Chaos detection tools

Autores
Maffione, Nicolás Pablo; Darriba, Luciano A.; Cincotta, Pablo M.; Giordano, Claudia M.
Año de publicación
2012
Idioma
español castellano
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
Fil: Maffione, Nicolas P. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Maffione, Nicolas P. Instituto de Astrofísica de La Plata; Argentina.
Fil: Maffione, Nicolas P. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Darriba, Luciano A. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Darriba, Luciano A. Instituto de Astrofísica de La Plata; Argentina.
Fil: Darriba, Luciano A. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Cincotta, Pablo M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Cincotta, Pablo M. Instituto de Astrofísica de La Plata; Argentina.
Fil: Cincotta, Pablo M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Giordano, Claudia M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Giordano, Claudia M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Giordano, Claudia M. Instituto de Astrofísica de La Plata; Argentina.
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 component. 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 Neary Orbits (MEGNO): the MEGNO? 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 the MEGNO/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.
Materia
Astronomía
Methods
Numerical
Galaxies
kinematics
Dynamics
Astronomía
Nivel de accesibilidad
acceso restringido
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
RID-UNRN (UNRN)
Institución
Universidad Nacional de Río Negro
OAI Identificador
oai:rid.unrn.edu.ar:20.500.12049/2869
Acceder
id RIDUNRN_f28c8296acd59274667efa34f4aeca9c
oai_identifier_str oai:rid.unrn.edu.ar:20.500.12049/2869
network_acronym_str RIDUNRN
repository_id_str 4369
network_name_str RID-UNRN (UNRN)
spelling Chaos detection toolsApplication to a self-consistent triaxial modelMaffione, Nicolás PabloDarriba, Luciano A.Cincotta, Pablo M.Giordano, Claudia M.AstronomíaMethodsNumericalGalaxieskinematicsDynamicsAstronomíaFil: Maffione, Nicolas P. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; ArgentinaFil: Maffione, Nicolas P. Instituto de Astrofísica de La Plata; Argentina.Fil: Maffione, Nicolas P. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Darriba, Luciano A. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; ArgentinaFil: Darriba, Luciano A. Instituto de Astrofísica de La Plata; Argentina.Fil: Darriba, Luciano A. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Cincotta, Pablo M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; ArgentinaFil: Cincotta, Pablo M. Instituto de Astrofísica de La Plata; Argentina.Fil: Cincotta, Pablo M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Giordano, Claudia M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; ArgentinaFil: Giordano, Claudia M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Giordano, Claudia M. Instituto de Astrofísica de La Plata; Argentina.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 component. 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 Neary Orbits (MEGNO): the MEGNO? 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 the MEGNO/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.2012-12-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfMaffione, Nicolas P., Darriba, Luciano A., Cincotta, Pablo M. & Giordano, Claudia M. (2012). Chaos detection tools: application to a self-consistent triaxial model. Oxford University. Monthly Notices of the Royal Astronomical Society; 429; 3; pp. 2700-27170035-8711http://arxiv.org/abs/1212.3175http://mnras.oxfordjournals.org/content/429/3/2700.abstracthttp://hdl.handle.net/11336/3411https://rid.unrn.edu.ar/jspui/handle/20.500.12049/2869http://dx.doi.org/10.1093/mnras/sts539spa429Monthly Notices of the Royal Astronomical Societyinfo:eu-repo/semantics/restrictedAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/reponame:RID-UNRN (UNRN)instname:Universidad Nacional de Río Negro2025-10-23T11:17:12Zoai:rid.unrn.edu.ar:20.500.12049/2869instacron:UNRNInstitucionalhttps://rid.unrn.edu.ar/jspui/Universidad públicaNo correspondehttps://rid.unrn.edu.ar/oai/snrdrid@unrn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:43692025-10-23 11:17:12.713RID-UNRN (UNRN) - Universidad Nacional de Río Negrofalse
dc.title.none.fl_str_mv Chaos detection tools
Application to a self-consistent triaxial model
title Chaos detection tools
spellingShingle Chaos detection tools
Maffione, Nicolás Pablo
Astronomía
Methods
Numerical
Galaxies
kinematics
Dynamics
Astronomía
title_short Chaos detection tools
title_full Chaos detection tools
title_fullStr Chaos detection tools
title_full_unstemmed Chaos detection tools
title_sort Chaos detection tools
dc.creator.none.fl_str_mv Maffione, Nicolás Pablo
Darriba, Luciano A.
