Testing evolution models against population-level data

Develop principled statistical and machine learning approaches to rigorously test theoretical models of planetary system evolution against population-level observational datasets, enabling robust inference even when models and data are well specified.

Background

Despite progress in modeling (e.g., N-body dynamics) and abundant exoplanet demographics, drawing statistically robust conclusions remains challenging. The author points to the need for methods that bridge theory and large datasets, improving the rigor and power of population-level tests of formation and evolution scenarios.