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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...

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Autores principales: Bazzani, A., Giovannozzi, M., Montanari, C.E., Turchetti, G.
Lenguaje:eng
Publicado: 2023
Materias:
Acceso en línea:https://dx.doi.org/10.1103/PhysRevE.107.064209
http://cds.cern.ch/record/2856415
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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.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2023
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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