KiDS-Legacy: Redshift distributions and their calibration
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2025
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| author | Wright, Angus H. Hildebrandt, Hendrik Busch, Jan Luca van den Bilicki, Maciej Heymans, Catherine Joachimi, Benjamin Mahony, Constance Reischke, Robert Stölzner, Benjamin Wittje, Anna Asgari, Marika Chisari, Nora Elisa Dvornik, Andrej Georgiou, Christos Giblin, Benjamin Hoekstra, Henk Jalan, Priyanka William, Anjitha John Joudaki, Shahab Kuijken, Konrad Lesci, Giorgio Francesco Li, Shun-Sheng Linke, Laila Loureiro, Arthur Maturi, Matteo Moscardin, Lauro Porth, Lucas Radovich, Mario Tröster, Tilman von Wietersheim-Kramsta, Maximilian Yan, Ziang Yoon, Mijin Zhang, Yun-Hao |
| author_facet | Wright, Angus H. Hildebrandt, Hendrik Busch, Jan Luca van den Bilicki, Maciej Heymans, Catherine Joachimi, Benjamin Mahony, Constance Reischke, Robert Stölzner, Benjamin Wittje, Anna Asgari, Marika Chisari, Nora Elisa Dvornik, Andrej Georgiou, Christos Giblin, Benjamin Hoekstra, Henk Jalan, Priyanka William, Anjitha John Joudaki, Shahab Kuijken, Konrad Lesci, Giorgio Francesco Li, Shun-Sheng Linke, Laila Loureiro, Arthur Maturi, Matteo Moscardin, Lauro Porth, Lucas Radovich, Mario Tröster, Tilman von Wietersheim-Kramsta, Maximilian Yan, Ziang Yoon, Mijin Zhang, Yun-Hao |
| contents | 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 (SOM) 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 validate our colour-based redshift distribution estimates with spectroscopic cross-correlations (CC). We find that improvements to our cross-correlation 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_19440 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | KiDS-Legacy: Redshift distributions and their calibration Wright, Angus H. Hildebrandt, Hendrik Busch, Jan Luca van den Bilicki, Maciej Heymans, Catherine Joachimi, Benjamin Mahony, Constance Reischke, Robert Stölzner, Benjamin Wittje, Anna Asgari, Marika Chisari, Nora Elisa Dvornik, Andrej Georgiou, Christos Giblin, Benjamin Hoekstra, Henk Jalan, Priyanka William, Anjitha John Joudaki, Shahab Kuijken, Konrad Lesci, Giorgio Francesco Li, Shun-Sheng Linke, Laila Loureiro, Arthur Maturi, Matteo Moscardin, Lauro Porth, Lucas Radovich, Mario Tröster, Tilman von Wietersheim-Kramsta, Maximilian Yan, Ziang Yoon, Mijin Zhang, Yun-Hao Cosmology and Nongalactic Astrophysics 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 (SOM) 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 validate our colour-based redshift distribution estimates with spectroscopic cross-correlations (CC). We find that improvements to our cross-correlation 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. |
| title | KiDS-Legacy: Redshift distributions and their calibration |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2503.19440 |