Galaxy clusters at 0.3<z<0.4 and the value of  0

Abstract

A B S T R A C TThe observed evolution of the galaxy cluster X-ray integral temperature distribution function between z 0:05 and z 0:32 is used in an attempt to constrain the value of the density parameter, Q 0 , for both open and spatially¯at universes. We estimate the overall uncertainty in the determination of both the observed and predicted galaxy cluster X-ray integral temperature distribution functions at z 0:32 by carrying out Monte Carlo simulations, where we take into careful consideration all the most important sources of possible error. We include the effect of the formation epoch on the relation between virial mass and X-ray temperature, improving on the assumption that clusters form at the observed redshift which leads to an overestimate of Q 0 . We conclude that at present both the observational data and the theoretical modelling carry suf®ciently large associated uncertainties to prevent an unambiguous determination of Q 0 . We ®nd that values of Q 0 around 0.75 are most favoured, with Q 0 < 0:3 excluded with at least 90 per cent con®dence. In particular, the Q 0 1 hypothesis is found to be still viable as far as this data set is concerned. As a by-product, we also use the revised data on the abundance of galaxy clusters at z 0:05 to update the constraint on j 8 given by Viana & Liddle, ®nding slightly lower values than before.

How accurately can the SZ effect measure peculiar cluster velocities and bulk flows?

“…The mass variance σ 2 (M, z) of the fluctuation spectrum, filtered on mass scale M , is related to the power spectrum of the initial density fluctuations P (k) (Peebles 1980). Following Viana & Liddle (1996) and Viana & Liddle (1999), we use an approximation of the variance in spheres of radius R (R = (3M/4πρ) 1/3 ) in the vicinity of 8 h −1 Mpc:…”

Improvements in the X-ray luminosity function and constraints on the cosmological parameters from X-ray luminous clusters

“…Studies by different authors (Bahcall et al 1997;Bahcall & Fan 1998;Sadat et al 1998;Blanchard et al 1998;Blanchard & Bartlett 1998;Eke et al 1998;Viana & Liddle 1999;Reichart et al 1999;Donahue & Voit 1999;Borgani et al 2001) found values for Ω m spanning the entire range of acceptable values: 0.2 ≤ Ω m ≤ 1. On the basis of the same data set of Eke et al (1998) with Viana & Liddle (1999), showed that uncertainties both in fitting local data and in the theoretical modelling could significantly change the final results. They found Ω m 0.75 as a preferred value with a critical density model acceptable at <90% c.l., while Eke et al (1998) found Ω m = 0.45 ± 0.2.…”

SDSS-RASS: Next Generation of Cluster-Finding Algorithms

“…Many authors have used this technique with a preponderance of the evidence for a low Ω m , but the observed scatter between the various measurements is large. For example, we have seen Ω m = 0.3 ± 0.1 (Bahcall et al 1997), Ω m = 0.45 ± 0.2 (Eke et al 1998), Ω m = 0.5 ± 0.14 (Henry 1997), Ω m ∼ 0.75 (Viana & Liddle 1999), Ω m ∼ 0.85±0.2 (Sadat et al 1998), and Ω = 0.96 +0. 36 −0.32 (Reichart et al 1999).…”

“…For example, we have seen Ω m = 0.3 ± 0.1 (Bahcall et al 1997), Ω m = 0.45 ± 0.2 (Eke et al 1998), Ω m = 0.5 ± 0.14 (Henry 1997), Ω m ∼ 0.75 (Viana & Liddle 1999), Ω m ∼ 0.85±0.2 (Sadat et al 1998), and Ω = 0.96 +0. 36 −0.32 (Reichart et al 1999). This scatter could be the combination of several effects including small sample sizes, errors in the survey selection functions as well as the necessity to compare local samples of clusters to more distant samples in any effort to see an evolutionary signal.…”