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Journal of Computational Dynamics
Article . 2021 . Peer-reviewed
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zbMATH Open
Article . 2021
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https://dx.doi.org/10.48550/ar...
Article . 2020
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Article . 2021
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On computational Poisson geometry II: Numerical methods

On computational Poisson geometry. II. Numerical methods
Authors: M. A. Evangelista-Alvarado; J. C. Ruíz-Pantaleón; Pablo Suárez-Serrato;

On computational Poisson geometry II: Numerical methods

Abstract

We present twelve numerical methods for evaluation of objects and concepts from Poisson geometry. We describe how each method works with examples, and explain how it is executed in code. These include methods that evaluate Hamiltonian and modular vector fields, compute the image under the coboundary and trace operators, the Lie bracket of differential 1-forms, gauge transformations, and normal forms of Lie-Poisson structures on $\mathbf{R}^{3}$. The complexity of each of our methods is calculated, and we include experimental verifications on examples in dimensions two and three.

Keywords

Mathematics - Differential Geometry, G.4, 53-04, 53D17, 65P10, Poisson structures, G.1, G.1; G.4, Numerical Analysis (math.NA), Numerical methods for Hamiltonian systems including symplectic integrators, Hamiltonian dynamics, Poisson manifolds; Poisson groupoids and algebroids, python, Poisson-Nijenhuis calculus, Differential Geometry (math.DG), Mathematics - Symplectic Geometry, numerical methods, FOS: Mathematics, Symplectic Geometry (math.SG), Software, source code, etc. for problems pertaining to differential geometry, Mathematics - Numerical Analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold