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The halo model as a versatile tool to predict intrinsic alignments.

Authors :
Fortuna, Maria Cristina
Hoekstra, Henk
Joachimi, Benjamin
Johnston, Harry
Chisari, Nora Elisa
Georgiou, Christos
Mahony, Constance
Source :
Monthly Notices of the Royal Astronomical Society. Feb2021, Vol. 501 Issue 2, p2983-3002. 20p.
Publication Year :
2021

Abstract

Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for Stage-III and Stage-IV cosmic shear surveys. We account for the different IA signatures at large and small scales, as well as for the different contributions from central/satellite and red/blue galaxies, and we use realistic mocks to account for the characteristics of the galaxy populations as a function of redshift. We inform our model using the most recent observational findings: we include a luminosity dependence at both large and small scales and a radial dependence of the signal within the halo. We predict the impact of the total IA signal on the lensing angular power spectra, including the current uncertainties from the IA best-fits to illustrate the range of possible impact on the lensing signal: the lack of constraints for fainter galaxies is the main source of uncertainty for our predictions of the IA signal. We investigate how well effective models with limited degrees of freedom can account for the complexity of the IA signal. Although these lead to negligible biases for Stage-III surveys, we find that, for Stage-IV surveys, it is essential to at least include an additional parameter to capture the redshift dependence. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00358711
Volume :
501
Issue :
2
Database :
Academic Search Index
Journal :
Monthly Notices of the Royal Astronomical Society
Publication Type :
Academic Journal
Accession number :
148344681
Full Text :
https://doi.org/10.1093/mnras/staa3802