Chaos detection tools: application to a self-consistent triaxial model

Autores
Maffione, Nicolás Pablo; Darriba, Luciano Ariel; Cincotta, Pablo Miguel; Giordano, Claudia Marcela
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Together with the variational indicators of chaos, the spectral analysis methods have also achieved great popularity in the field of chaos detection. The former are based on the concept of local exponential divergence. The latter are based on the numerical analysis of some particular quantities of a single orbit, e.g. its frequency. In spite of having totally different conceptual bases, they are used for the very same goals such as, for instance, separating the chaotic and the regular components. In fact, we show herein that the variational indicators serve to distinguish both components of a Hamiltonian system in a more reliable fashion than a spectral analysis method does. We study two start spaces for different energy levels of a self-consistent triaxial stellar dynamical model by means of some selected variational indicators and a spectral analysis method. In order to select the appropriate tools for this paper, we extend previous studies where we make a comparison of several variational indicators on different scenarios. Herein, we compare the average power-law exponent (APLE) and an alternative quantity given by the mean exponential growth factor of nearby orbits (MEGNO): the MEGNO's slope estimation of the largest Lyapunov characteristic exponent (SElLCE). The spectral analysis method selected for the investigation is the frequency modified Fourier transform (FMFT). Besides a comparative study of the APLE, the fast Lyapunov indicator (FLI), the orthogonal fast Lyapunov indicator (OFLI) and theMEGNO/SElLCE, we show that the SElLCE could be an appropriate alternative to the MEGNO when studying large samples of initial conditions. The SElLCE separates the chaotic and the regular components reliably and identifies the different levels of chaoticity. We show that the FMFT is not as reliable as the SElLCE to describe clearly the chaotic domains in the experiments. We use the latter indicator as the main variational indicator to analyse the phase space portraits of the model under study.
Facultad de Ciencias Astronómicas y Geofísicas
Instituto de Astrofísica de La Plata
Materia
Ciencias Astronómicas
Kinematics and dynamics
Methods
Numerical-Galaxies
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/85418

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spelling Chaos detection tools: application to a self-consistent triaxial modelMaffione, Nicolás PabloDarriba, Luciano ArielCincotta, Pablo MiguelGiordano, Claudia MarcelaCiencias AstronómicasKinematics and dynamicsMethodsNumerical-GalaxiesTogether with the variational indicators of chaos, the spectral analysis methods have also achieved great popularity in the field of chaos detection. The former are based on the concept of local exponential divergence. The latter are based on the numerical analysis of some particular quantities of a single orbit, e.g. its frequency. In spite of having totally different conceptual bases, they are used for the very same goals such as, for instance, separating the chaotic and the regular components. In fact, we show herein that the variational indicators serve to distinguish both components of a Hamiltonian system in a more reliable fashion than a spectral analysis method does. We study two start spaces for different energy levels of a self-consistent triaxial stellar dynamical model by means of some selected variational indicators and a spectral analysis method. In order to select the appropriate tools for this paper, we extend previous studies where we make a comparison of several variational indicators on different scenarios. Herein, we compare the average power-law exponent (APLE) and an alternative quantity given by the mean exponential growth factor of nearby orbits (MEGNO): the MEGNO's slope estimation of the largest Lyapunov characteristic exponent (SElLCE). The spectral analysis method selected for the investigation is the frequency modified Fourier transform (FMFT). Besides a comparative study of the APLE, the fast Lyapunov indicator (FLI), the orthogonal fast Lyapunov indicator (OFLI) and theMEGNO/SElLCE, we show that the SElLCE could be an appropriate alternative to the MEGNO when studying large samples of initial conditions. The SElLCE separates the chaotic and the regular components reliably and identifies the different levels of chaoticity. We show that the FMFT is not as reliable as the SElLCE to describe clearly the chaotic domains in the experiments. We use the latter indicator as the main variational indicator to analyse the phase space portraits of the model under study.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plata2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf2700-2717http://sedici.unlp.edu.ar/handle/10915/85418enginfo:eu-repo/semantics/altIdentifier/issn/0035-8711info:eu-repo/semantics/altIdentifier/doi/10.1093/mnras/sts539info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:16:30Zoai:sedici.unlp.edu.ar:10915/85418Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:16:31.139SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Chaos detection tools: application to a self-consistent triaxial model
title Chaos detection tools: application to a self-consistent triaxial model
spellingShingle Chaos detection tools: application to a self-consistent triaxial model
Maffione, Nicolás Pablo
Ciencias Astronómicas
