Résumé / Abstract Seminaire_GReCO

"Biases on cosmological parameter estimators from galaxy cluster number counts"

Mariana Penna Lima

The abundance of galaxy clusters is becoming a standard cosmological probe. In particular, Sunyaev-Zel’dovich (SZ) surveys are promising probes of the Dark Energy equation of state, given their ability to find distant clusters and provide estimates for their mass. However, current SZ catalogs contain tens to hundreds of objects. In this case, it is not guaranteed that maximum likelihood estimators of cosmological parameters are unbiased. In this presentation we show the study of estimators from cluster abundance for some cosmological parameters. We use the Monte Carlo approach to determine the presence of bias and its behavior with both area and depth of the survey, and the number of cosmological parameters fitted simultaneously. Our fiducial models are based on the South Pole Telescope SZ survey. Assuming perfect knowledge on mass and redshift, we obtain that some estimators have non negligible biases. For example, the bias of sigma_8 corresponds to 37% of its statistical error bar when it is fitted together with the cold dark matter density parameter Omega_c and the dark energy equation of state parameter w_0. Including mass and redshift uncertainties, decreases the relevance of the bias in comparison with the error bars. Considering a joint likelihood for cluster abundance and distance priors from the cosmic microwave background, we obtain that, in most cases, the biases are negligible compared to the statistical error bars. Finally, we compute the error bars of Omega_c, sigma_8, and w_0 using Fisher matrix and profile likelihood approaches, showing that they are compatible with the Monte Carlo ones. The results of this work validate the use of the current maximum likelihood methods for cluster abundance.

lundi 24 février 2014 - 11:00
Salle des séminaires Évry Schatzman,
Institut d'Astrophysique de Paris

Page web du séminaire / Seminar's webpage