Cincotta, Pablo M.
Giordano, Claudia M.
author Maffione, Nicolás Pablo
author_facet Maffione, Nicolás Pablo
Darriba, Luciano A.
Cincotta, Pablo M.
Giordano, Claudia M.
author_role author
author2 Darriba, Luciano A.
Cincotta, Pablo M.
Giordano, Claudia M.
author2_role author
author
author
dc.subject.none.fl_str_mv Astronomía
Methods
Numerical
Galaxies
kinematics
Dynamics
Astronomía
topic Astronomía
Methods
Numerical
Galaxies
kinematics
Dynamics
Astronomía
dc.description.none.fl_txt_mv Fil: Maffione, Nicolas P. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Maffione, Nicolas P. Instituto de Astrofísica de La Plata; Argentina.
Fil: Maffione, Nicolas P. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Darriba, Luciano A. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Darriba, Luciano A. Instituto de Astrofísica de La Plata; Argentina.
Fil: Darriba, Luciano A. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Cincotta, Pablo M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Cincotta, Pablo M. Instituto de Astrofísica de La Plata; Argentina.
Fil: Cincotta, Pablo M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Giordano, Claudia M. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
Fil: Giordano, Claudia M. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina
Fil: Giordano, Claudia M. Instituto de Astrofísica de La Plata; Argentina.
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 component. 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 Neary Orbits (MEGNO): the MEGNO? 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 the MEGNO/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.
description Fil: Maffione, Nicolas P. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata; Argentina
publishDate 2012
dc.date.none.fl_str_mv 2012-12-14
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv Maffione, Nicolas P., Darriba, Luciano A., Cincotta, Pablo M. & Giordano, Claudia M. (2012). Chaos detection tools: application to a self-consistent triaxial model. Oxford University. Monthly Notices of the Royal Astronomical Society; 429; 3; pp. 2700-2717
0035-8711
http://arxiv.org/abs/1212.3175
http://mnras.oxfordjournals.org/content/429/3/2700.abstract
http://hdl.handle.net/11336/3411
https://rid.unrn.edu.ar/jspui/handle/20.500.12049/2869
http://dx.doi.org/10.1093/mnras/sts539
identifier_str_mv Maffione, Nicolas P., Darriba, Luciano A., Cincotta, Pablo M. & Giordano, Claudia M. (2012). Chaos detection tools: application to a self-consistent triaxial model. Oxford University. Monthly Notices of the Royal Astronomical Society; 429; 3; pp. 2700-2717
0035-8711
url http://arxiv.org/abs/1212.3175
http://mnras.oxfordjournals.org/content/429/3/2700.abstract
http://hdl.handle.net/11336/3411
https://rid.unrn.edu.ar/jspui/handle/20.500.12049/2869
http://dx.doi.org/10.1093/mnras/sts539
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv 429
Monthly Notices of the Royal Astronomical Society
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:RID-UNRN (UNRN)
instname:Universidad Nacional de Río Negro
reponame_str RID-UNRN (UNRN)
collection RID-UNRN (UNRN)
instname_str Universidad Nacional de Río Negro
repository.name.fl_str_mv RID-UNRN (UNRN) - Universidad Nacional de Río Negro
repository.mail.fl_str_mv rid@unrn.edu.ar
_version_ 1846787709961502720
score 12.982451

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