SIMBAD references

2009MNRAS.397..577S - Mon. Not. R. Astron. Soc., 397, 577-607 (2009/August-1)

The XMM Cluster Survey: forecasting cosmological and cluster scaling-relation parameter constraints.

SAHLEN M., VIANA P.T.P., LIDDLE A.R., ROMER A.K., DAVIDSON M., HOSMER M., LLOYD-DAVIES E., SABIRLI K., COLLINS C.A., FREEMAN P.E., HILTON M., HOYLE B., KAY S.T., MANN R.G., MEHRTENS N., MILLER C.J., NICHOL R.C., STANFORD S.A. and WEST M.J.

Abstract (from CDS):

We forecast the constraints on the values of σ8m and cluster scaling-relation parameters which we expect to obtain from the XMM Cluster Survey (XCS). We assume a flat Λ cold dark matter Universe and perform a Monte Carlo Markov Chain analysis of the evolution of the number density of galaxy clusters that takes into account a detailed simulated selection function. Comparing our current observed number of clusters shows good agreement with predictions. We determine the expected degradation of the constraints as a result of self-calibrating the luminosity-temperature relation (with scatter), including temperature measurement errors, and relying on photometric methods for the estimation of galaxy cluster redshifts. We examine the effects of systematic errors in scaling relation and measurement error assumptions. Using only (T, z) self-calibration, we expect to measure Ωm to ±0.03 (and ΩΛto the same accuracy assuming flatness), and σ8 to ±0.05, also constraining the normalization and slope of the luminosity-temperature relation to ±6 and ±13 per cent (at 1σ), respectively, in the process. Self-calibration fails to jointly constrain the scatter and redshift evolution of the luminosity-temperature relation significantly. Additional archival and/or follow-up data will improve on this. We do not expect measurement errors or imperfect knowledge of their distribution to degrade constraints significantly. Scaling-relation systematics can easily lead to cosmological constraints 2σ or more away from the fiducial model. Our treatment is the first exact treatment to this level of detail, and introduces a new `smoothed ML' (Maximum Likelihood) estimate of expected constraints.

Abstract Copyright: © 2009 The Authors. Journal compilation © 2009 RAS

Journal keyword(s): methods: statistical - galaxies: clusters: general - cosmological parameters - cosmology: observations - cosmology: theory - X-rays: galaxies: clusters

Status at CDS:  

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2020.04.07-11:27:41

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