Kinematics and dynamics
Methods
Numerical-Galaxies
title_short Chaos detection tools: application to a self-consistent triaxial model
title_full Chaos detection tools: application to a self-consistent triaxial model
title_fullStr Chaos detection tools: application to a self-consistent triaxial model
title_full_unstemmed Chaos detection tools: application to a self-consistent triaxial model
title_sort Chaos detection tools: application to a self-consistent triaxial model
dc.creator.none.fl_str_mv Maffione, Nicolás Pablo
Darriba, Luciano Ariel
Cincotta, Pablo Miguel
Giordano, Claudia Marcela
author Maffione, Nicolás Pablo
author_facet Maffione, Nicolás Pablo
Darriba, Luciano Ariel
Cincotta, Pablo Miguel
Giordano, Claudia Marcela
author_role author
author2 Darriba, Luciano Ariel
Cincotta, Pablo Miguel
Giordano, Claudia Marcela
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Astronómicas
Kinematics and dynamics
Methods
Numerical-Galaxies
topic Ciencias Astronómicas
Kinematics and dynamics
Methods
Numerical-Galaxies
dc.description.none.fl_txt_mv Together with the variational indicators of chaos, the spectral analysis methods have also achieved great popularity in the field of chaos detection. The former are based on the concept of local exponential divergence. The latter are based on the numerical analysis of some particular quantities of a single orbit, e.g. its frequency. In spite of having totally different conceptual bases, they are used for the very same goals such as, for instance, separating the chaotic and the regular components. In fact, we show herein that the variational indicators serve to distinguish both components of a Hamiltonian system in a more reliable fashion than a spectral analysis method does. We study two start spaces for different energy levels of a self-consistent triaxial stellar dynamical model by means of some selected variational indicators and a spectral analysis method. In order to select the appropriate tools for this paper, we extend previous studies where we make a comparison of several variational indicators on different scenarios. Herein, we compare the average power-law exponent (APLE) and an alternative quantity given by the mean exponential growth factor of nearby orbits (MEGNO): the MEGNO's slope estimation of the largest Lyapunov characteristic exponent (SElLCE). The spectral analysis method selected for the investigation is the frequency modified Fourier transform (FMFT). Besides a comparative study of the APLE, the fast Lyapunov indicator (FLI), the orthogonal fast Lyapunov indicator (OFLI) and theMEGNO/SElLCE, we show that the SElLCE could be an appropriate alternative to the MEGNO when studying large samples of initial conditions. The SElLCE separates the chaotic and the regular components reliably and identifies the different levels of chaoticity. We show that the FMFT is not as reliable as the SElLCE to describe clearly the chaotic domains in the experiments. We use the latter indicator as the main variational indicator to analyse the phase space portraits of the model under study.
Facultad de Ciencias Astronómicas y Geofísicas
Instituto de Astrofísica de La Plata
description Together with the variational indicators of chaos, the spectral analysis methods have also achieved great popularity in the field of chaos detection. The former are based on the concept of local exponential divergence. The latter are based on the numerical analysis of some particular quantities of a single orbit, e.g. its frequency. In spite of having totally different conceptual bases, they are used for the very same goals such as, for instance, separating the chaotic and the regular components. In fact, we show herein that the variational indicators serve to distinguish both components of a Hamiltonian system in a more reliable fashion than a spectral analysis method does. We study two start spaces for different energy levels of a self-consistent triaxial stellar dynamical model by means of some selected variational indicators and a spectral analysis method. In order to select the appropriate tools for this paper, we extend previous studies where we make a comparison of several variational indicators on different scenarios. Herein, we compare the average power-law exponent (APLE) and an alternative quantity given by the mean exponential growth factor of nearby orbits (MEGNO): the MEGNO's slope estimation of the largest Lyapunov characteristic exponent (SElLCE). The spectral analysis method selected for the investigation is the frequency modified Fourier transform (FMFT). Besides a comparative study of the APLE, the fast Lyapunov indicator (FLI), the orthogonal fast Lyapunov indicator (OFLI) and theMEGNO/SElLCE, we show that the SElLCE could be an appropriate alternative to the MEGNO when studying large samples of initial conditions. The SElLCE separates the chaotic and the regular components reliably and identifies the different levels of chaoticity. We show that the FMFT is not as reliable as the SElLCE to describe clearly the chaotic domains in the experiments. We use the latter indicator as the main variational indicator to analyse the phase space portraits of the model under study.
publishDate 2013
dc.date.none.fl_str_mv 2013
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dc.language.none.fl_str_mv eng
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dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0035-8711
info:eu-repo/semantics/altIdentifier/doi/10.1093/mnras/sts539
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