Orateur
Alessandra Celletti
(Università Tor Vergata, Roma)
Description
We consider two problems relying on perturbative methods in Celestial Mechanics: the computation of proper elements for the space debris problem and effective stability estimates close to resonances in rotational dynamics.
We show that perturbative methods can be integrated with Machine Learning techniques, specifically to investigate the dynamics of groups of objects for the classification and clustering of space debris generated by break-up events of artificial satellites.
We use Nekhoroshev-like estimates to provide effective stability bounds close to resonances in the the spin-orbit problem, described by a 1D time-dependent Hamiltonian, and the spin-spin-orbit model, described by a 2D time-dependent Hamiltonian.
