- Center for Computational Astrophysics
- | Columbia University
- | Lawrence Berkeley National Lab
- | Harvard University
- | Stockholm University
- | Institute D'Astrophysique de Paris
- | Université de Montreal
- | Princeton University
- | Carnegie Mellon University
- | Max-Planck Institute for Astrophysics
Learning the Universe is a Simons Collaboration with the following goals: 1) develop physically grounded models for galaxy evolution using multiscale simulations 2) build new tools to create detailed ‘synthetic observations’ based on simulations 3) develop machine learning-based techniques to accelerate forward modeling of cosmological galaxy formation simulations 4) incorporate these new accelerated forward models into traditional and implicit likelihood inference frameworks and use observational data to constrain cosmological parameters, the initial conditions of the Universe, and the uncertainties of galaxy formation modeling.
Simons Collaborations bring together groups of outstanding scientists to address topics of fundamental scientific importance in which a significant new development has created a novel area for exploration in an established field. To view all Simons Collaborations go here.