Image Classification of Retrograde Resonance in the Planar Circular Restricted Three-Body Problem

Kurzfassung

The advancement of computational techniques and methods such as artificial intelligence applied to celestial mechanics, including image classification. These techniques have been applied in the identification of mean motion resonances for asteroids (Smirnov and Markov, 2017; Carruba et al., 2021) and secular resonances for asteroids Carruba et al. (2022). The rapid growth of machine learning methods applications enables us to leverage these tools for the investigation of dynamical systems such as asteroid and planetary dynamics.In the restricted three-body problem (R3BP), prograde orbits are those with an inclination less than 90 degrees with respect to the orbital plane of the perturber. Retrograde orbits are defined is this case with an inclination higher than 90 degrees (Morais and Namouni, 2017). These retrograde orbits can occur due to a range of astronomical events, such as collisions, close encounters and dissipation. This study aims to present a machine learning image classification method in order to search for periodic and quasi-periodic orbits, for example, retrograde orbits in the R3BP