Evolution of the cluster abundance in non-Gaussian models

Robinson, James C.; Baker, Jonathan

doi:10.1046/j.1365-8711.2000.03109.x

Cited by 61 publications

(76 citation statements)

References 32 publications

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“…o M \ 0), tive expression for f, used by some authors (e.g., Robinson & Baker 2000). In the most general case, however, the latter result is not valid.…”

Section: Press-schechter Approach To Non-gaussian Density Fieldsmentioning

confidence: 96%

The Abundance of High‐Redshift Objects as a Probe of Non‐Gaussian Initial Conditions

Matarrese

Verde

Jiménez

2000

ApJ

268

489

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The observed abundance of high-redshift galaxies and clusters contains precious information about the properties of the initial perturbations. We present a method to compute analytically the number density of objects as a function of mass and redshift for a range of physically motivated non-Gaussian models. In these models the non-Gaussianity can be dialed from zero and is assumed to be small. We compute the probability density function for the smoothed dark matter density Ðeld, and we extend the PressSchechter approach to mildly non-Gaussian density Ðelds. The abundance of high-redshift objects can be directly related to the non-Gaussianity parameter and thus to the physical processes that generated deviations from the Gaussian behavior. Even a skewness parameter of order 0.1 implies a dramatic change in the predicted abundance of objects. Observations from the Next Generation Space T elescope z Z 1 (NGST ) and X-ray satellites (XMM) can be used to accurately measure the amount of non-Gaussianity in the primordial density Ðeld.

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“…o M \ 0), tive expression for f, used by some authors (e.g., Robinson & Baker 2000). In the most general case, however, the latter result is not valid.…”

Section: Press-schechter Approach To Non-gaussian Density Fieldsmentioning

confidence: 96%

The Abundance of High‐Redshift Objects as a Probe of Non‐Gaussian Initial Conditions

Matarrese

Verde

Jiménez

2000

ApJ

268

489

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“…The standard observables to constrain non-Gaussianity are the cosmic microwave background and large-scale structure. A powerful technique is based on the abundance (Matarrese et al 2000;Verde et al 2001;LoVerde et al 2007;Robinson & Baker 2000; and clustering (Grinstein & Wise 1986;Matarrese et al 1986;Lucchin et al 1988) of rare events such as dark matter density peaks as they trace the tail of the underlying distribution. These theoretical predictions have been tested against numerical N-body simulations (Kang et al 2007;Grossi et al 2007;Dalal et al 2007).…”

Section: Introductionmentioning

confidence: 99%

The Effect of Primordial Non-Gaussianity on Halo Bias

Matarrese¹,

Verde²

2008

ApJ

422

650

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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.

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“…In addition, various aspects of large‐scale structure have also been examined as probes of non‐Gaussianity. These include halo abundances and bias (Lucchin, Matarrese & Vittorio 1988; Koyama, Soda & Taruya 1999; Matarrese, Verde & Jimenez 2000; Robinson & Baker 2000; Afshordi & Tolley 2008; Carbone, Verde & Matarrese 2008; Desjacques, Seljak & Iliev 2008; Dalal et al 2008; Lo Verde et al 2008; Matarrese & Verde 2008; Slosar et al 2008); higher order effects on the galaxy power spectrum (Izumi & Soda 2007; McDonald 2008; Taruya, Koyama & Matsubara 2008); and the galaxy bispectrum (Scoccimarro, Sefusatti & Zaldarriaga 2004; Sefusatti & Komatsu 2007). Slosar (2009) has discussed how to optimize the constraint on f nl by applying weightings on subsamples from a single tracer.…”

Section: Introductionmentioning

confidence: 99%

The non-linear probability distribution function in models with local primordial non-Gaussianity

Lam

Sheth

2009

Monthly Notices of the Royal Astronomical Society

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We use the spherical evolution approximation to investigate non‐linear evolution from the non‐Gaussian initial conditions characteristic of the local fnl model. We provide an analytic formula for the non‐linearly evolved probability distribution function (PDF) of the dark matter which shows that the underdense tail of the non‐linear PDF in the fnl model should differ significantly from that for Gaussian initial conditions. Measurements of the underdense tail in numerical simulations may be affected by discreteness effects, and we use a Poisson counting model to describe this effect. Once this has been accounted, our model is in good quantitative agreement with the simulations. In principle, our calculation is an important first step in programs which seek to reconstruct the shape of the initial PDF from observations of large‐scale structures in the Lyα forest and the galaxy distribution at later times.

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Evolution of the cluster abundance in non-Gaussian models

Cited by 61 publications

References 32 publications

The Abundance of High‐Redshift Objects as a Probe of Non‐Gaussian Initial Conditions

The Abundance of High‐Redshift Objects as a Probe of Non‐Gaussian Initial Conditions

The Effect of Primordial Non-Gaussianity on Halo Bias

The non-linear probability distribution function in models with local primordial non-Gaussianity

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