Inferring matter density from halo spatial distribution

The current picture of structure formation in cosmology suggests that initially over-dense regions of dark matter collapse to form halos. These halos also host most of the luminous matter like galaxies. However, we cannot trace the dark matter directly since it does not interact with light. Therefore, the relationship between the underlying cosmic density and the presence of halos remain unclear. Understanding this relationship is of immense importance in inferring the cosmic density field. We propose using a forward modeling method based on Bayesian Inference to reconstruct the mass density field of the local universe. This process involves producing an ensemble of initial conditions and evolving them according to the known physical laws to the present day. These evolved densities can then be compared to the observed reality statistically. TO BE CONT’D

Faculty Supervisor:

Michael Hudson

Student:

Partner:

Université Pierre et Marie Curie

Discipline:

Physics

Sector:

Education

University:

University of Waterloo

Program: