Influence of Projection in Cluster Cosmology Studies

TL;DR

This paper investigates how projection effects in galaxy cluster observations bias cosmological parameters and proposes a mixture model to account for non-Gaussianity, improving the accuracy of dark energy constraints.

Contribution

It introduces a mixture model for projection effects in cluster cosmology and quantifies their impact on cosmological parameter estimates.

Findings

Projection causes significant biases in Omega_DE and w.

Incorporating additional parameters increases forecast uncertainties.

Knowledge of blending fractions can limit degradation in dark energy constraints.

Abstract

Projection tends to skew the mass-observable relation of galaxy clusters by creating a small fraction of severely blended systems, those for which the measured observable property of a cluster is strongly boosted relative to the value of its primary host halo. We examine the bias in cosmological parameter estimates caused by incorrectly assuming a Gaussian (projection-free) mass-observable relation when the true relation is non-Gaussian due to projection. We introduce a mixture model for projection and explore Fisher forecasts for a survey of 5000 sq. deg. to z=1.1 and an equivalent mass threshold of 10^13.7 h^-1 solar masses. Using a blended fraction motivated by optical cluster finding applied to the Millennium Simulation and applying Planck and otherwise weak priors, we find that the biases in Omega_DE and w are significant, being factors of 2.8 and 2.4, respectively, times previous forecast uncertainties. Incorporating eight new degrees of freedom to describe cluster selection with projection increases the forecast uncertainty in Omega_DE and w by similar factors. Knowledge of these additional parameters at the 5% level limits degradation in dark energy constraints to <10% relative to projection-free forecasts. We discuss strategies for using simulations and complementary observations to characterize the fraction of blended clusters and their mass selection properties.