Cluster Correlations in the Zel'dovich Approximation

We show how to simulate the clustering of rich clusters of galaxies using a technique based on the Zel'dovich approximation. This method well reproduces the spatial distribution of clusters obtainable from full N-body simulations at a fraction of the computational cost. We use an ensemble of large--scale simulations to assess the level and statistical significance of cluster clustering in open, tilted and flat versions of the Cold Dark Matter (CDM) model, as well as a model comprising a mixture of Cold and Hot Dark Matter (CHDM). We find the open and flat CDM models are excluded by the data. The tilted CDM model with a slight tilt is in marginal agreement, while larger tilt produces the right amount of clustering; CHDM is the best of all our models at reproducing the observations of cluster clustering. We find that {\em all} our models display a systematically weaker relationship between clustering length and mean cluster separation than seems to be implied by observations. We also note that the cluster bias factor, is not constant in any of the models, showing that one needs to be very careful when relating cluster clustering statistics to primordial density fluctuations.