Identifying finite-time coherent sets from limited quantities of Lagrangian data

DOI10.1063/1.4927424zbMath1374.37121arXiv1412.7441OpenAlexW1515976134WikidataQ30990993 ScholiaQ30990993MaRDI QIDQ4591745

Irina I. Rypina, Clarence W. Rowley, Matthew O. Williams

Publication date: 17 November 2017

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

Full work available at URL: https://arxiv.org/abs/1412.7441

Mathematics Subject Classification ID

Dynamical systems in fluid mechanics, oceanography and meteorology (37N10) Time series analysis of dynamical systems (37M10)

Related Items (16)

From large deviations to semidistances of transport and mixing: coherence analysis for finite Lagrangian data ⋮ Generalized Lagrangian coherent structures ⋮ On the numerical approximation of the Perron-Frobenius and Koopman operator ⋮ On fast computation of finite-time coherent sets using radial basis functions ⋮ Detecting Lagrangian coherent structures from sparse and noisy trajectory data ⋮ Quantifying the Role of Folding in Nonautonomous Flows: The Unsteady Double-Gyre ⋮ Sparse subsampling of flow measurements for finite-time Lyapunov exponent in domains with obstacles ⋮ Sparse eigenbasis approximation: multiple feature extraction across spatiotemporal scales with application to coherent set identification ⋮ Understanding the geometry of transport: Diffusion maps for Lagrangian trajectory data unravel coherent sets ⋮ A critical comparison of Lagrangian methods for coherent structure detection ⋮ Estimating the Finite Time Lyapunov Exponent from Sparse Lagrangian Trajectories ⋮ Kernel methods for detecting coherent structures in dynamical data ⋮ Observability of laminar bidimensional fluid flows seen as autonomous chaotic systems ⋮ Topological colouring of fluid particles unravels finite-time coherent sets ⋮ Network measures of mixing ⋮ Linear response for the dynamic Laplacian and finite-time coherent sets

Uses Software

• Matlab
• GAIO
• ROMS
• PRMLT

Cites Work

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