PNG-UNITsims: Halo clustering response to primordial non-Gaussianities as a function of mass

Author:

Gutiérrez Adame AdriánORCID,Avila SantiagoORCID,Gonzalez-Perez VioletaORCID,Yepes GustavoORCID,Pellejero MarcosORCID,Wang Mike S.ORCID,Chuang Chia-HsunORCID,Feng Yu,Garcia-Bellido JuanORCID,Knebe AlexanderORCID

Abstract

This paper presents the PNG-UNITSIMS suite, which includes the largest full N-body simulation to date with local primordial non-Gaussianities (local PNG), the PNG-UNIT. The amplitude of the PNGs is given by f localNL=100. The simulation follows the evolution of 40963 particles in a periodic box with Lbox = 1 h−1 Gpc, resulting in a mass resolution of mp = 1.24 × 109h−1M, enough to finely resolve the galaxies targeted by stage-IV spectroscopic surveys. The PNG-UNIT has fixed initial conditions with phases also matching the pre-existing UNIT simulation with Gaussian initial conditions. The fixed and matched initial conditions reduce the simulation uncertainty significantly. In this first study of the PNG-UNITSIMS, we measure the PNG response parameter, p, as a function of the halo mass. halos with masses between 1 × 1012 and 5 × 1013h−1M are well described by the universality relation, given by p = 1. For halos with masses between 2 × 1010 and 1 × 1012h−1M we find that p < 1, at a significance between 1.5 and 3.1σ. Combining all the halos between 2 × 1010 and 5 × 1013h−1M, we find p consistent with a value of 0.955 ± 0.013, which is 3σ away from the universality relation. We demonstrate that these findings are robust to mass resolution, scale cuts and uncertainty estimation. We also compare our measurements to separate universe simulations, finding that the PNG-UNITSIMS constraints outperform the former for the setup considered. Using a prior on p as tight as the one reported here for DESI-like forecast can result in fNL constraints comparable to fixing p. At the same time, fixing p to a wrong value (p = 1) may result in up to 2σ biases on fNL.

Funder

Generalitat de Catalunya

Agencia Estatal de Investigación

Red Española de Supercomputación

Ministerio de Ciencia, Tecnología e Innovación

Comunidad de Madrid

Publisher

EDP Sciences

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