A Consistent Comparison of Bias Models using Observational Data

Details A Consistent Comparison of Bias Models using Observational Data A Consistent Comparison of Bias Models using Observational Data

2012-01-23

arxiv.org/abs/1201.4878v1

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

MNRAS in press, 12 pages, 6 color figures, 4 tables

Scientific paper

We investigate five different models for the dark matter halo bias, ie., the ratio of the fluctuations of mass tracers to those of the underlying mass, by comparing their cosmological evolution using optical QSO and galaxy bias data at different redshifts, consistently scaled to the WMAP7 cosmology. Under the assumption that each halo hosts one extragalactic mass tracer, we use a $\chi^2$ minimization procedure to determine the free parameters of the bias models as well as to statistically quantify their ability to represent the observational data. Using the Akaike information criterion we find that the model that represents best the observational data is the Basilakos & Plionis (2001; 2003) model with the tracer merger extension of Basilakos, Plionis & Ragone-Figueroa (2008) model. The only other statistically equivalent model, as indicated by the same criterion, is the Tinker et al. (2010) model. Finally, we find an average, over the different models, dark matter halo mass that hosts optical QSOs of: $M_h\simeq 2.7 (\pm 0.6) \times 10^{12} h^{-1} M_{\odot}$, while the corresponding value for optical galaxies is: $M_h\simeq 6.3 (\pm 2.1) \times 10^{11} h^{-1} M_{\odot}$.

Affiliated with

Also associated with

No associations

Rating

A Consistent Comparison of Bias Models using Observational Data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Consistent Comparison of Bias Models using Observational Data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Consistent Comparison of Bias Models using Observational Data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-105332