Project Description: The large-scale structure of the Universe can be used to measure and constrain cosmological parameters and models. This large-scale structure is dominated by dark matter and energy with a relatively small contribution from baryonic (ordinary) matter. However, at small scales baryonic processes such as feedback from star formation and active galactic nuclei can significantly impact the cosmological distribution of matter. Therefore, to include such small scales in cosmological measurements it is critical to develop robust and efficient models of baryonic effects. The Space Grant intern will help to develop such a model and apply it to a variety of cosmological lensing observables. This will involve surveying the existing literature on baryonification, developing simplified versions of existing baryonic effects models using machine learning methods, and validating these models with cosmological hydrodynamical simulations.
NASA Relevance: This research is on modeling cosmological baryonic effects to enable robust inference of cosmological parameters from survey data. This is directly relevant to fully exploiting the data that will be available from existing and upcoming NASA missions such as the Roman Space Telescope.
Work Description: Surveying the literature on cosmological models of baryonic effects. Using linear algebra (e.g. PCA) or machine learning methods to simplify existing models of baryonic effects. Measuring relevant quantities in hydrodynamical simulations to test our simplified baryonic effect models.
Open or Reserved Project: 1 position reserved, 2 positions total