TL;DR
This paper enhances the Pinocchio code for fast halo catalog generation by incorporating third-order Lagrangian Perturbation Theory, significantly improving the accuracy of clustering statistics compared to previous versions.
Contribution
The paper introduces the use of 3rd-order LPT in Pinocchio, improving the accuracy of halo displacement and clustering predictions over earlier methods.
Findings
3LPT provides the best agreement with N-body simulations for halo displacements.
Using 3LPT, the halo power spectrum is recovered within 10% up to k~0.5 h/Mpc.
2LPT improves halo construction accuracy over Zeldovich approximation.
Abstract
We present the latest version of Pinocchio, a code that generates catalogues of DM haloes in an approximate but fast way with respect to an N-body simulation. This code version extends the computation of particle and halo displacements up to 3rd-order Lagrangian Perturbation Theory (LPT), in contrast with previous versions that used Zeldovich approximation (ZA). We run Pinocchio on the same initial configuration of a reference N-body simulation, so that the comparison extends to the object-by-object level. We consider haloes at redshifts 0 and 1, using different LPT orders either for halo construction - where displacements are needed to decide particle accretion onto a halo or halo merging - or to compute halo final positions. We compare the clustering properties of Pinocchio haloes with those from the simulation by computing the power spectrum and 2-point correlation function…
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