Seminário GDOP

Data: 29/04/2022
Horário: 14h00.
Local: apresentação remota.

Large observational surveys, like those that will be conducted at the Vera C. Rubin Observatory, are expected to discover up to one million new asteroids in the first year of operation. This will more than double the database of known asteroids in a very short time. New methods and techniques will be needed to handle the large influx of data. Here, we tested some of these new methods by studying the population of asteroids on stable orbits inside the ${\nu}_6$ secular resonance. This resonance is one of the strongest mechanisms for destabilizing the orbits of main-belt bodies and producing Near-Earth Asteroids (NEAs). Yet, stable orbital configurations where the asteroid pericenter is either aligned or anti-aligned with that of Saturn exist inside the resonance. The population of stable ${\nu}_6$ resonators, first discovered in the early 2010s, is now the largest population of asteroids in stable orbits inside a secular resonance.
Here we obtained the largest sample of asteroids’ proper elements for numbered and multi-opposition objects most likely to be affected by the resonance. Artificial Neural Networks (ANN) were then used to identify the images of resonant angles of asteroids in stable orbits, more than doubling their number. Clustering methods and the use of machine learning algorithms allowed the identification of the known asteroid families crossed by the ${\nu}_6$  resonance, the Tina, Euphrosyne, and Svea clusters, and of two entirely new groups: the Tiffanykapler and the 138605 QW177 families.