PIRSA:20020021

Inferring dark matter velocities from simulations and Gaia data

APA

Bozorgnia, N. (2020). Inferring dark matter velocities from simulations and Gaia data. Perimeter Institute for Theoretical Physics. https://pirsa.org/20020021

MLA

Bozorgnia, Nassim. Inferring dark matter velocities from simulations and Gaia data. Perimeter Institute for Theoretical Physics, Feb. 19, 2020, https://pirsa.org/20020021

BibTex

          @misc{ scivideos_PIRSA:20020021,
            doi = {10.48660/20020021},
            url = {https://pirsa.org/20020021},
            author = {Bozorgnia, Nassim},
            keywords = {Other Physics},
            language = {en},
            title = {Inferring dark matter velocities from simulations and Gaia data},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2020},
            month = {feb},
            note = {PIRSA:20020021 see, \url{https://scivideos.org/index.php/pirsa/20020021}}
          }
          

Nassim Bozorgnia York University

Talk numberPIRSA:20020021
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

High resolution hydrodynamic simulations of galaxy formation are powerful tools, which can provide important information on the properties of the dark matter halo. Combined with the information obtained from the second data release of the Gaia satellite, simulations can significantly improve our understanding of the dark matter distribution in the Solar neighborhood. Determining the local dark matter velocity distribution is crucial for the correct analysis and interpretation of data from dark matter direct detection experiments. I will discuss the local dark matter distribution of Milky Way-like galaxies extracted from state-of-the-art hydrodynamic simulations, and present an analysis of direct detection data using this distribution. I will also discuss the properties of the dark matter component of the radially anisotropic stellar population recently discovered in the Gaia data, using the Auriga simulations. In particular, I will present the local dark matter density and velocity distributions of the simulated Milky Way-like galaxies with and without the anisotropic substructure, and discuss their implications for dark matter direct detection.