Speaker:
Phil Armitage
(Stony Brook University, Center for Computational Astrophysics, Flatiron Institute)
Abstract:
Searches for extrasolar planets have shown that planetary systems are
not just common, but that they exhibit a broad and mostly unanticipated
diversity of architectures. In this talk I will discuss how we can use
machine learning methods to better characterize observed systems of
close-in planets, and review what we have learnt about the formation and
early evolution of planetary systems. Data on exoplanets, from
observations of protoplanetary disks, and from the New Horizons mission
to the outer Solar System, all motivate novel models in which planet
formation proceeds far faster than was previously suspected. I will
discuss the prospects for improved theoretical and observational tests
of such models.