Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence

The use of transfer entropy has proven to be helpful in detecting which is the verse of dynamical driving in the interaction of two processes, X and Y . In this paper, we present a different normalization for the transfer entropy, which is capable of better detecting the information transfer directi...

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Main Authors: Massimo Materassi, Giuseppe Consolini, Nathan Smith, Rossana De Marco
Format: Article
Language:English
Published: MDPI AG 2014-02-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/16/3/1272
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author Massimo Materassi
Giuseppe Consolini
Nathan Smith
Rossana De Marco
author_facet Massimo Materassi
Giuseppe Consolini
Nathan Smith
Rossana De Marco
author_sort Massimo Materassi
collection DOAJ
description The use of transfer entropy has proven to be helpful in detecting which is the verse of dynamical driving in the interaction of two processes, X and Y . In this paper, we present a different normalization for the transfer entropy, which is capable of better detecting the information transfer direction. This new normalized transfer entropy is applied to the detection of the verse of energy flux transfer in a synthetic model of fluid turbulence, namely the Gledzer–Ohkitana–Yamada shell model. Indeed, this is a fully well-known model able to model the fully developed turbulence in the Fourier space, which is characterized by an energy cascade towards the small scales (large wavenumbers k), so that the application of the information-theory analysis to its outcome tests the reliability of the analysis tool rather than exploring the model physics. As a result, the presence of a direct cascade along the scales in the shell model and the locality of the interactions in the space of wavenumbers come out as expected, indicating the validity of this data analysis tool. In this context, the use of a normalized version of transfer entropy, able to account for the difference of the intrinsic randomness of the interacting processes, appears to perform better, being able to discriminate the wrong conclusions to which the “traditional” transfer entropy would drive.
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spelling doaj.art-950f2d18833c4e7e9188e8239d19d2da2022-12-22T04:23:28ZengMDPI AGEntropy1099-43002014-02-011631272128610.3390/e16031272e16031272Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid TurbulenceMassimo Materassi0Giuseppe Consolini1Nathan Smith2Rossana De Marco3Istituto dei Sistemi Complessi ISC-CNR, via Madonna del Piano 10, 50019 Sesto Fiorentino, ItalyINAF-Istituto di Astrofisica e Planetologia Spaziali Area di Ricerca Roma Tor Vergata, Via del Fossodel Cavaliere, 100, 00133 Roma, ItalyDepartment of Electronic and Electrical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UKINAF-Istituto di Astrofisica e Planetologia Spaziali Area di Ricerca Roma Tor Vergata, Via del Fossodel Cavaliere, 100, 00133 Roma, ItalyThe use of transfer entropy has proven to be helpful in detecting which is the verse of dynamical driving in the interaction of two processes, X and Y . In this paper, we present a different normalization for the transfer entropy, which is capable of better detecting the information transfer direction. This new normalized transfer entropy is applied to the detection of the verse of energy flux transfer in a synthetic model of fluid turbulence, namely the Gledzer–Ohkitana–Yamada shell model. Indeed, this is a fully well-known model able to model the fully developed turbulence in the Fourier space, which is characterized by an energy cascade towards the small scales (large wavenumbers k), so that the application of the information-theory analysis to its outcome tests the reliability of the analysis tool rather than exploring the model physics. As a result, the presence of a direct cascade along the scales in the shell model and the locality of the interactions in the space of wavenumbers come out as expected, indicating the validity of this data analysis tool. In this context, the use of a normalized version of transfer entropy, able to account for the difference of the intrinsic randomness of the interacting processes, appears to perform better, being able to discriminate the wrong conclusions to which the “traditional” transfer entropy would drive.http://www.mdpi.com/1099-4300/16/3/1272transfer entropydynamical systemsturbulencecascadesshell models
spellingShingle Massimo Materassi
Giuseppe Consolini
Nathan Smith
Rossana De Marco
Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
Entropy
transfer entropy
dynamical systems
turbulence
cascades
shell models
title Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
title_full Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
title_fullStr Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
title_full_unstemmed Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
title_short Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence
title_sort information theory analysis of cascading process in a synthetic model of fluid turbulence
topic transfer entropy
dynamical systems
turbulence
cascades
shell models
url http://www.mdpi.com/1099-4300/16/3/1272
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AT nathansmith informationtheoryanalysisofcascadingprocessinasyntheticmodeloffluidturbulence
AT rossanademarco informationtheoryanalysisofcascadingprocessinasyntheticmodeloffluidturbulence