Large-Scale Galaxy Bias

By V. Desjacques, D. Jeong, F. Schmidt. 2016

707 citations recorded by the source corpus.

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Subfields: Astronomy and Astrophysics

View Paper: https://www.semanticscholar.org/paper/3c01452f4b75de71967320054b58d1f102e0f75a

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In Astronomy and Astrophysics

Citations in the corpus

BOSS DR12 full-shape cosmology: ΛCDM constraints from the large-scale galaxy power spectrum and bispectrum monopole (2021, background): “Data-points are shown in blue, whilst the red curves give predictions for the dark-matter bias relations, from [113] and [111] for b2 and bG2 respectively.”
Probing the theory of gravity with gravitational lensing of gravitational waves and galaxy surveys (2019, methodology): “(11) In this analysis, we have taken a linear bias model with the value of the bias parameter as bg = 1.6 (Anderson et al. 2012; Alam et al. 2017a; Desjacques et al. 2018) and the non-linear dark matter power spectrum from the numerical code CLASS (Blas et al. 2011; Lesgourgues 2011).”
Consistent modeling of velocity statistics and redshift-space distortions in one-loop perturbation theory (2020, background): “Our treatment of this stochastic contribution differs from much of the literature [25, 26]; this is of no consequence when fitting the redshift-space power spectrum, since its contribution there is degenerate with that of the stochastic component to v(k), but makes a signficant difference when study”
The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: BAO and RSD measurements from anisotropic clustering analysis of the quasar sample in configuration space between redshift 0.8 and 2.2 (2020, background): “The shape of the two-point correlation function of QSOs may potentially be affected by the radiation field or large-scale outflows during its formation (Desjacques et al. 2018).”
Cosmological parameters from the BOSS galaxy power spectrum (2019, methodology): “This includes nonlinearities in the dark matter fluid [10, 11], the bias model [12–15] (for a review see [16]), and redshift space distortions [17, 18].”
Nonlinear perturbation theory extension of the Boltzmann code CLASS (2020, background): “The perturbative bias model, (at least up to third order, which is needed for the one-loop power spectrum), is now well established and tested against various numerical simulations (for a review see [58]).”