Chaos identification through the autocorrelation function indicator (ACFI)

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dc.contributor.authorCarruba, V. [UNESP]
dc.contributor.authorAljbaae, S.
dc.contributor.authorDomingos, R. C. [UNESP]
dc.contributor.authorHuaman, M.
dc.contributor.authorBarletta, W. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionNational Space Research Institute (INPE)
dc.contributor.institutionUniversidad Tecnológica del Perú (UTP)
dc.date.accessioned2022-05-01T08:15:12Z
dc.date.available2022-05-01T08:15:12Z
dc.date.issued2021-08-01
dc.description.abstractChaotic motion affecting small bodies in the Solar system can be caused by close encounters or collisions or by resonance overlapping. Chaotic motion can be detected using approaches that measure the separation rate of trajectories that starts infinitesimally close or changes in the frequency power spectrum of time series, among others. In this work, we introduce an approach based on the autocorrelation function of time series, the ACF index (ACFI). Autocorrelation coefficients measure the correlation of a time series with a lagged copy of itself. By measuring the fraction of autocorrelation coefficients obtained after a given time lag that are higher than the 5% null hypothesis threshold, we can determine how the time series autocorrelates with itself. This allows identifying unpredictable time series, characterized by low values of ACFI. Applications of ACFI to orbital regions affected by both types of chaos show that this method can correctly identify chaotic motion caused by resonance overlapping, but it is mostly blind to close encounters induced chaos. ACFI could be used in these regions to select the effects of resonance overlapping.en
dc.description.affiliationSchool of Natural Sciences and Engineering São Paulo State University (UNESP)
dc.description.affiliationDivision of Space Mechanics and Control National Space Research Institute (INPE), C.P. 515
dc.description.affiliationSão Paulo State University (UNESP)
dc.description.affiliationUniversidad Tecnológica del Perú (UTP), Cercado de Lima
dc.description.affiliationUnespSchool of Natural Sciences and Engineering São Paulo State University (UNESP)
dc.description.affiliationUnespSão Paulo State University (UNESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdCNPq: 121889/2020-3
dc.description.sponsorshipIdFAPESP: 2016/024561-0
dc.description.sponsorshipIdCNPq: 301577/2017-0
dc.description.sponsorshipIdCAPES: 88887.374148/2019-00
dc.identifierhttp://dx.doi.org/10.1007/s10569-021-10036-6
dc.identifier.citationCelestial Mechanics and Dynamical Astronomy, v. 133, n. 8, 2021.
dc.identifier.doi10.1007/s10569-021-10036-6
dc.identifier.issn1572-9478
dc.identifier.issn0923-2958
dc.identifier.scopus2-s2.0-85112361312
dc.identifier.urihttp://hdl.handle.net/11449/233378
dc.language.isoeng
dc.relation.ispartofCelestial Mechanics and Dynamical Astronomy
dc.sourceScopus
dc.subjectAsteroid belt
dc.subjectCelestial mechanics
dc.subjectChaotic motions
dc.subjectStatistical methods
dc.titleChaos identification through the autocorrelation function indicator (ACFI)en
dc.typeArtigo
unesp.author.orcid0000-0003-2786-0740[1]
unesp.departmentMatemática - FEGpt

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Guaratinguetá - FEG - Faculdade de Engenharia e Ciências