Constraints on the richness–mass relation and the optical-SZE positional offset distribution for SZE-selected clusters
We cross-match galaxy cluster candidates selected via their Sunyaev–Zel'dovich effect
(SZE) signatures in 129.1 deg2 of the South Pole Telescope 2500d SPT-SZ survey with
optically identified clusters selected from the Dark Energy Survey science verification data.
We identify 25 clusters between 0.1≲ z≲ 0.8 in the union of the SPT-SZ and redMaPPer
(RM) samples. RM is an optical cluster finding algorithm that also returns a richness estimate
for each cluster. We model the richness λ-mass relation with the following function< ln λ| M …
(SZE) signatures in 129.1 deg2 of the South Pole Telescope 2500d SPT-SZ survey with
optically identified clusters selected from the Dark Energy Survey science verification data.
We identify 25 clusters between 0.1≲ z≲ 0.8 in the union of the SPT-SZ and redMaPPer
(RM) samples. RM is an optical cluster finding algorithm that also returns a richness estimate
for each cluster. We model the richness λ-mass relation with the following function< ln λ| M …
Constraints on the richness-mass relation and the optical-SZE positional offset distribution for SZE-selected clusters
K Romer, DES Collaboration, et al - 2015 - sussex.figshare.com
We cross-match galaxy cluster candidates selected via their Sunyaev-Zel'dovich effect (SZE)
signatures in 129.1 deg2 of the South Pole Telescope 2500d SPT-SZ survey with optically
identified clusters selected from the Dark Energy Survey science verification data. We
identify 25 clusters between 0.1? z? 0.8 in the union of the SPT-SZ and redMaPPer (RM)
samples. RM is an optical cluster finding algorithm that also returns a richness estimate for
each cluster. We model the richness lambda-mass relation with the following function …
signatures in 129.1 deg2 of the South Pole Telescope 2500d SPT-SZ survey with optically
identified clusters selected from the Dark Energy Survey science verification data. We
identify 25 clusters between 0.1? z? 0.8 in the union of the SPT-SZ and redMaPPer (RM)
samples. RM is an optical cluster finding algorithm that also returns a richness estimate for
each cluster. We model the richness lambda-mass relation with the following function …
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