Deep learning classification of asteroids in g-type secular resonances

Abstract

Linear secular resonances happen when there is a commensurability between the precession frequency of the pericenter, g, or longitude of the node, s, of an asteroid and a planet. Non-linear resonances are higherorder combinations of these frequencies. Here, we studied the three most diffusive g−type non-linear secular resonances using Artificial Neural Networks. We identified a population of more than 2100 resonant objects in the g − 2g6 + g5 and g − 3g6 + 2g5 resonances. This allows the creation of a Convolutional Neural Network model for the g − 2g6 + g5 resonance, able to predict the status of several thousands of asteroids in seconds. We identified 12 new possible dynamical groups among the resonant population, including the 5507 and 170776 families, which have both estimated ages of less than 7 My. These are the two first-ever identified young families in resonant configurations of the investigated resonances, which allows setting limits on their original ejection velocity field.