Disentangling correlated scatter in cluster mass measurements
  The challenge of obtaining galaxy cluster masses is increasingly being
addressed by multiwavelength measurements. As scatters in measured cluster
masses are often sourced by properties of or around the clusters themselves,
correlations between mass scatters are frequent and can be significant, with
consequences for errors on mass estimates obtained both directly and via
stacking. Using a high resolution 250 Mpc/h side N-body simulation, combined
with proxies for observational cluster mass measurements, we obtain mass
scatter correlations and covariances for 243 individual clusters along ~96
lines of sight each, both separately and together. Many of these scatters are
quite large and highly correlated. We use principal component analysis (PCA) to
characterize scatter trends and variations between clusters. PCA identifies
combinations of scatters, or variations more generally, which are uncorrelated
or non-covariant. The PCA combination of mass measurement techniques which
dominates the mass scatter is similar for many clusters, and this combination
is often present in a large amount when viewing the cluster along its long
axis. We also correlate cluster mass scatter, environmental and intrinsic
properties, and use PCA to find shared trends between these. For example, if
the average measured richness, velocity dispersion and Compton decrement mass
for a cluster along many lines of sight are high relative to its true mass, in
our simulation the cluster's mass measurement scatters around this average are
also high, its sphericity is high, and its triaxiality is low.
  Our analysis is based upon estimated mass distributions for fixed true mass.
Extensions to observational data would require further calibration from
numerical simulations, tuned to specific observational survey selection
functions and systematics.
