Koltai, P. and Renger, M. (2017) From large deviations to transport semidistances: coherence analysis for finite Lagrangian data. SFB 1114 Preprint in arXiv:1709.02352 . pp. 134. (Unpublished)

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Official URL: https://arxiv.org/abs/1709.02352
Abstract
One way to analyze complicated nonautonomous flows is through trying to understand their transport behavior. In a quantitative, setoriented approach to transport, finite time coherent sets play an important role. These are timeparametrized families of sets with unlikely transport to and from their surroundings under small or vanishing random perturbations of the dynamics. Here we propose, as a measure of transport, (semi)distances that arise under vanishing perturbations in the sense of large deviations. Analogously, for given finite Lagrangian trajectory data we derive a discretetime and space semidistance that comes from the "best" approximation of the randomly perturbed process conditioned on this limited information on the deterministic flow. It can be computed as shortest path in a graph with timedependent weights. Furthermore, we argue that coherent sets are regions of maximal farness in terms of transport, hence they occur as extremal regions on a spanning structure of the state space under this semidistance  in fact, under any distance measure arising from the physical notion of transport. Based on this notion we develop a tool to analyze the state space (or the finite trajectory data at hand) and identify coherent regions. We validate our approach on idealized prototypical examples and wellstudied standard cases.
Item Type:  Article 

Subjects:  Mathematical and Computer Sciences > Mathematics 
Divisions:  Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group 
ID Code:  2137 
Deposited By:  Silvia Hoemke 
Deposited On:  27 Nov 2017 11:35 
Last Modified:  16 Feb 2018 09:41 
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