Video URL
https://pirsa.org/24050075Joint modeling of astrophysical systematics for cosmological surveys
APA
Sarcevic, N. (2024). Joint modeling of astrophysical systematics for cosmological surveys. Perimeter Institute for Theoretical Physics. https://pirsa.org/24050075
MLA
Sarcevic, Nikolina. Joint modeling of astrophysical systematics for cosmological surveys. Perimeter Institute for Theoretical Physics, May. 14, 2024, https://pirsa.org/24050075
BibTex
@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/index.php/pirsa/24050075}} }
Niko Sarcevic Newcastle University
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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