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Performance analysis of indicators of chaos for nonlinear dynamical systems
The efficient detection of chaotic behavior in orbits of a complex dynamical system is an active domain of research. Several indicators have been proposed, and new ones have recently been developed in view of improving the performance of chaos detection by means of numerical simulations. The challen...
Autores principales: | , , , |
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Lenguaje: | eng |
Publicado: |
2023
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1103/PhysRevE.107.064209 http://cds.cern.ch/record/2856415 |
_version_ | 1780977505137590272 |
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author | Bazzani, A. Giovannozzi, M. Montanari, C.E. Turchetti, G. |
author_facet | Bazzani, A. Giovannozzi, M. Montanari, C.E. Turchetti, G. |
author_sort | Bazzani, A. |
collection | CERN |
description | The efficient detection of chaotic behavior in orbits of a complex dynamical system is an active domain of research. Several indicators have been proposed, and new ones have recently been developed in view of improving the performance of chaos detection by means of numerical simulations. The challenge is to predict chaotic behavior based on the analysis of orbits of limited length. In this paper the performance analysis of past and recent indicators of chaos, in terms of predictive power, is carried out in detail using the dynamical system characterized by a symplectic Hénon-like cubic polynomial map. |
id | cern-2856415 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2023 |
record_format | invenio |
spelling | cern-28564152023-07-11T13:41:44Zdoi:10.1103/PhysRevE.107.064209http://cds.cern.ch/record/2856415engBazzani, A.Giovannozzi, M.Montanari, C.E.Turchetti, G.Performance analysis of indicators of chaos for nonlinear dynamical systemsphysics.acc-phAccelerators and Storage Ringsnlin.CDNonlinear Systemsmath.DSMathematical Physics and MathematicsThe efficient detection of chaotic behavior in orbits of a complex dynamical system is an active domain of research. Several indicators have been proposed, and new ones have recently been developed in view of improving the performance of chaos detection by means of numerical simulations. The challenge is to predict chaotic behavior based on the analysis of orbits of limited length. In this paper the performance analysis of past and recent indicators of chaos, in terms of predictive power, is carried out in detail using the dynamical system characterized by a symplectic Hénon-like cubic polynomial map.The efficient detection of chaotic behavior in orbits of a complex dynamical system is an active domain of research. Several indicators have been proposed in the past, and new ones have recently been developed in view of improving the performance of chaos detection by means of numerical simulations. The challenge is to predict chaotic behavior based on the analysis of orbits of limited length. In this paper, the performance analysis of past and recent indicators of chaos, in terms of predictive power, is carried out in detail using the dynamical system characterized by a symplectic Hénon-like cubic polynomial map.arXiv:2304.08340oai:cds.cern.ch:28564152023-04-13 |
spellingShingle | physics.acc-ph Accelerators and Storage Rings nlin.CD Nonlinear Systems math.DS Mathematical Physics and Mathematics Bazzani, A. Giovannozzi, M. Montanari, C.E. Turchetti, G. Performance analysis of indicators of chaos for nonlinear dynamical systems |
title | Performance analysis of indicators of chaos for nonlinear dynamical systems |
title_full | Performance analysis of indicators of chaos for nonlinear dynamical systems |
title_fullStr | Performance analysis of indicators of chaos for nonlinear dynamical systems |
title_full_unstemmed | Performance analysis of indicators of chaos for nonlinear dynamical systems |
title_short | Performance analysis of indicators of chaos for nonlinear dynamical systems |
title_sort | performance analysis of indicators of chaos for nonlinear dynamical systems |
topic | physics.acc-ph Accelerators and Storage Rings nlin.CD Nonlinear Systems math.DS Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1103/PhysRevE.107.064209 http://cds.cern.ch/record/2856415 |
work_keys_str_mv | AT bazzania performanceanalysisofindicatorsofchaosfornonlineardynamicalsystems AT giovannozzim performanceanalysisofindicatorsofchaosfornonlineardynamicalsystems AT montanarice performanceanalysisofindicatorsofchaosfornonlineardynamicalsystems AT turchettig performanceanalysisofindicatorsofchaosfornonlineardynamicalsystems |