Forming planetesimals from gravitational collapse

Before planets form, smaller bodies called planetesimals must form. The leading hypothesis for their formation is the gravitational collapse of clouds of approximately pebble-sized objects. Some planetesimals are relicts in the modern Solar System and can serve to test this hypothesis. This project at Michigan State University (MSU) uses novel computer simulations of gravitational collapse to predict planetesimal properties at the end of the process. The collapse process involves of order 10^21 pebbles, and current simulations make such drastic simplifications that they cannot predict with accuracy many planetesimal properties such as shape and spin. The new MSU model will transition between different pebble interactions in different regimes of validity, which allow the final properties to be realistic. The broader impact of this work will be felt through training of students (particularly underrepresented minorities) in STEM. The team will also engage with the MSU community and the public via the MSU Science Festival, MSU Observatory open houses, and public events at Abrams Planetarium. The overall objective of the proposed work is to accurately simulate the gravitational collapse of a pebble cloud using a hybrid N-body model and reproduce observed properties of relict planetesimals in the solar system. The new hybrid N-body model combines the best aspects of existing perfect merger and soft-sphere discrete element methods in order to simulate the gravitational collapse process. The project maps independent variables such as cloud rotation state, internal mass distribution, and model contact physics to dependent variables such as final planetesimal mass, shape, spin, and bound multiple system (i.e., binary) properties. The physical parameters in the protoplanetary disk thus might be inferred from the distribution of those properties. The group will train a graduate student and six undergraduate students (recruited directly from the MSU Drew Scholars program) with important STEM skills such as high-performance computing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.