Symplectic Gaussian process regression of maps in Hamiltonian systems

DOI10.1063/5.0048129zbMath1471.37072arXiv2009.05569OpenAlexW3163612619MaRDI QIDQ4993722

Bernd Bischl, Katharina Rath, Udo von Toussaint, Christopher G. Albert

Publication date: 16 June 2021

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.05569

zbMATH Keywords

Poincaré mapsGaussian process regressionHamiltonian flow mapsstructure-preserving emulators

Mathematics Subject Classification ID

Numerical methods for Hamiltonian systems including symplectic integrators (65P10) Discretization methods and integrators (symplectic, variational, geometric, etc.) for dynamical systems (37M15)

Related Items

SympGPR, Variational learning of Euler-Lagrange dynamics from data

Uses Software

• L-BFGS-B
• L-BFGS
• LBFGS-B
• pycma
• proFit

Cites Work

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