2008/03/31 by Hao‐Yi Wu, Hao-Yi Wu, Eduardo Rozo +1
Mathematics · Physics and Astronomy · #Amplitude #Astronomy and Astrophysical Research #Astrophysics #Calibration #Cluster (spacecraft) #Cluster analysis #Computer science #Cosmology #Dark matter #Galaxies: Formation, Evolution, Phenomena #Galaxy #Galaxy cluster #Halo #Halo effect #Mathematics #Observable #Optics #Physics #Statistics #Stellar, planetary, and galactic studies #astro-ph
paper · pdf · doi:10.1086/591929
published as Astrophys.J.688:729-741, 2008 · 13 pages, 5 figures, replaced to match published version
openalex publication_date 2008/11/17 · arxiv created 2008/11/19 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Self-calibration techniques for analyzing galaxy cluster counts utilize the abundance and the clustering amplitude of dark matter halos. These properties simultaneously constrain cosmological parameters and the cluster observable-mass relation. It was recently discovered that the clustering amplitude of halos depends not only on the halo mass, but also on various secondary variables, such as the halo formation time and the concentration; these dependences are collectively termed "assembly bias." Applying modified Fisher matrix formalism, we explore whether these secondary variables have a significant impact on the study of dark energy properties using the self-calibration technique in current (SDSS) and the near future (DES, SPT, and LSST) cluster surveys. The impact of the secondary dependence is determined by (1) the scatter in the observable-mass relation and (2) the correlation between observable and secondary variables. We find that for optical surveys, the secondary dependence does not significantly influence an SDSS-like survey; however, it may affect a DES-like survey (given the high scatter currently expected from optical clusters) and an LSST-like survey (even for low scatter values and low correlations). For an SZ survey such as SPT, the impact of secondary dependence is insignificant if the scatter is 20% or lower but can be enhanced by the potential high scatter values introduced by a highly correlated background. Accurate modeling of the assembly bias is necessary for cluster self-calibration in the era of precision cosmology.