The nature of assembly bias - II. Observational properties

Details The nature of assembly bias - II. Observational properties The nature of assembly bias - II. Observational properties

2011-10-27

arxiv.org/abs/1110.6174v2

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

15 pages, 20 figures. Submitted to MNRAS. After comments of referee, we add Table 3 and Figure 4

Scientific paper

We analyse catalogues of galaxies from the Sloan Digital Sky Survey (SDSS) and find a weak but significant assembly-type bias, where old galaxies have a higher clustering amplitude at scales r > 1 Mpc than young galaxies of equal magnitude. When using the definition of age based on the luminosity-weighted stellar age, the difference increases from -19 < M_r < -18 to -22 < M_r < -21 SDSS galaxies, from a 25 percent to a factor of two at r ~ 2.5 Mpc. In contrast, when using the definition based on the Dn4000 index, the clustering amplitude at large scales shows a weaker signal-to-noise for the assembly bias detection. In semi-analytic galaxies the difference in clustering using the stellar age is similar at distances beyond 3 Mpc, but they overpredict the assembly bias found in SDSS galaxies at smaller scales. We then adapt the model presented by Lacerna & Padilla (Paper I) to redefine the overdensity peak height, that traces the assembly bias such that galaxies in equal density peaks show the same clustering regardless of their age, but this time using observational features. The proxy of peak height for observational data consists in the luminosity inside cylinders of different radii centred in each galaxy. This radius is parameterized as a function of stellar age and magnitude M_r. The best-fitting set of parameters that make the assembly bias practically absent for both simulated and real galaxies are similar (a=0.75, b=-0.36 and a=1, b=-0.36, respectively). Even though in this case we consider neighbour galaxies in cylinders in contrast to using a smooth density field, e.g. the dark matter particles distribution, our simulations show that the new method is correlated to the definition of Paper I as both measure the crowding around objects that traces the assembly bias effect.

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