Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds (Q6194167)

scientific article; zbMATH DE number 7804966

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English	Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds	scientific article; zbMATH DE number 7804966

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instance of

scholarly article

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title

Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds (English)

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Computer Methods in Applied Mechanics and Engineering

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publication date

14 February 2024

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full work available at URL

https://arxiv.org/abs/2305.15490

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zbMATH Keywords

symplectic model reduction

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Hamiltonian systems

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data-driven modeling

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quadratic manifolds

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scientific machine learning

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MaRDI profile type

MaRDI publication profile

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cites work

Symplectic Model Reduction of Hamiltonian Systems

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Structure Preserving Model Reduction of Parametric Hamiltonian Systems

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Structure-preserving Galerkin POD reduced-order modeling of Hamiltonian systems

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Rank-adaptive structure-preserving model order reduction of Hamiltonian systems

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Decay of the Kolmogorov \(N\)-width for wave problems

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Nonlinear model order reduction based on local reduced-order bases

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Localized Discrete Empirical Interpolation Method

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Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases

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Predicting solar wind streams from the inner-heliosphere to Earth via shifted operator inference

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The neural network shifted-proper orthogonal decomposition: a machine learning approach for non-linear reduction of hyperbolic equations

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The Shifted Proper Orthogonal Decomposition: A Mode Decomposition for Multiple Transport Phenomena

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Reduced basis techniques for nonlinear conservation laws

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Dynamical Low‐Rank Approximation

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Dynamically orthogonal field equations for continuous stochastic dynamical systems

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Non-intrusive model reduction of large-scale, nonlinear dynamical systems using deep learning

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An artificial neural network framework for reduced order modeling of transient flows

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Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

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A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

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Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder

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Quadratic approximation manifold for mitigating the Kolmogorov barrier in nonlinear projection-based model order reduction

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Operator inference for non-intrusive model reduction with quadratic manifolds

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Numerical methods for Hamiltonian PDEs

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Preserving energy resp. dissipation in numerical PDEs using the ``Average Vector Field'' method

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Geometric Numerical Integration

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A review of structure-preserving numerical methods for engineering applications

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Q4016507

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Symplectic integration of Hamiltonian wave equations

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On the stability of symplectic and energy-momentum algorithms for nonlinear Hamiltonian systems with symmetry

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Performance assessment of energy-preserving, adaptive time-step variational integrators

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Efficient reduced models and<i>a posteriori</i>error estimation for parametrized dynamical systems by offline/online decomposition

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The Differentiation of Pseudo-Inverses and Nonlinear Least Squares Problems Whose Variables Separate

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A linearly implicit energy-preserving exponential integrator for the nonlinear Klein-Gordon equation

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Structure-preserving reduced basis methods for Poisson systems

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Data-driven operator inference for nonintrusive projection-based model reduction

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Identifiers

arXiv ID

2305.15490

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DOI

10.1016/j.cma.2023.116402

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6194167