Velocity dispersions of clusters in the Dark Energy Survey Y3 redMaPPer catalogue Academic Article uri icon


  • ABSTRACT We measure the velocity dispersions of clusters of galaxies selected by the red-sequence Matched-filter Probabilistic Percolation (redMaPPer) algorithm in the first three years of data from the Dark Energy Survey (DES), allowing us to probe cluster selection and richness estimation, , in light of cluster dynamics. Our sample consists of 126 clusters with sufficient spectroscopy for individual velocity dispersion estimates. We examine the correlations between cluster velocity dispersion, richness, X-ray temperature, and luminosity, as well as central galaxy velocity offsets. The velocity dispersionrichness relation exhibits a bimodal distribution. The majority of clusters follow scaling relations between velocity dispersion, richness, and X-ray properties similar to those found for previous samples; however, there is a significant population of clusters with velocity dispersions that are high for their richness. These clusters account for roughly 22percent of the > 70 systems in our sample, but more than half (55percent) of > 70 clusters at z < 0.5. A couple of these systems are hot and X-ray bright as expected for massive clusters with richnesses that appear to have been underestimated, but most appear to have high velocity dispersions for their X-ray properties likely due to line-of-sight structure. These results suggest that projection effects contribute significantly to redMaPPer selection, particularly at higher redshifts and lower richnesses. The redMaPPer determined richnesses for the velocity dispersion outliers are consistent with their X-ray properties, but several are X-ray undetected and deeper data are needed to understand their nature.

published proceedings


altmetric score

  • 8.83

author list (cited authors)

  • Wetzell, V., Jeltema, T. E., Hegland, B., Everett, S., Giles, P. A., Wilkinson, R., ... Weller, J.

citation count

  • 3

complete list of authors

  • Wetzell, V||Jeltema, TE||Hegland, B||Everett, S||Giles, PA||Wilkinson, R||Farahi, A||Costanzi, M||Hollowood, DL||Upsdell, E||Saro, A||Myles, J||Bermeo, A||Bhargava, S||Collins, CA||Cross, D||Eiger, O||Gardner, G||Hilton, M||Jobel, J||Kelly, P||Laubner, D||Liddle, AR||Mann, RG||Martinez, V||Mayers, J||McDaniel, A||Romer, AK||Rooney, P||Sahlen, M||Stott, J||Swart, A||Turner, DJ||Viana, PTP||Abbott, TMC||Aguena, M||Allam, S||Andrade-Oliveira, F||Annis, J||Asorey, J||Bertin, E||Burke, DL||Calcino, J||Carnero Rosell, A||Carollo, D||Carrasco Kind, M||Carretero, J||Choi, A||Crocce, M||da Costa, LN||Pereira, MES||Davis, TM||De Vicente, J||Desai, S||Diehl, HT||Dietrich, JP||Doel, P||Evrard, AE||Ferrero, I||Fosalba, P||Frieman, J||Garcia-Bellido, J||Gaztanaga, E||Glazebrook, K||Gruen, D||Gruendl, RA||Gschwend, J||Gutierrez, G||Hinton, SR||Honscheid, K||James, DJ||Kuehn, K||Kuropatkin, N||Lahav, O||Lewis, GF||Lidman, C||Lima, M||Maia, MAG||Marshall, JL||Melchior, P||Menanteau, F||Miquel, R||Morgan, R||Palmese, A||Paz-Chinchon, F||Plazas Malagon, AA||Sanchez, E||Scarpine, V||Serrano, S||Sevilla-Noarbe, I||Smith, M||Soares-Santos, M||Suchyta, E||Tarle, G||Thomas, D||Tucker, BE||Tucker, DL||Varga, TN||Weller, J

publication date

  • July 2022