Angular clustering and bias of photometric quasars in the Kilo-Degree Survey Data Release 4
Anjitha John William, Maciej Bilicki, Wojciech A. Hellwing, Szymon J. Nakoneczny, and Priyanka Jalan

TL;DR
This study measures the angular clustering and bias of photometric quasars in KiDS DR4, using deep learning-based redshift estimates, revealing their dark matter halo properties and emphasizing the importance of redshift calibration.
Contribution
First application of KiDS-selected quasars for cosmology, providing updated redshifts, clustering measurements, and bias estimates across redshift bins.
Findings
Quasars' bias increases from 1.6 to 4.0 with redshift.
Quasars reside in dark matter halos of mass ~10^12.7 to 10^12.9 M_sun.
Redshift distribution assumptions significantly affect bias estimates.
Abstract
We investigate the angular clustering and effective bias of photometrically selected quasars in the Kilo-Degree Survey Data Release 4 (KiDS DR4). We update the previous photometric redshifts (photo-s) of the KiDS quasars using Hybrid-z, a deep learning framework combining four-band KiDS images and nine-band KiDS+VIKING magnitudes. Hybrid-z is trained on the latest Dark Energy Spectroscopic Instrument (DESI) DR1 and Sloan Digital Sky Survey (SDSS) DR17 quasars matching with KiDS, and achieves average bias and scatter on a test sample. The updated catalog of quasars over is divided into four tomographic bins spanning . In each bin, we measure the angular two-point correlation function and compare it with theoretical predictions for dark matter clustering. We…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · Cosmology and Gravitation Theories
