Digitally filtered resonant arguments for deep learning classification of asteroids in secular resonances

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorNatl Space Res Inst INPE-
Autor(es): dc.creatorCarruba, V-
Autor(es): dc.creatorAljbaae, S.-
Autor(es): dc.creatorDomingos, R. C.-
Autor(es): dc.creatorCarita, G.-
Autor(es): dc.creatorAlves, A.-
Autor(es): dc.creatorDelfino, E. M. D. S.-
Data de aceite: dc.date.accessioned2025-08-21T22:58:34Z-
Data de disponibilização: dc.date.available2025-08-21T22:58:34Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-06-21-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1093/mnras/stae1446-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/298190-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/298190-
Descrição: dc.descriptionNode secular resonances, or s-type secular resonances, occur when the precession frequencies of the node of an asteroid and some planets are in commensurability. They are important for changing the proper inclination of asteroids interacting with them. Traditionally, identifying the asteroid resonant status was mostly performed by visual inspection of plots of the time series of the asteroid resonant argument to check for oscillations around an equilibrium point. Recently, deep learning methods based on convolutional neural networks (CNNs) for the automatic classification of images have become more popular for these kinds of tasks, allowing for the classification of thousands of orbits in a few minutes. In this work, we study 11 s-type resonances in the asteroid main belt and in the Hungaria region and focus on the four most diffusive ones. Two secular resonances in the Hungaria region, the 2 . s - s(4) - s(6) and the s - 2 . s(6) + s(7) - g(6) + g(8) overlap, but this has negligible effects in terms of chaotic dynamics. Here, we obtained filtered images of the resonant arguments by filtering out all low-frequency signals with a Butterworth filter. A simple method based on amplitudes and periods of librations can perform a preliminary selection of asteroids in librating orbits. Our results show that CNN models applied to filtered images are much more effective in terms of metrics like accuracy, Precision, Recall, and F1-score than those that use images of osculating resonant arguments. Filtered resonant arguments should be preferentially used to identify asteroids interacting with secular resonances.-
Descrição: dc.descriptionHeising-Simons Foundation-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionSao Paulo State Univ UNESP, Sch Engn & Sci, BR-12516410 Guaratingueta, SP, Brazil-
Descrição: dc.descriptionNatl Space Res Inst INPE, Postgrad Div, CP 515, BR-12227310 Sao Jose Dos Campos, SP, Brazil-
Descrição: dc.descriptionMake Way,R Elvira Ferraz 250 FL Off 305-306, BR-04545015 Sao Paulo, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ UNESP, BR-13876750 Sao Joao Da Boa Vista, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ UNESP, Sch Engn & Sci, BR-12516410 Guaratingueta, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ UNESP, BR-13876750 Sao Joao Da Boa Vista, SP, Brazil-
Descrição: dc.descriptionHeising-Simons Foundation: 2021-2975-
Descrição: dc.descriptionCNPq: 304168/2021-1-
Descrição: dc.descriptionFAPESP: 2021/08274-9-
Formato: dc.format4432-4443-
Idioma: dc.languageen-
Publicador: dc.publisherOxford Univ Press-
Relação: dc.relationMonthly Notices Of The Royal Astronomical Society-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectmethods: statistical-
Palavras-chave: dc.subjectminor planets, asteroids: general-
Título: dc.titleDigitally filtered resonant arguments for deep learning classification of asteroids in secular resonances-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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