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We present a new methodology to generate mock halo or galaxy catalogues,which have accurate clustering properties, nearly indistinguishable from full$N$-body solutions, in terms of the one-point, two-point, and three-pointstatistics. In particular, the agreement is remarkable, within $1\%$ up to$k=0.55$ $h$Mpc$^{-1}$ and down to $r=10$ $h^{-1}$Mpc, for the power spectrumand two-point correlation function respectively, while the bispectrum agrees ingeneral within $20\%$ for different scales and shapes. Our approach is based onthe Zel'dovich approximation, however, effectively including with the simpleprescriptions the missing physical ingredients, and stochastic scale-dependent,non-local and nonlinear biasing contributions. The computing time and memoryrequired to produce one mock is similar to that using the log-normal model.With high accuracy and efficiency, the effective Zel'dovich approximation mocks(EZmocks) provide a reliable and practical method to produce massive mockgalaxy catalogues for the analysis of large-scale structure measurements.

EZmocks: extending the Zel'dovich approximation to generate mock galaxy catalogues with accurate clustering statistics