Optimizing Redshift Distribution Inference through Joint Self-Calibration and Clustering-Redshift Synergy

Accurately characterizing the true redshift (true-\(z\)) distribution of a photometric redshift (photo-\(z\)) sample is critical for cosmological analyses in imaging surveys. Clustering-based techniques, which include clustering-redshift (CZ) and self-calibration (SC) methods--depending on whether e...

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Veröffentlicht in:	arXiv.org 2024-12
Hauptverfasser:	Zheng, Weilun, Chan, Kwan Chuen, Xu, Haojie, Zhang, Le, Song, Ruiyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Calibration Clustering Constraining Inference Optimization Red shift Self calibration Weighting functions
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