Data di Pubblicazione:
2017
Citazione:
Simulating cosmologies beyond ΛCDM with PINOCCHIO / L.A. Rizzo, F. Villaescusa-Navarro, P. Monaco, E. Munari, S. Borgani, E. Castorina, E. Sefusatti. - In: JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS. - ISSN 1475-7516. - 2017:1(2017 Jan). [10.1088/1475-7516/2017/01/008]
Abstract:
We present a method that extends the capabilities of the PINpointing Orbit-Crossing Collapsed HIerarchical Objects (PINOCCHIO) code, allowing it to generate accurate dark matter halo mock catalogues in cosmological models where the linear growth factor and the growth rate depend on scale. Such cosmologies comprise, among others, models with massive neutrinos and some classes of modified gravity theories. We validate the code by comparing the halo properties from PINOCCHIO against N-body simulations, focusing on cosmologies with massive neutrinos: νΛCDM. We analyse the halo mass function, halo two-point correlation function and halo power spectrum, showing that PINOCCHIO reproduces the results from simulations with the same level of precision as the original code (∼ 5-10%). We demonstrate that the abundance of halos in cosmologies with massless and massive neutrinos from PINOCCHIO matches very well the outcome of simulations, and point out that PINOCCHIO can reproduce the Ων - σ8 degeneracy that affects the halo mass function. We finally show that the clustering properties of the halos from PINOCCHIO matches accurately those from simulations both in real and redshift-space, in the latter case up to k = 0.3 h Mpc-1. We emphasize that the computational time required by PINOCCHIO to generate mock halo catalogues is orders of magnitude lower than the one needed for N-body simulations. This makes this tool ideal for applications like covariance matrix studies within the standard ΛCDM model but also in cosmologies with massive neutrinos or some modified gravity theories.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Cosmic web; Cosmological parameters from LSS; Neutrino masses from cosmology; Redshift surveys
Elenco autori:
L.A. Rizzo, F. Villaescusa-Navarro, P. Monaco, E. Munari, S. Borgani, E. Castorina, E. Sefusatti
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