The DEEP2 galaxy redshift survey: evolution of the colour–density relation at 0.4 < z < 1.35

By M. Cooper, J. Newman, A. Coil, Darren Croton, B. Gerke, R. Yan, M. Davis, S. Faber, P. Guhathakurta, D. Koo and 2 more. 2006

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Using a sample of 19464 galaxies drawn from the DEEP2 Galaxy Redshift Survey, we study the relationship between galaxy colour and environment at 0.4 1, being larger in regions of greater galaxy density. At all epochs probed, we also find a small population of red, morphologically early-type galaxies residing in regions of low measured overdensity. The observed correlations between the red fraction and local overdensity are highly significant, with the trend at z > 1 detected at a greater than 5σ level. Over the entire redshift regime studied, we find that the colour-density relation evolves continuously, with red galaxies more strongly favouring overdense regions at low z relative to their red-sequence counterparts at high redshift. At z ≥ 1.3, the red fraction only weakly correlates with overdensity, implying that any colour dependence to the clustering of ∼L* galaxies at that epoch must be small. Our findings add weight to existing evidence that the build-up of galaxies on the red sequence has occurred preferentially in overdense environments (i.e. galaxy groups) at z≤ 1.5. Furthermore, we identify the epoch (z ∼ 2) at which typical ∼L* galaxies began quenching and moved on to the red sequence in significant number. The strength of the observed evolutionary trends at 0 < z < 1.35 suggests that the correlations observed locally, such as the morphology-density and colour-density relations, are the result of environment-driven mechanisms (i.e. 'nurture') and do not appear to have been imprinted (by 'nature') upon the galaxy population during their epoch of formation.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition, Ecology

View Paper: https://www.semanticscholar.org/paper/1e47b3131ce81e078c0ed8b01e271af2d4b0906b

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In Astronomy and Astrophysics

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In Computer Vision and Pattern Recognition

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In Ecology

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  6. C. Conroy
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