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We address the question of whether or not assembly bias arises in the absence of highly non-linear effects such as tidal stripping of halos near larger mass concentrations. Therefore, we use a simplified dynamical scheme where these effects are not modeled. We choose the punctuated Zeldovich (PZ) approximation, which prevents orbit mixing by coalescing particles coming within a critical distance of each other. A numerical implementation of this approximation is fast, allowing us to run a large number of simulations to study assembly bias. We measure an assembly bias from 60 PZ simulations, each with 512^3 cold particles in a 128h^-1 Mpc cubic box. The assembly bias estimated from the correlation functions at separations < 5h^-1 Mpc for objects (halos) at z=0 is comparable to that obtained in full N-body simulations. For masses 4x10^11 h^-1 Mo the oldest 10% haloes are 3-5 times more correlated than the youngest 10%. The bias weakens with increasing mass, also in agreement with full N-body simulations. We find that that halo ages are correlated with the dimensionality of the surrounding linear structures as measured by the parameter (lambda_1+lambda_2+lambda_3)/ (lambda_1^2+lambda_2^2+lambda_3^2)^{1/2} where lambda_i are proportional to the eigenvalues of the velocity deformation tensor. Our results suggest that assembly bias may already be encoded in the early stages of the evolution.
The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f_NL, offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the
The two-point clustering of dark matter halos is influenced by halo properties besides mass, a phenomenon referred to as halo assembly bias. Using the depth of the gravitational potential well, $V_{rm max}$, as our secondary halo property, in this pa
Dark matter halo clustering depends not only on halo mass, but also on other properties such as concentration and shape. This phenomenon is known broadly as assembly bias. We explore the dependence of assembly bias on halo definition, parametrized by
We present significant evidence of halo assembly bias for SDSS redMaPPer galaxy clusters in the redshift range $[0.1, 0.33]$. By dividing the 8,648 clusters into two subsamples based on the average member galaxy separation from the cluster center, we
We derive a simple prescription for including beyond-linear halo bias within the standard, analytical halo-model power spectrum calculation. This results in a corrective term that is added to the usual two-halo term. We measure this correction using