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.
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The data that support the plots within this paper and other findings of this study either are available in the paper and in its supplementary tables, or are available from the corresponding author on reasonable request.
The machine-learning codes used in this work are available in the GitHub repository under an MIT public license (https://github.com/valeriocarruba/Natastron). The source code for the symplectic integrator used for the numerical simulation of the asteroid orbits is part of the SWIFT package, which can be obtained at https://www.boulder.swri.edu/~hal/swift.html. Any other codes or data presented in this paper can be obtained from the corresponding author on reasonable request.
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We would like to thank the São Paulo State Science Foundation (FAPESP), which supported this work via grant 18/20999-6, and the Brazilian National Research Council (CNPq, grants 301577/2017-0, 153683/2018-0). The work of F.S. is supported by the CNES fellowship research programme. We are grateful for useful discussion with E. R. De Oliveira on the use of machine-learning algorithms in dynamical astronomy, to D. Nesvorný and O. Winter for comments on a revised version of this manuscript and to D. Vokrouhlický for many helpful discussions on young asteroid families. We also thank AstDyS (https://newton.spacedys.com/astdys/, ref. 1) for the use of data. This publication also makes use of data products from the Wide-field Infrared Survey Explorer (WISE) and Near-Earth Objects (NEOWISE), which are a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This work used data from the European Space Agency mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Finally, this research has also made use of data and/or services provided by the International Astronomical Union’s Minor Planet Center.
The authors declare no competing interests.
Peer review information Nature Astronomy thanks Apostolos Christou and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Carruba, V., Spoto, F., Barletta, W. et al. The population of rotational fission clusters inside asteroid collisional families. Nat Astron 4, 83–88 (2020). https://doi.org/10.1038/s41550-019-0887-8