PIRSA:16010079

Video URL

https://pirsa.org/16010079

Fast and Accurate Mocks: Getting the Most from Large Scale Structure Surveys

Alvarez, M. (2016). Fast and Accurate Mocks: Getting the Most from Large Scale Structure Surveys. Perimeter Institute for Theoretical Physics. https://pirsa.org/16010079

Alvarez, Marcelo. Fast and Accurate Mocks: Getting the Most from Large Scale Structure Surveys. Perimeter Institute for Theoretical Physics, Jan. 21, 2016, https://pirsa.org/16010079 

          @misc{ scivideos_PIRSA:16010079,
            doi = {10.48660/16010079},
            url = {https://pirsa.org/16010079},
            author = {Alvarez, Marcelo},
            keywords = {Strong Gravity},
            language = {en},
            title = {Fast and Accurate Mocks: Getting the Most from Large Scale Structure Surveys},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2016},
            month = {jan},
            note = {PIRSA:16010079 see, \url{https://scivideos.org/index.php/pirsa/16010079}}
          }

Marcelo Alvarez Canadian Institute for Theoretical Astrophysics (CITA)

Talk numberPIRSA:16010079
DOI10.48660/16010079
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

Generation of accurate mock observations tailored specifically to upcoming surveys such as Advanced ACT, CHIME, and LSST is a key technical challenge in cosmology. Traditional approaches involving N-body simulation are fraught with difficulties due to increasingly large survey volumes and depths. Typically, statistical ensembles can only be realized for a few carefully-chosen parameters, limiting exploration to a significantly restricted cosmological model space. We have developed a new massively parallel algorithm to generate accurate halo masses and positions in a fraction (~1e-3 to 1e-2) of the time taken by N-body simulations. I will present a suite of simulated full sky cluster Sunyaev-Zel’dovich maps that have been produced with this approach, and describe the types of virtual large scale structure observations that are now within reach in the coming years.