Clustering properties of a type-selected volume-limited sample of galaxies in the CFHTLS

TL;DR

This study analyzes the clustering behavior of galaxies across different redshifts, luminosities, and spectral types using a large photometric redshift dataset, revealing how galaxy clustering varies with these properties.

Contribution

It provides a detailed analysis of galaxy clustering dependence on luminosity, spectral type, and redshift using a large, volume-limited galaxy sample from CFHTLS.

Findings

Clustering length decreases from z~0.3 to z~1.

Redder galaxies have 2-3 times higher clustering amplitudes.

Clustering amplitude for bright red and blue galaxies remains constant with redshift.

Abstract

(abridged) We present an investigation of the clustering of i'AB<24.5 galaxies in the redshift interval 0.2<z<1.2. Using 100,000 precise photometric redshifts in the four ultra-deep fields of the Canada-France Legacy Survey, we construct a set of volume-limited galaxy catalogues. We study the dependence of the amplitude and slope of the galaxy correlation function on absolute B-band rest-frame luminosity, redshift and best-fitting spectral type. We find: 1. The comoving correlation length for all galaxies decreases steadily from z~0.3 to z~1. 2. At all redshifts and luminosities, galaxies with redder rest-frame colours have clustering amplitudes between two and three times higher than bluer ones. 3. For bright red and blue galaxies, the clustering amplitude is invariant with redshift. 4. At z~0.5, less luminous galaxies have higher clustering amplitudes of around 6 h-1 Mpc. 5. The relative bias between galaxies with red and blue rest-frame colours increases gradually towards fainter absolute magnitudes. One of the principal implications of these results is that although the full galaxy population traces the underlying dark matter distribution quite well (and is therefore quite weakly biased), redder, older galaxies have clustering lengths which are almost invariant with redshift, and by z~1 are quite strongly biased.