SPATIAL CORRELATION-FUNCTION AND PAIRWISE VELOCITY DISPERSION OF GALAXIES - COLD DARK-MATTER MODELS VERSUS THE LAS-CAMPANAS SURVEY

We show, with the help of large N-body simulations, that both the real -space two-point correlation function and pairwise velocity dispersion of galaxies can be measured reliably from the Las Campanas Redshift S urvey. The real-space correlation function is well fitted by the power law xi(r) = (r(0)/r)(gamma) with r(0) = (5.06 +/- 0.12) h(-1) Mpc and gamma = 1.862 +/- 0.034, and the pairwise velocity dispersion at 1 h( -1) Mpc is 570 +/- 80 km s(-1). A detailed comparison between these ob servational results and the predictions of current cold dark matter (C DM) cosmogonies is carried out. We construct 60 mock samples for each theoretical model from a large set of high-resolution N-body simulatio ns, which allows us to include various observational selection effects in the analyses and to use exactly the same methods for both real and theoretical samples. We demonstrate that such a procedure is essentia l in the comparison between models and observations. The observed two- point correlation function is significantly flatter than the mass corr elation function in current CDM models on scales less than or similar to 1 h(-1) Mpc. The observed pairwise velocity dispersion is also lowe r than that of dark matter particles in these models. We propose a sim ple antibias model to explain these discrepancies. This model assumes that the number of galaxies per unit dark matter mass, N/M, decreases with the mass of dark haloes. The predictions of CDM models with sigma (8) Omega(0)(0.6) similar to 0.4 - 0.5 and Gamma similar to 0.2 are in agreement with the observational results, if the trend of N/M with M is at the level already observed for rich clusters of galaxies. Thus C DM models with Gamma similar to 0.2 and with cluster-abundance normali zation are consistent with the observed correlation function and pairw ise velocity dispersion of galaxies. A high level of velocity bias is not required in these models.