Clustering Properties of restframe UV selected galaxies II: Migration of Star Formation sites with cosmic time from GALEX and CFHTLS
Sebastien Heinis, Bruno Milliard, Stephane Arnouts, Jeremy Blaizot,, David Schiminovich, Tamas Budavari, Olivier Ilbert, Marie Treyer, Ted K., Wyder, Henry J. McCracken, Tom A. Barlow, Karl Forster, Peter G. Friedman, D., Christopher Martin, Patrick Morrissey, Susan G. Neff

TL;DR
This study examines how the sites of star formation in UV-selected galaxies migrate over cosmic time, revealing a shift from high-mass to low-mass dark matter halos from high to low redshift, supporting the downsizing scenario.
Contribution
It provides the first direct comparison of galaxy clustering and star formation migration across different redshifts using consistent UV-selected samples.
Findings
Bias parameter declines from >2 at high redshift to ~0.79 at low redshift.
Star formation shifts from high-mass to low-mass dark matter halos over time.
Supports the downsizing model of galaxy evolution.
Abstract
We analyze the clustering properties of ultraviolet selected galaxies by using GALEX-SDSS data at z<0.6 and CFHTLS deep u' imaging at z=1. These datasets provide a unique basis at z< 1 which can be directly compared with high redshift samples built with similar selection criteria. We discuss the dependence of the correlation function parameters (r0, delta) on the ultraviolet luminosity as well as the linear bias evolution. We find that the bias parameter shows a gradual decline from high (b > 2) to low redshift (b ~ 0.79^{+0.1}_{-0.08}). When accounting for the fraction of the star formation activity enclosed in the different samples, our results suggest that the bulk of star formation migrated from high mass dark matter halos at z>2 (10^12 < M_min < 10^13 M_sun, located in high density regions), to less massive halos at low redshift (M_min < 10^12 M_sun, located in low density…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · Gamma-ray bursts and supernovae
