# Calibrating the Planck Cluster Mass Scale with Cluster Velocity Dispersions

## TL;DR

This study measures the Planck cluster mass bias using galaxy velocity dispersions, correcting for biases, and finds results consistent with previous weak lensing estimates, highlighting the impact of velocity bias uncertainties.

## Contribution

The paper provides a dynamical mass measurement of Planck clusters via velocity dispersions and explores the dependence of mass bias on galaxy velocity bias, offering insights into calibration.

## Key findings

- Mass bias parameter (1-b) is approximately 0.64 with 17% error.
- Results are consistent with previous weak lensing measurements.
- Uncertainty in velocity bias limits precision in mass bias determination.

## Abstract

We measure the Planck cluster mass bias using dynamical mass measurements based on velocity dispersions of a subsample of 17 Planck-detected clusters. The velocity dispersions were calculated using redshifts determined from spectra obtained at Gemini observatory with the GMOS multi-object spectrograph. We correct our estimates for effects due to finite aperture, Eddington bias and correlated scatter between velocity dispersion and the Planck mass proxy. The result for the mass bias parameter, $(1-b)$, depends on the value of the galaxy velocity bias $b_v$ adopted from simulations: $(1-b)=(0.51\pm0.09) b_v^3$. Using a velocity bias of $b_v=1.08$ from Munari et al., we obtain $(1-b)=0.64\pm 0.11$, i.e, an error of 17% on the mass bias measurement with 17 clusters. This mass bias value is consistent with most previous weak lensing determinations. It lies within $1\sigma$ of the value needed to reconcile the Planck cluster counts with the Planck primary CMB constraints. We emphasize that uncertainty in the velocity bias severely hampers precision measurements of the mass bias using velocity dispersions. On the other hand, when we fix the Planck mass bias using the constraints from Penna-Lima et al., based on weak lensing measurements, we obtain a positive velocity bias $b_v \gtrsim 0.9$ at $3\sigma$.