Video URL

https://pirsa.org/24050075

Joint modeling of astrophysical systematics for cosmological surveys

Sarcevic, N. (2024). Joint modeling of astrophysical systematics for cosmological surveys. Perimeter Institute for Theoretical Physics. https://pirsa.org/24050075

Sarcevic, Nikolina. Joint modeling of astrophysical systematics for cosmological surveys. Perimeter Institute for Theoretical Physics, May. 14, 2024, https://pirsa.org/24050075 

          @misc{ scivideos_PIRSA:24050075,
            doi = {10.48660/24050075},
            url = {https://pirsa.org/24050075},
            author = {Sarcevic, Nikolina},
            keywords = {Cosmology},
            language = {en},
            title = {Joint modeling of astrophysical systematics for cosmological surveys},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2024},
            month = {may},
            note = {PIRSA:24050075 see, \url{https://scivideos.org/pirsa/24050075}}
          }

Niko Sarcevic Newcastle University

DOI10.48660/24050075
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

In this talk, I will present a novel framework for modeling the weak lensing source galaxy redshift distribution and galaxy intrinsic alignment via a shared luminosity function. In the context of LSST Year 1 and Year 10 cosmic shear analysis, I demonstrate the significant impact of the luminosity function on source galaxy redshift distributions and intrinsic alignment contamination. I establish the influence of Schechter luminosity function parameters on the redshift distribution of a magnitude-limited sample and show the effects of marginalizing over these parameters in intrinsic alignment modeling. I forecast how this joint modeling approach affects cosmological parameter constraints, finding that it yields constraints comparable to standard analyses while mitigating potential biases from incorrectly fixed luminosity function parameters. I highlight the specific impact of the luminosity function shape on the cosmic shear data vector and discuss the method's potential for modeling generic selection functions and extending to a 3x2pt analysis with galaxy bias incorporation. While focused on LSST cosmic shear, this framework is broadly applicable to weak lensing surveys.

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