Autor(es): Carruba, V. [UNESP] ; Spoto, F. ; Barletta, W. [UNESP] ; Aljbaae, S. ; Fazenda, L. ; Martins, B. [UNESP]
Data: 2020
Identificador Persistente: http://hdl.handle.net/11449/201268
Origem: Oasisbr
Autor(es): Carruba, V. [UNESP] ; Spoto, F. ; Barletta, W. [UNESP] ; Aljbaae, S. ; Fazenda, L. ; Martins, B. [UNESP]
Data: 2020
Identificador Persistente: http://hdl.handle.net/11449/201268
Origem: Oasisbr
Made available in DSpace on 2020-12-12T02:28:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01
Asteroid families are groups of objects sharing similar orbits. They are mostly the results of past collisions between two asteroids. Recent studies have shown that some asteroid families can also be the outcome of the spin-up-induced fission of a critically rotating parent body (fission clusters). In at least four young fission clusters, more than 5% of their members belong to subfamilies, secondary clusters of objects mostly formed after the main fission event. However, asteroidal subfamilies are still not well characterized. In this work, using family recognition methods based on time-reversal dynamical simulations, machine-learning clustering algorithms and the exceptional orbit accuracy obtained from Gaia observations of Solar System objects, we identify several subclusters within four extremely young collisional families. We find that collisional asteroid families younger than 100 Myr have a higher fraction of young detectable fission subclusters with respect to older groups. The collisional events that form asteroid families may trigger a subsequent cascade of spin-induced formations of fission clusters by producing fragments in highly rotating states.
São Paulo State University (UNESP) School of Natural Sciences and Engineering
Université de la Côte d’Azur Observatoire de la Côte d’Azur (CNRS) Laboratoire Lagrange
National Space Research Institute (INPE) Division of Space Mechanics and Control
Federal University of São Paulo (UNIFESP) Science and Technology Institute
São Paulo State University (UNESP) School of Natural Sciences and Engineering