Estimating Cosmological Parameters and Cluster Masses through Escape Velocity Measurements in Galaxy Clusters.

Abstract

Galaxy clusters are large virialized structures that exist at the intersection of filaments of matter that make up the cosmic web. Due to their hierarchical growth history, they are excellent probes of the cosmology that governs our universe. Here, we aim to use clusters to better constrain cosmological parameters by systematically studying the uncertainties on galaxy cluster mass estimation for use in a halo mass function analysis. We find that the caustic technique is capable on average of recovering unbiased cluster masses to within 30% for well sampled systems. We also quantify potential statistical and systematic biases due to observational challenges. To address statistical biases in the caustic technique, we developed a new stacking algorithm to measure the average cluster mass for a single stack of projected cluster phase-spaces. By varying the number of galaxies and number of clusters we stack, we find that the single limited value is the total number of galaxies in the stack opening up the possibility for self-calibrated mass estimates of low mass or poorly sampled clusters in large surveys. We then utilize the SDSS-C4 catalog of galaxy clusters to place some of the tightest galaxy cluster based constraints on the matter density and power spectrum normalization for matter in our universe.