Abstract

ABSTRACT 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 data from N-body simulations and demonstrate that it can boost power in the two-halo term by a factor of ∼2 at scales $k\sim 0.7\, h\mathrm{Mpc}^{-1}$, with the exact magnitude of the boost determined by the specific pair of fields in the two-point function. How this translates to the full power spectrum depends on the relative strength of the one-halo term, which can mask the importance of this correction to a greater or lesser degree, again depending on the fields. Generally, we find that our correction is more important for signals that arise from lower mass haloes. When comparing our calculation to simulated data, we find that the underprediction of power in the transition region between the two- and one-halo terms, which typically plagues halo-model calculations, is almost completely eliminated when including the full non-linear halo bias. We show improved results for the autospectra and cross-spectra of galaxies, haloes, and matter. In the specific case of matter–matter or matter–halo power, we note that a large fraction of the improvement comes from the non-linear biasing between low- and high-mass haloes. We envisage our model being useful in the analytical modelling of cross-correlation signals. Our non-linear bias halo-model code is available at https://github.com/alexander-mead/BNL.

Highlights

  • The halo model is widely used in the interpretation of data from cosmological large-scale structure surveys

  • We have proposed an extension to the analytical halo-model formalism that allows for beyond-linear halo bias to be included within an otherwise standard calculation

  • We have expressed our correction in such a way that the a single new term is added to the two-halo term, so that it can be integrated within existing halo-model implementations

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Summary

Introduction

The halo model (reviewed by Cooray & Sheth 2002) is widely used in the interpretation of data from cosmological large-scale structure surveys. All matter is taken to reside in haloes that trace the large-scale matter fluctuations in a biased way, with this ‘halo bias’ usually taken to be linear with respect to the underlying linear matter field. The model makes a number of other simplifying assumptions; usually that haloes are spherical, devoid of substructure, and that the halo mass determines all of the halo properties with no scatter. Choices must be made for the mass function, biasing recipe, and profile for haloes. Fields, be they sourced by point tracers or else via some emissivity, can be assumed to occupy haloes in different ways depending on the halo properties; the model will make predictions for the n-point correlation functions. The halo model has been successful in explaining the broad shape of the galaxy–galaxy correlation function (e.g., Seljak 2000; Peacock & Smith 2000), as well as making inroads in the understanding of the

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