Galaxy cluster mass estimation from stacked spectroscopic analysis

We use simulated galaxy surveys to study: (i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and (ii) the accuracy of a mean dynamical cluster mass, M-sigma(lambda), derived from stacked pairwise spectroscopy of clusters with richness lambda. Using similar to 130...

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Main Authors: Farahi, Arya, Evrard, August E., Rozo, Eduardo, Rykoff, Eli S., Wechsler, Risa H.
Other Authors: Univ Arizona, Dept Phys
Language:en
Published: OXFORD UNIV PRESS 2016
Subjects:
Online Access:http://hdl.handle.net/10150/621426
http://arizona.openrepository.com/arizona/handle/10150/621426
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spelling ndltd-arizona.edu-oai-arizona.openrepository.com-10150-6214262016-11-30T03:00:31Z Galaxy cluster mass estimation from stacked spectroscopic analysis Farahi, Arya Evrard, August E. Rozo, Eduardo Rykoff, Eli S. Wechsler, Risa H. Univ Arizona, Dept Phys methods: statistical galaxies: clusters: general galaxies: haloes We use simulated galaxy surveys to study: (i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and (ii) the accuracy of a mean dynamical cluster mass, M-sigma(lambda), derived from stacked pairwise spectroscopy of clusters with richness lambda. Using similar to 130 000 galaxy pairs patterned after the Sloan Digital Sky Survey (SDSS) redMaPPer cluster sample study of Rozo et al., we show that the pairwise velocity probability density function of central-satellite pairs with m(i) < 19 in the simulation matches the form seen in Rozo et al. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes similar to 60 per cent of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. to the velocity normalization matches, to within a few per cent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with miscentring and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at z = 0.2 of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al., we find aEuroln (M-200c)|lambda aEuro parts per thousand = ln (< M-30) + alpha(m) ln (lambda/30) with M-30 = 1.56 +/- 0.35 x 10(14) M-aS (TM) and alpha(m) = 1.31 +/- 0.06(stat) +/- 0.13(sys). Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget. 2016-08-21 Article Galaxy cluster mass estimation from stacked spectroscopic analysis 2016, 460 (4):3900 Monthly Notices of the Royal Astronomical Society 0035-8711 1365-2966 10.1093/mnras/stw1143 http://hdl.handle.net/10150/621426 http://arizona.openrepository.com/arizona/handle/10150/621426 Monthly Notices of the Royal Astronomical Society en http://mnras.oxfordjournals.org/lookup/doi/10.1093/mnras/stw1143 © 2016 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society OXFORD UNIV PRESS
collection NDLTD
language en
sources NDLTD
topic methods: statistical
galaxies: clusters: general
galaxies: haloes
spellingShingle methods: statistical
galaxies: clusters: general
galaxies: haloes
Farahi, Arya
Evrard, August E.
Rozo, Eduardo
Rykoff, Eli S.
Wechsler, Risa H.
Galaxy cluster mass estimation from stacked spectroscopic analysis
description We use simulated galaxy surveys to study: (i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and (ii) the accuracy of a mean dynamical cluster mass, M-sigma(lambda), derived from stacked pairwise spectroscopy of clusters with richness lambda. Using similar to 130 000 galaxy pairs patterned after the Sloan Digital Sky Survey (SDSS) redMaPPer cluster sample study of Rozo et al., we show that the pairwise velocity probability density function of central-satellite pairs with m(i) < 19 in the simulation matches the form seen in Rozo et al. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes similar to 60 per cent of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. to the velocity normalization matches, to within a few per cent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with miscentring and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at z = 0.2 of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al., we find aEuroln (M-200c)|lambda aEuro parts per thousand = ln (< M-30) + alpha(m) ln (lambda/30) with M-30 = 1.56 +/- 0.35 x 10(14) M-aS (TM) and alpha(m) = 1.31 +/- 0.06(stat) +/- 0.13(sys). Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget.
author2 Univ Arizona, Dept Phys
author_facet Univ Arizona, Dept Phys
Farahi, Arya
Evrard, August E.
Rozo, Eduardo
Rykoff, Eli S.
Wechsler, Risa H.
author Farahi, Arya
Evrard, August E.
Rozo, Eduardo
Rykoff, Eli S.
Wechsler, Risa H.
author_sort Farahi, Arya
title Galaxy cluster mass estimation from stacked spectroscopic analysis
title_short Galaxy cluster mass estimation from stacked spectroscopic analysis
title_full Galaxy cluster mass estimation from stacked spectroscopic analysis
title_fullStr Galaxy cluster mass estimation from stacked spectroscopic analysis
title_full_unstemmed Galaxy cluster mass estimation from stacked spectroscopic analysis
title_sort galaxy cluster mass estimation from stacked spectroscopic analysis
publisher OXFORD UNIV PRESS
publishDate 2016
url http://hdl.handle.net/10150/621426
http://arizona.openrepository.com/arizona/handle/10150/621426
work_keys_str_mv AT farahiarya galaxyclustermassestimationfromstackedspectroscopicanalysis
AT evrardauguste galaxyclustermassestimationfromstackedspectroscopicanalysis
AT rozoeduardo galaxyclustermassestimationfromstackedspectroscopicanalysis
AT rykoffelis galaxyclustermassestimationfromstackedspectroscopicanalysis
AT wechslerrisah galaxyclustermassestimationfromstackedspectroscopicanalysis
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