A Monte Carlo study of cosmological parameter estimators from galaxy cluster number counts

Abstract

Models for galaxy clusters abundance and their spatial distribution are sensitive to cosmological parameters. Present and future surveys will provide high-redshift sample of clusters, such as Dark Energy Survey (z ⩽ 1.3), making cluster number counts one of the most promising cosmological probes. In the literature, some cosmological analyses are carried out using small cluster catalogs (tens to hundreds), like in Sunyaev-Zel'dovich (SZ) surveys. However, it is not guaranteed that maximum likelihood estimators of cosmological parameters are unbiased in this scenario. In this work we study different estimators of the cold dark matter density parameter Ω_c, σ₈ and the dark energy equation of state parameter w₀ obtained from cluster abundance. Using an unbinned likelihood for cluster number counts and the Monte Carlo approach, we determine the presence of bias and how it varies with the size of the sample. Our fiducial models are based on the South Pole Telescope (SPT). We show that the biases from SZ estimators do not go away with increasing sample sizes and they may become the dominant source of error for an all sky survey at the SPT sensitivity.