Clustering of red sequence galaxies in the fourth data release of the Kilo-Degree Survey

Author:

Vakili Mohammadjavad,Hoekstra Henk,Bilicki Maciej,Fortuna Maria Cristina,Kuijken Konrad,Wright Angus H.,Asgari Marika,Brown Michael,Dombrovskij Elisabeth,Erben Thomas,Giblin Benjamin,Heymans Catherine,Hildebrandt Hendrik,Johnston Harry,Joudaki Shahab,Kannawadi Arun

Abstract

We present a sample of luminous red sequence galaxies as the basis for a study of the large-scale structure in the fourth data release of the Kilo-Degree Survey. The selected galaxies are defined by a red sequence template, in the form of a data-driven model of the colour-magnitude relation conditioned on redshift. In this work, the red sequence template was built using the broad-band optical+near infrared photometry of KiDS-VIKING and the overlapping spectroscopic data sets. The selection process involved estimating the red sequence redshifts, assessing the purity of the sample and estimating the underlying redshift distributions of redshift bins. After performing the selection, we mitigated the impact of survey properties on the observed number density of galaxies by assigning photometric weights to the galaxies. We measured the angular two-point correlation function of the red galaxies in four redshift bins and constrain the large-scale bias of our red sequence sample assuming a fixed ΛCDM cosmology. We find consistent linear biases for two luminosity-threshold samples (‘dense’ and ‘luminous’). We find that our constraints are well characterised by the passive evolution model.

Funder

Netherlands Organization of Scientific Research

Polish National Science Center

Polish Ministry of Science and Higher 50 Education

UK Science and Technology Facilities Council (STFC) Studentship

European Research Council

Royal Society

Max Planck Society and the Alexander von Humboldt Foundation in the frame work of the Max Planck-Humboldt Research Award

Heisenberg grant of the Deutsche Forschungsgemeinschaft

Beecroft Trust

Publisher

EDP Sciences

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The miniJPAS survey;Astronomy & Astrophysics;2023-10

2. Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite;The Astrophysical Journal;2023-08-18

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