We present a self-consistent non-parametric model of the local cosmic velocity field derived from the distribution of IRAS galaxies in the PSCz redshift survey. The survey has been analysed using two independent methods, both based on the assumptions of gravitational instability and linear biasing. The two methods, which give very similar results, have been tested and calibrated on mock PSCz catalogues constructed from cosmological N-body simulations. The denser sampling provided by the PSCz survey compared with previous IRAS galaxy surveys allows an improved reconstruction of the density and velocity fields out to large distances. The most striking feature of the model velocity field is a coherent large-scale streaming motion along the baseline connecting Perseus-Pisces, the Local Supercluster, the Great Attractor and the Shapley Concentration. We find no evidence for back-infall on to the Great Attractor. Instead, material behind and around the Great Attractor is inferred to be streaming towards the Shapley Concentration, aided by the compressional push of two large nearby underdensities. The PSCz model velocities compare well with those predicted from the 1.2-Jy redshift survey of IRAS galaxies and, perhaps surprisingly, with those predicted from the distribution of Abell/ACO clusters, out to 140h(-1)Mpc. Comparison of the real-space density fields (or, alternatively, the peculiar velocity fields) inferred from the PSCz and cluster catalogues gives a relative (linear) bias parameter between clusters and IRAS galaxies of b(c) = 4.4 +/- 0.6. Finally, we implement a likelihood analysis that uses all the available information on peculiar velocities in our local Universe to estimate beta = Omega(0)(0.6)/b = 0.6(-0.15)(+0.22) (1 sigma), where b is the bias parameter for IRAS galaxies

We describe the 2dF Galaxy Redshift Survey (2dFGRS) and the current status of the observations. In this exploratory paper, we apply a principal component analysis to a preliminary sample of 5869 galaxy spectra and use the two most significant components to split the sample into five spectral classes. These classes are defined by considering visual classifications of a subset of the 2dF spectra, and also by comparison with high‐quality spectra of local galaxies. We calculate a luminosity function for each of the different classes and find that later‐type galaxies have a fainter characteristic magnitude, and a steeper faint‐end slope. For the whole sample we find M*=−19.7 (for Ω=1, H0=100 km s−1 Mpc−1), α=−1.3, φ*=0.017. For class 1 (‘early‐type’) we find M*=−19.6, α=−0.7, while for class 5 (‘late‐type’) we find M*=−19.0, α=−1.7. The derived 2dF luminosity functions agree well with other recent luminosity function estimates.

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We investigate the large‐scale clustering of radio sources in the FIRST 1.4‐GHz survey by analysing the distribution function (counts in cells). We select a reliable sample from the the FIRST catalogue, paying particular attention to the problem of how to define single radio sources from the multiple components listed. We also consider the incompleteness of the catalogue. We estimate the angular two‐point correlation function w(θ), the variance Ψ2 and skewness Ψ3 of the distribution for the various subsamples chosen on different criteria. Both w(θ) and Ψ2 show power‐law behaviour with an amplitude corresponding to a spatial correlation length of r0 ∼ 10 h−1Mpc. We detect significant skewness in the distribution, the first such detection in radio surveys. This skewness is found to be related to the variance through Ψ3 = S3(Ψ2)α, with α = 1.9 ± 0.1, consistent with the non‐linear gravitational growth of perturbations from primordial Gaussian initial conditions. We show that the amplitude of variance and the skewness are consistent with realistic models of galaxy clustering.