynjulf Owren

We suggest a numerical integration procedure for solving the equations of motion of certain classical spin systems which preserves the underlying symplectic structure of the phase space. Such symplectic integrators have been successfully…

Statistical Mechanics · Physics 2007-05-23 Robin Steinigeweg , Heinz-Jürgen Schmidt

A variational framework for accelerated optimization was recently introduced on normed vector spaces and Riemannian manifolds in Wibisono et al. (2016) and Duruisseaux and Leok (2021). It was observed that a careful combination of…

Optimization and Control · Mathematics 2023-05-16 Valentin Duruisseaux , Melvin Leok

In many applications, one encounters signals that lie on manifolds rather than a Euclidean space. In particular, covariance matrices are examples of ubiquitous mathematical objects that have a non Euclidean structure. The application of…

Signal Processing · Electrical Eng. & Systems 2024-07-25 Lucas Drumetz , Alexandre Reiffers-Masson , Naoufal El Bekri , Franck Vermet