Video URL

https://pirsa.org/21100001

Combining Spectroscopic and Photometric Surveys with the DMASS sample

Lee, S. (2021). Combining Spectroscopic and Photometric Surveys with the DMASS sample. Perimeter Institute for Theoretical Physics. https://pirsa.org/21100001

Lee, Sujeong. Combining Spectroscopic and Photometric Surveys with the DMASS sample. Perimeter Institute for Theoretical Physics, Oct. 12, 2021, https://pirsa.org/21100001 

          @misc{ scivideos_PIRSA:21100001,
            doi = {10.48660/21100001},
            url = {https://pirsa.org/21100001},
            author = {Lee, Sujeong},
            keywords = {Cosmology},
            language = {en},
            title = {Combining Spectroscopic and Photometric Surveys with the DMASS sample},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2021},
            month = {oct},
            note = {PIRSA:21100001 see, \url{https://scivideos.org/pirsa/21100001}}
          }

Sujeong Lee Duke University

DOI 10.48660/21100001
Source Repository PIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

Redshift space distortions and weak gravitational lensing have been used as a powerful combination of growth data to test gravity. In particular, combining these two probes where spectroscopic and photometric surveys overlap, can yield much stronger dark energy and growth constraints than a combination of independent measurements of the two. However, this approach is limited due to a fairly small overlapping area between spectroscopic and photometric surveys. In this talk, I will introduce a new method to optimally combine spectroscopic and photometric surveys, using the DMASS galaxy sample as gravitational lenses. The new approach can extract the full statistical power of photometric surveys beyond the overlapping area. I will illustrate how this approach with DMASS improves cosmological constraints in the frame of modified gravity and will show its application to future surveys having a limited overlap such as DESI and LSST.