Galaxy Cluster Mass Reconstruction Project: II. Quantifying scatter and bias using contrasting mock catalogues
L. Old, R. Wojtak, G. A. Mamon, R. A. Skibba, F. R. Pearce, D. Croton,, S. Bamford, P. Behroozi, R. de Carvalho, J. C. Mu\~noz-Cuartas, D. Gifford,, M. E. Gray, A. von der Linden, M.R. Merrifield, S. I. Muldrew, V. M\"uller,, R. J. Pearson, T. J. Ponman, E. Rozo, E. Rykoff

TL;DR
This study compares 25 galaxy-based cluster mass estimation methods using mock catalogues to evaluate their accuracy, bias, and scatter, providing guidance for cosmological analyses involving galaxy clusters.
Contribution
It systematically quantifies the scatter and bias of various mass estimation techniques across two mock galaxy catalogues, highlighting the effectiveness of richness and abundance matching methods.
Findings
RMS errors range from 0.18 to 1.08 dex across methods.
Richness and abundance matching methods perform best.
Certain methods produce catastrophic mass estimation errors.
Abstract
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the RMS errors in log M200c delivered by the different methods (0.18 to 1.08 dex, i.e., a factor of ~1.5 to 12), with abundance matching and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or over-estimated by a factor greater than 10.…
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