Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/126944
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Type: | Journal article |
Title: | Disentangling resolution, precision, and inherent stochasticity in nonlinear systems |
Author: | Fang, L. Balasuriya, S. Ouellette, N. |
Citation: | Physical Review Research, 2020; 2(2):023343-1-023343-9 |
Publisher: | American Physical Society |
Issue Date: | 2020 |
ISSN: | 2643-1564 2643-1564 |
Statement of Responsibility: | Lei Fang, Sanjeeva Balasuriya, and Nicholas T. Ouellette |
Abstract: | Reliable measurement, simulation, and analysis of dynamical systems rely on appropriately bounded uncertainty. Errors that lead to uncertainty naturally arise from finite precision or resolution, but an additional unappreciated source of uncertainty is the effective stochasticity associated with nonlinear dynamics. Here we describe and quantify the interplay between these three sources of uncertainty using a recently developed framework known as stochastic sensitivity theory. Using fluid mixing as a test case and considering data from an analytical flow, a laboratory experiment, and geophysical observations, we show how to delimit regimes that are limited by finite resolution or by inherent stochasticity. We arrive at the surprising conclusion that in some cases, refining the resolution of a measurement or simulation can actually be counterproductive and lead to an outcome that is less faithful to the true dynamics. Our results have significant implications for the measurement and analysis of nonlinear systems. |
Description: | Published 16 June 2020 |
Rights: | Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. |
DOI: | 10.1103/PhysRevResearch.2.023343 |
Grant ID: | http://purl.org/au-research/grants/arc/FT130100484 http://purl.org/au-research/grants/arc/DP200101764 |
Published version: | http://dx.doi.org/10.1103/physrevresearch.2.023343 |
Appears in Collections: | Aurora harvest 4 Mathematical Sciences publications |
Files in This Item:
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hdl_126944.pdf | Published version | 3.76 MB | Adobe PDF | View/Open |
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