A sample of 6C radio sources designed to find objects at redshift z>4– III. Imaging and the radio galaxy K–z relation

In this paper, the third and final of a series, we present complete K -band imaging and some complementary I -band imaging of the filtered 6C* sample. We find no systematic differences between the K – z relation of 6C* radio galaxies and those from complete samples, so the near-infrared properties of luminous radio galaxies are not obviously biased by the additional 6C* radio selection criteria (steep spectral index and small angular size). The 6C* K – z data significantly improve delineation of the K – z relation for radio galaxies at high redshift ( z >2) . Accounting for non-stellar contamination, and for correlations between radio luminosity and stellar mass, we find little support for previous claims that the underlying scatter in the stellar luminosity of radio galaxies increases significantly at z >2 . In a particular spatially flat universe with a cosmological constant (Ω_M=0.3 and Ω_Λ=0.7) , the most luminous radio sources appear to be associated with galaxies with a luminosity distribution with a high mean (≈5  L *), and a low dispersion ( σ ∼0.5 mag) which formed their stars at epochs corresponding to z ≳2.5 . This result is in line with recent submillimetre studies of high-redshift radio galaxies and the inferred ages of extremely red objects from faint radio samples.     

Temporal Variations in the Second-Degree Stokes Tesseral Geopotential Coefficients from Topex/Poseidon Altimetry

The TOPEX/POSEIDON (T/P) altimetry data set covering the periodof January 1, 1993 to January 3, 2001 was used to derive monthlyseries of the second-degree tesseral geopotential coefficients.To account for the sea water temperature variations, rathersimple models have been devised and discussed, describinglocalized as well as areal variations of sea water temperatureand heights. The second-degree tesseral coefficients have alsobeen shown to be proportional to the pressureportions of the oceanic equatorial effective excitation functions,used in Ocean Angular Momentum (OAM) data. OAM datatogether with Atmospheric Angular Momentum (AAM) data canbe used to study observed polar motion (PM) series.The excess PM rates, derived from the T/P effective excitationfunctions, were compared to the corresponding observed PM rates,derived from the International Earth Rotation Service (IERS)Bulletin A and corrected with AAM also obtainedfrom IERS. The noise of the T/P derived PM rate series was foundto be significantly larger than the corresponding Bulletin A/AAMPM rate residuals as well as the PM rates derived from anindependent OAM series that was also available for the1993–2000 period.     

The 2dF Galaxy Redshift Survey: the nature of the relative bias between galaxies of different spectral type

We present an analysis of the relative bias between early- and late-type galaxies in the Two-degree Field Galaxy Redshift Survey (2dFGRS) – as defined by the η parameter of Madgwick et al., which quantifies the spectral type of galaxies in the survey. We calculate counts in cells for flux-limited samples of early- and late-type galaxies, using approximately cubical cells with sides ranging from 7 to  42 h ⁻¹ Mpc  . We measure the variance of the counts in cells using the method of Efstathiou et al., which we find requires a correction for a finite volume effect equivalent to the integral constraint bias of the autocorrelation function. Using a maximum-likelihood technique we fit lognormal models to the one-point density distribution, and develop methods of dealing with biases in the recovered variances resulting from this technique. We then examine the joint density distribution function,   f (δ_E, δ_L)  , and directly fit deterministic bias models to the joint counts in cells. We measure a linear relative bias of ≈1.3, which does not vary significantly with ℓ. A deterministic linear bias model is, however, a poor approximation to the data, especially on small scales  (ℓ≤ 28  h ⁻¹ Mpc)  where deterministic linear bias is excluded at high significance. A power-law bias model with index   b ₁≈ 0.75  is a significantly better fit to the data on all scales, although linear bias becomes consistent with the data for  ℓ≳ 40  h ⁻¹ Mpc  .     

MoMaF: the Mock Map Facility

We present the Mock Map Facility, a powerful tool for converting theoretical outputs of hierarchical galaxy formation models into catalogues of virtual observations. The general principle is straightforward: mock observing cones can be generated using semi-analytically post-processed snapshots of cosmological N -body simulations. These cones can then be projected to synthesize mock sky images. To this end, the paper describes in detail an efficient technique for creating such mock cones and images from the galaxies in cosmological simulations ( galics ) semi-analytic model, providing the reader with an accurate quantification of the artefacts it introduces at every step. We show that replication effects introduce a negative bias on the clustering signal – typically peaking at less than 10 per cent around the correlation length. We also thoroughly discuss how the clustering signal is affected by finite-volume effects, and show that it vanishes at scales larger than approximately one-tenth of the simulation box size. For the purpose of analysing our method, we show that number counts and redshift distributions obtained with galics / momaf compare well with K -band observations and the two-degree field galaxy redshift survey. Given finite-volume effects, we also show that the model can reproduce the automatic plate measuring machine angular correlation function. The momaf results discussed here are made publicly available to the astronomical community through a public data base. Moreover, a user-friendly Web interface ( http://galics.iap.fr ) allows any user to recover her/his own favourite galaxy samples through simple SQL queries. The flexibility of this tool should permit a variety of uses ranging from extensive comparisons between real observations and those predicted by hierarchical models of galaxy formation, to the preparation of observing strategies for deep surveys and tests of data processing pipelines.