$i(cm)z$, a semi-analytic model for the thermodynamic properties in galaxy clusters: calibrations with mass and redshift, and implication for the hydrostatic bias

Abstract

In the self-similar scenario for galaxy cluster formation and evolution, the thermodynamic properties of the X-ray emitting plasma can be predicted in their dependencies on the halo mass and redshift only. However, several departures from this simple self-similar scenario have been observed. We show how our semi-analytic model $i(cm)z$, which modifies the self-similar predictions through two temperature-dependent quantities, the gas mass fraction $f_g=f_0 T^{f_1} E_z^{f_z}$ and the temperature variation $f_T=t_0 T^{t_1} E_z^{t_z}$, can be calibrated to incorporate the mass and redshift dependencies. We used a published set of 17 scaling relations to constrain the parameters of the model. We were subsequently able to make predictions as to the slope of any observed scaling relation within a few percent of the central value and about one $\sigma$ of the nominal error. Contextually, the evolution of these scaling laws was also determined, with predictions within $1.5 \sigma$ and within 10 percent of the observational constraints. Relying on this calibration, we have also evaluated the consistency of the predictions on the radial profiles with some observational datasets. For a sample of high-quality data (X-COP), we were able to constrain a further parameter of the model, the hydrostatic bias $b$. By calibrating the model, we have determined that (i) the slopes of the temperature dependence are $f_1=0.403 (\pm0.009)$ and $t_1=0.144 (\pm0.017)$; and that (ii) the dependence upon $E_z$ are constrained to be $f_z=-0.004 (\pm 0.023)$ and $t_z=0.349 (\pm 0.059)$. These values permit one to estimate directly how the normalizations of a given quantity $Q_{\Delta}$ changes as a function of the mass (or temperature) and redshift halo in the form $Q_{\Delta} \sim M^{a_M} E_z^{a_z} \sim T^{a_T} E_z^{a_{Tz}}$, in very good agreement with the current observational constraints.