KiDS-Legacy: Redshift distributions and their calibration

We present the redshift calibration methodology and bias estimates for the cosmic shear analysis of the fifth and final data release (DR5) of the Kilo-Degree Survey (KiDS). KiDS-DR5 includes a greatly expanded compilation of calibrating spectra, drawn from 27 square degrees of dedicated optical and near-IR imaging taken over deep spectroscopic fields. The redshift distribution calibration leverages a range of new methods and updated simulations to produce the most precise N(z) bias estimates used by KiDS to date. Improvements to our colour-based redshift distribution measurement method using self-organising maps (SOMs) mean that we are able to use many more sources per tomographic bin for our cosmological analyses and better estimate the representation of our source sample given the available spec-z. We validated our colour-based redshift distribution estimates with spectroscopic cross-correlations (CCs). We find that improvements to our CC redshift distribution measurement methods mean that redshift distribution biases estimated between the SOM and CC methods are fully consistent on simulations, and the data calibration is consistent to better than 2σ in all tomographic bins.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-14
DOI
https://doi.org/10.1051/0004-6361/202554909/pdf
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
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article

KiDS-Legacy: Redshift distributions and their calibration

Springer Link (Chiba Institute of Technology)
Galaxies: Formation, Evolution, Phenomena
article

KiDS-Legacy: Redshift distributions and their calibration

article en

Abstract

We present the redshift calibration methodology and bias estimates for the cosmic shear analysis of the fifth and final data release (DR5) of the Kilo-Degree Survey (KiDS). KiDS-DR5 includes a greatly expanded compilation of calibrating spectra, drawn from 27 square degrees of dedicated optical and near-IR imaging taken over deep spectroscopic fields. The redshift distribution calibration leverages a range of new methods and updated simulations to produce the most precise N(z) bias estimates used by KiDS to date. Improvements to our colour-based redshift distribution measurement method using self-organising maps (SOMs) mean that we are able to use many more sources per tomographic bin for our cosmological analyses and better estimate the representation of our source sample given the available spec-z. We validated our colour-based redshift distribution estimates with spectroscopic cross-correlations (CCs). We find that improvements to our CC redshift distribution measurement methods mean that redshift distribution biases estimated between the SOM and CC methods are fully consistent on simulations, and the data calibration is consistent to better than 2σ in all tomographic bins.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 37%
Galaxies: Formation, Evolution, Phenomena
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