Abstract
The analysis of weak gravitational lensing in widefield imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate knowledge of the galaxy mean redshift ⟨z⟩. We investigate the possibility of measuring ⟨z⟩ with an accuracy better than 0.002(1 + z) in ten tomographic bins spanning the redshift interval 0.2 < z < 2.2, the requirements for the cosmic shear analysis of Euclid. We implement a sufficiently realistic simulation in order to understand the advantages and complementarity, as well as the shortcomings, of two standard approaches: the direct calibration of ⟨z⟩ with a dedicated spectroscopic sample and the combination of the photometric redshift probability distribution functions (zPDFs) of individual galaxies. We base our study on the HorizonAGN hydrodynamical simulation, which we analyse with a standard galaxy spectral energy distribution templatefitting code. Such a procedure produces photometric redshifts with realistic biases, precisions, and failure rates. We find that the current Euclid design for direct calibration is sufficiently robust to reach the requirement on the mean redshift, provided that the purity level of the spectroscopic sample is maintained at an extremely high level of > 99.8%. The zPDF approach can also be successful if the zPDF is debiased using a spectroscopic training sample. This approach requires deep imaging data but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the debiasing method and confirm our finding by applying it to realworld weaklensing datasets (COSMOS and KiDS+VIKING450).
Original language  English 

Article number  A117 
Pages (fromto)  121 
Number of pages  21 
Journal  Astronomy and Astrophysics 
Volume  647 
DOIs  
Publication status  Published  1 Mar 2021 
Keywords
 Dark energy
 Galaxies: distances and redshifts
 Methods: statistical
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Data availability statement for 'Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography'.
Ilbert, O. (Creator), Amara, A. (Creator) & Markovic, K. (Creator), EDP Sciences, 1 Mar 2021
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