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Rapid simulations of halo and subhalo clustering

Berner P.
•
Refregier A.
•
Sgier R.
altro
Monaco P.
2022
  • journal article

Periodico
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
Abstract
The analysis of cosmological galaxy surveys requires realistic simulations for their interpretation. Forward modelling is a powerful method to simulate galaxy clustering without the need for an underlying complex model. This approach requires fast cosmological simulations with a high resolution and large volume, to resolve small dark matter halos associated to single galaxies. In this work, we present fast halo and subhalo clustering simulations based on the Lagrangian perturbation theory code PINOCCHIO, which generates halos and merger trees. The subhalo progenitors are extracted from the merger history and the survival of subhalos is modelled. We introduce a new fitting function for the subhalo merger time, which includes a redshift dependence of the fitting parameters. The spatial distribution of subhalos within their hosts is modelled using a number density profile. We compare our simulations with the halo finder ROCKSTAR applied to the full N-body code GADGET-2. The subhalo velocity function and the correlation function of halos and subhalos are in good agreement. We investigate the effect of the chosen number density profile on the resulting subhalo clustering. Our simulation is approximate yet realistic and significantly faster compared to a full N-body simulation combined with a halo finder. The fast halo and subhalo clustering simulations offer good prospects for galaxy forward models using subhalo abundance matching.
DOI
10.1088/1475-7516/2022/11/002
WOS
WOS:000899443700002
Archivio
https://hdl.handle.net/11368/3054120
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85141989413
https://iopscience.iop.org/article/10.1088/1475-7516/2022/11/002
Diritti
closed access
license:copyright editore
license uri:iris.pri02
FVG url
https://arts.units.it/request-item?handle=11368/3054120
Soggetti
  • cosmological simulati...

  • dark matter simulatio...

  • galaxy clustering

  • Statistical sampling ...

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