Clustering of CODEX clusters

Kavli Affiliate: Eli Rykoff

| First 5 Authors: Valtteri Lindholm, Alexis Finoguenov, Johan Comparat, Charles C. Kirkpatrick, Eli Rykoff

| Summary:

Aims. We analyze the autocorrelation function of a large contiguous sample of
galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which
we take particular care of cluster definition. These clusters were X-ray
selected using the RASS survey and then identified as galaxy clusters using the
code redMaPPer run on the photometry of the SDSS. We develop methods for
precisely accounting for the sample selection effects on the clustering and
demonstrate their robustness using numerical simulations. Methods. Using the
clean CODEX sample, which was obtained by applying a redshift-dependent
richness selection, we computed the two-point autocorrelation function of
galaxy clusters in the $0.1<z<0.3$ and $0.3<z<0.5$ redshift bins. We compared
the bias in the measured correlation function with values obtained in numerical
simulations using a similar cluster mass range. Results. By fitting a power
law, we measured a correlation length $r_0=18.7 pm 1.1$ and slope $gamma=1.98
pm 0.14$ for the correlation function in the full redshift range. By fixing
the other cosmological parameters to their WMAP9 values, we reproduced the
observed shape of the correlation function under the following cosmological
conditions: $Omega_{m_0}=0.22^{+0.04}_{-0.03}$ and $S_8=sigma_8 (Omega_{m_0}
/0.3)^{0.5}=0.85^{+0.10}_{-0.08}$ with estimated additional systematic errors
of $sigma_{Omega_{m_0}} = 0.02$ and $sigma_{S_8} = 0.20$. We illustrate the
complementarity of clustering constraints by combining them with CODEX
cosmological constraints based on the X-ray luminosity function, deriving
$Omega_{m_0} = 0.25 pm 0.01$ and $sigma_8 = 0.81^{+0.01}_{-0.02}$ with an
estimated additional systematic error of $sigma_{Omega_{m_0}} = 0.07$ and
$sigma_{sigma_8} = 0.04$. The mass calibration and statistical quality of the
mass tracers are the dominant source of uncertainty.

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