Constraints on the Optical Depth of Galaxy Groups and Clusters

Abstract

Future data from galaxy redshift surveys, combined with high-resolutions maps of the cosmic microwave background, will enable measurements of the pairwise kinematic Sunyaev-Zel'dovich (kSZ) signal with unprecedented statistical significance. This signal probes the matter-velocity correlation function, scaled by the average optical depth (τ) of the galaxy groups and clusters in the sample, and is thus of fundamental importance for cosmology. However, in order to translate pairwise kSZ measurements into cosmological constraints, external constraints on τ are necessary. In this work, we present a new model for the intracluster medium, which takes into account star formation, feedback, non-thermal pressure, and gas cooling. Our semi-analytic model is computationally efficient and can reproduce results of recent hydrodynamical simulations of galaxy cluster formation. We calibrate the free parameters in the model using recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters. Our observationally calibrated model predicts the average 500 t (i.e., the integrated τ within a disk of size R 500 ) to better than 6% modeling uncertainty (at 95% confidence level). If the remaining uncertainties associated with other astrophysical uncertainties and X-ray selection effects can be better understood, our model for the optical depth should break the degeneracy between optical depth and cluster velocity in the analysis of future pairwise kSZ measurements and improve cosmological constraints with the combination of upcoming galaxy and CMB surveys, including the nature of dark energy, modified gravity, and neutrino mass.

A one-dimensional hydrodynamic model for accretion, cooling, and heating of gas in dark matter haloes from z = 6 to z = 0

“…The thermodynamics of the gas in clusters and groups is interesting to study, particularly with the advent of future galaxy redshift surveys and the measurement of the kinetic and thermal Sunyaev-Zel'dovich signal (Lim et al 2017, Park, Alvarez & Bond 2018, Schaan et al 2016) combined with the existing X-ray observations. In order to test a large number of ICM models and reasonable parametric profiles to compare with new observations, simple semi-analytical models (Flender, Nagai & McDonald 2017 ) are preferred over large scale hydrodynamic simulations. However, our 1D model, with hydrodynamic evolution of baryons, is computationally less expensive.…”

Cross-correlation of the thermal Sunyaev–Zel’dovich effect and weak gravitational lensing: Planck and Subaru Hyper Suprime-Cam first-year data

“…Several analytical prescriptions have been proposed to model theoretically the tSZ effect and the evolution of ICM (e.g., Makino et al 1998;Komatsu & Seljak 2001;Bode et al 2009;Shaw et al 2010;Flender et al 2017). The complexities of highly non-linear ICM physics make it challenging for such models to provide accurate theoretical predictions.…”

Probing cosmology and cluster astrophysics with multiwavelength surveys – I. Correlation statistics

“…This ICM model is the modified version of the one originally proposed in Ostriker et al (2005). The updated features from the original model include a radially-dependent non-thermal pressure component (e.g., turbulence or bulk flows) (Nelson et al 2014b) and gascooling effect in cluster cores to provide a better description of recent X-ray data (Flender et al 2017).…”

“…For the normalization of halo concentration, we take A C = 1 as a baseline model which is consistent with the dark-matter-only N-body prediction by DK15. For the polytropic exponent in the cluster core we refer the best-fit value to recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters as in Flender et al (2017). We also adopt the value of parameters for feedback processes, stellar mass fraction as constrained in Flender et al (2017) and nonthermal pressure as discussed in Nelson et al (2014b).…”

“…For the polytropic exponent in the cluster core we refer the best-fit value to recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters as in Flender et al (2017). We also adopt the value of parameters for feedback processes, stellar mass fraction as constrained in Flender et al (2017) and nonthermal pressure as discussed in Nelson et al (2014b). The parameters for gas clumping are derived from X-ray angular power spectrum measurements from ROSAT All-Sky Survey (Lau et al in prep.).…”