2017
DOI: 10.1093/mnras/stx1053
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Weak-lensing mass calibration of redMaPPer galaxy clusters in Dark Energy Survey Science Verification data

Abstract: We use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8,000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter 5 λ 180 and redshift 0.2 z 0.8, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluste… Show more

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Cited by 124 publications
(187 citation statements)
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References 118 publications
(168 reference statements)
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“…The best fit parameters are listed in Table 1. We obtain a halo mass M 200 = 2.06 +0.61 −0.41 × 10 14 M that is consistent with the halo mass fitting result in Miyatake et al (2016), as well as the halo mass estimated by mass-richness relation in Melchior et al (2017) and Shan et al (2017) . To compare our measurements with the three-dimensional (3D) N-body simulation results directly, we correct the C 200 with the 3D correction in Giocoli et al (2012):…”
Section: Resultssupporting
confidence: 88%
“…The best fit parameters are listed in Table 1. We obtain a halo mass M 200 = 2.06 +0.61 −0.41 × 10 14 M that is consistent with the halo mass fitting result in Miyatake et al (2016), as well as the halo mass estimated by mass-richness relation in Melchior et al (2017) and Shan et al (2017) . To compare our measurements with the three-dimensional (3D) N-body simulation results directly, we correct the C 200 with the 3D correction in Giocoli et al (2012):…”
Section: Resultssupporting
confidence: 88%
“…Umetsu et al (2016) quantified unaccounted sources of systematic errors in the CLASH weak-lensing measurements by considering the following effects: (1) dilution of the weaklensing signal by residual contamination from cluster members (2.4%±0.7%), (2) photo-z bias in the mean depth estimates (0.27%; Section 3.2), and (3) shear calibration uncertainty (5%; Section 3.3.2). These errors add up to 5.6% in quadrature, which is translated into the cluster mass uncertainty as 5.6%/Γ;7%, with Γ;0.75 the typical value of the logarithmic derivative of the weak-lensing signal with respect to cluster mass (Melchior et al 2017).…”
Section: Systematic Errorsmentioning
confidence: 99%
“…Gravitational lensing offers a direct probe of the cluster mass distribution through observations of weak shear lensing (e.g., Gruen et al 2014;von der Linden et al 2014;Hoekstra et al 2015;Melchior et al 2017;Sereno et al 2017a;Medezinski et al 2018), weak magnification lensing (e.g., Hildebrandt et al 2011;Umetsu et al 2011b;Coupon et al 2013;Chiu et al 2016;Tudorica et al 2017), strong gravitational lensing (e.g., Broadhurst et al 2005a;Zitrin et al 2013;Jauzac et al 2015;Cerny et al 2017;Diego et al 2018), and the combination of these effects (e.g., Umetsu et al 2011a;Coe et al 2012;Medezinski et al 2013;Umetsu et al 2015Umetsu et al , 2016. The critical advantage of gravitational lensing is its unique ability to map the mass distribution independently of assumptions about their physical or dynamical state.…”
Section: Introductionmentioning
confidence: 99%
“…Many authors have argued that, when a limited number of filters are used in source selection by removing red-sequence galaxies, one of the important systematic errors is the contamination by faint blue cluster members (e.g., Broadhurst et al 2005;Okabe et al 2010;Applegate et al 2014;Melchior et al 2017). Recently, Medezinski et al (2017) suggested that the blue cluster member contamination is not only limited to the cluster central region, but also to outskirts and will thus impact determinations of both mass and concentration.…”
Section: Cluster Member Contaminationmentioning
confidence: 99%