The Effect of Primordial Non-Gaussianity on Halo Bias

By S. Matarrese, L. Verde. 2008

395 citations recorded by the source corpus.

It has long been known how to analytically relate the clustering properties of the collapsed structures (halos) to those of the underlying dark matter distribution for Gaussian initial conditions. Here we apply the same approach to physically motivated non-Gaussian models. The techniques we use were developed in the 1980s to deal with the clustering of peaks of non-Gaussian density fields. The description of the clustering of halos for non-Gaussian initial conditions has recently received renewed interest, motivated by the forthcoming large galaxy and cluster surveys. For inflationary-motivated non-Gaussianities, we find an analytic expression for the halo bias as a function of scale, mass, and redshift, employing only the approximations of high peaks and large separations.

Subfields: Astronomy and Astrophysics, Instrumentation

View Paper: https://www.semanticscholar.org/paper/79855f3891706f4591fa2844ba93ba2b717fffa2

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Citations in the corpus

Large-scale non-Gaussian mass function and halo bias: tests on N-body simulations (2009, methodology): “3 of Matarrese & Verde (2008).”
The (not so) squeezed limit of the primordial 3-point function (2011, methodology): “In order to estimate how the halo bias depends on the bispectrum, we use the following expression derived in [5] for an analytical estimate of the correction to the halo bias due to primordial nonGaussianity(7): ∆bh(k,R) bh = δc D(z)MR(k) 1 8π2σ2 R ∫ ∞”
The clustering of galaxies in the SDSS-III DR9 Baryon Oscillation Spectroscopic Survey: constraints on primordial non-Gaussianity (2012, background): “1 in the limit where k-space triangle configurations satisfy |~k12| |~k13|, |~k23| (known as the “squeezed” limit), it has been shown that a bias in the dark matter halo power spectrum proportional to f localNL k −2 would result (Dalal et al. 2008; Matarrese & Verde 2008).”
Scale-dependent bias induced by local non-Gaussianity: a comparison to N-body simulations (2008, background): “As shown in Dalal et al. (2008), Matarrese & Verde (2008) and Slosar et al. (2008), local non-Gaussianity gives rise to the scale-dependent bias correction eq.”
Primordial Non-Gaussianity and Bispectrum Measurements in the Cosmic Microwave Background and Large-Scale Structure (2010, methodology): “A first conservative estimate of the possibilities offered by this method in measurements of the galaxy bispectrum in the 2dF Galaxy Redshift Survey (Colless et al., 2001) and in the Sloan Digital Sky Survey (SDSS York et al., 2000) is given in Verde et al. (2000) as a simple extension of previous r”
Halo mass function and scale-dependent bias from N-body simulations with non-Gaussian initial conditions (2008, methodology): “Similar calculations have been presented by Matarrese & Verde (2008), Slosar et al. (2008), Afshordi & Tolley (2008) and McDonald (2008).”
Large-scale bias and efficient generation of initial conditions for nonlocal primordial non-Gaussianity (2011, background): “2) of the primordial bispectrum [9, 10, 22–24].”
Formation of Galaxy Clusters (2012, result): “As was discovered by Dalal et al. (2008) and confirmed in subsequent analytical (Afshordi & Tolley 2008; Matarrese & Verde 2008; McDonald 2008; Slosaret al. 2008; Taruya, Koyama & Matsubara 2008) and numerical studies (Desjacques, S ljak & Iliev 2009; Grossi et al. 2009; Pillepich, Porciani & Hahn…”
Probing primordial non-Gaussianity with SKA galaxy redshift surveys: a fully relativistic analysis (2014, background): “PNG modulates the formation of haloes in the cold dark matter, inducing a scale (and redshift) dependence in the halo bias (Dalal et al. 2008; Matarrese & Verde 2008).”
Primordial non-Gaussianity from the large-scale structure (2010, background): “The derivation of [145], based on the clustering of regions of the smoothed density field δM above threshold δc(z), is formally valid for high density peaks only.”
PRIMORDIAL NON-GAUSSIANITY, SCALE-DEPENDENT BIAS, AND THE BISPECTRUM OF GALAXIES (2009, methodology): “This approach is especially well suited for our purposes, as Matarrese & Verde (2008) have applied the MLB formula to compute the scale-dependent bias of the galaxy power spectrum.”
Cosmology with Phase 1 of the Square Kilometre Array Red Book 2018: Technical specifications and performance forecasts (2018, neutral): “In particular, PNG of the local type fNL introduces a scale-dependent correction to clustering bias (Dalal et al. 2008; Matarrese & Verde 2008) such that bHI ∝ fNL/k2.”