A Random Walk through Models of Nonlinear Clustering

Sheth, Ravi K.

doi:10.1111/j.1749-6632.2001.tb05617.x

Cited by 8 publications

(7 citation statements)

References 23 publications

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“…Interestingly, the form of n eff dependence modelled in peaks theory (e.g. Sheth 2001) predicts a smaller difference between the numbers of high‐ and low‐redshift haloes than we find in our simulations.…”

Section: Resultssupporting

confidence: 47%

The halo mass function from the dark ages through the present day

Reed

Bower

Frenk

et al. 2007

Monthly Notices of the Royal Astronomical Society

360

389

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We use an array of high-resolution N-body simulations to determine the mass function of dark matter haloes at redshifts 10-30. We develop a new method for compensating for the effects of finite simulation volume that allows us to find an approximation to the true ``global'' mass function. By simulating a wide range of volumes at different mass resolution, we calculate the abundance of haloes of mass 10^{5-12} Msun/h. This enables us to predict accurately the abundance of the haloes that host the sources that reionize the universe. In particular, we focus on the small mass haloes (>~10^{5.5-6} Msun/h) likely to harbour population III stars where gas cools by molecular hydrogen emission, early galaxies in which baryons cool by atomic hydrogen emission at a virial temperature of ~10^4K (10^{7.5-8} Msun/h), and massive galaxies that may be observable at redshift ~10. When we combine our data with simulations that include high mass halos at low redshift, we find that the best fit to the halo mass function depends not only on linear overdensity, as is commonly assumed in analytic models, but also upon the slope of the linear power spectrum at the scale of the halo mass. The Press-Schechter model gives a poor fit to the halo mass function in the simulations at all epochs; the Sheth-Tormen model gives a better match, but still overpredicts the abundance of rare objects at all times by up to 50%. Finally, we consider the consequences of the recently released WMAP 3-year cosmological parameters. These lead to much less structure at high redshift, reducing the number of z=10 ``mini-haloes'' by more than a factor of two and the number of z=30 galaxy hosts by more than four orders of magnitude. Code to generate our best-fit halo mass function may be downloaded from http://icc.dur.ac.uk/Research/PublicDownloads/genmf_readme.htmlComment: MNRAS accepted. Changes in response to referee comments, including discussion of uncertainties with 2 additional plots. Corrected version of 2 plots showing mass function dependence on cosmological parameters (WMAP3 vs WMAP1). Conclusions unchanged. Code to reproduce this mass function can be downloaded at http://icc.dur.ac.uk/Research/PublicDownloads/genmf_readme.htm

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Section: Resultssupporting

confidence: 47%

The halo mass function from the dark ages through the present day

Reed

Bower

Frenk

et al. 2007

Monthly Notices of the Royal Astronomical Society

360

389

View full text Add to dashboard Cite

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“…Carefully accounting for clouds in clouds in the peak formalism is a nontrivial problem even though, in a first approximation, we may simply enforce that the height of the peak be less than sc on scale R S þ dR S [132,133]. Figure 1 of [80] demonstrates that this substantially improves the agreement with the measured halo abundances at * 3 but underestimates the counts at & 2. Furthermore, adding this extra constraint also modifies the peak bias factors and, possibly, theb II -independent terms in Eq.…”

Section: E Scale Dependence Across the Acoustic Peakmentioning

confidence: 99%

“…Peak abundances, profiles, and correlation functions in real and redshift space have been studied in the literature [36,[65][66][67][68][69][70][71][72][73][74][75]. Some of these results have been used to interpret the abundance and clustering of rich clusters [42,[76][77][78][79][80], constrain the power spectrum of mass fluctuations [81,82], and study evolution bias [83] and assembly bias [84].…”

Section: Introductionmentioning

confidence: 99%

Modeling scale-dependent bias on the baryonic acoustic scale with the statistics of peaks of Gaussian random fields

2010

Self Cite

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Models of galaxy and halo clustering commonly assume that the tracers can be treated as a continuous field locally biased with respect to the underlying mass distribution. In the peak model pioneered by Bardeen et al. (1986), one considers instead density maxima of the initial, Gaussian mass density field as an approximation to the formation site of virialized objects. In this paper, the peak model is extended in two ways to improve its predictive accuracy. Firstly, we derive the two-point correlation function of initial density peaks up to second order and demonstrate that a peak-background split approach can be applied to obtain the k-independent and k-dependent peak bias factors at all orders. Secondly, we explore the gravitational evolution of the peak correlation function within the Zel'dovich approximation. We show that the local (Lagrangian) bias approach emerges as a special case of the peak model, in which all bias parameters are scale-independent and there is no statistical velocity bias. We apply our formulae to study how the Lagrangian peak biasing, the diffusion due to large scale flows and the mode-coupling due to nonlocal interactions affect the scale dependence of bias from small separations up to the baryon acoustic oscillation (BAO) scale. For 2σ density peaks collapsing at z = 0.3, our model predicts a ∼5% residual scale-dependent bias around the acoustic scale that arises mostly from first-order Lagrangian peak biasing (as opposed to second-order gravity mode-coupling). We also search for a scale dependence of bias in the large scale auto-correlation of massive halos extracted from a very large N-body simulation provided by the MICE collaboration. For halos with mass M 10 14 M⊙/h, our measurements demonstrate a scale-dependent bias across the BAO feature which is very well reproduced by a prediction based on the peak model.

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“…We then compared the number of structures with M members (N M ) with the expectation value using the toy model of Sheth (2001). Within the data set, the number of systems with M 4 30 < < galaxies identified using the Friends-of-friends algorithm always exceeded the expected, Poissonian value in our analysis.…”

Section: Confirmation Tests Of Structurementioning

confidence: 99%

THE CANDIDATE CLUSTER AND PROTOCLUSTER CATALOG (CCPC) OF SPECTROSCOPICALLY IDENTIFIED STRUCTURES SPANNING 2.74 < z < 3.71

Franck

McGaugh

2016

ApJ

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We developed a search methodology to identify galaxy protoclusters at z 2.74 > and implemented it on a sample of ∼14,000 galaxies with previously measured redshifts. The results of this search are recorded in the Candidate Cluster and Protocluster Catalog (CCPC). The catalog contains 12 clusters that are highly significant overdensities ( 7 gal d > ), 6 of which were previously known. We also identify another 31 candidate protoclusters (including four previously identified structures) of lower overdensities. CCPC systems vary over a wide range of physical sizes and shapes, from small, compact groups to large, extended, and filamentary collections of galaxies. This variety persists in the range from z = 3.71 to z = 2.74. These structures exist as galaxy overdensities ( gal d ) with a mean value of 2, similar to the values found for other protoclusters in the literature. The median number of galaxies for CCPC systems is 11. Virial mass estimates are large for these redshifts, with 13 cases apparently having M M 10 15 >  . If these systems are virialized, such masses would pose a challenge to ΛCDM.

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A Random Walk through Models of Nonlinear Clustering

Cited by 8 publications

References 23 publications

The halo mass function from the dark ages through the present day

The halo mass function from the dark ages through the present day

Modeling scale-dependent bias on the baryonic acoustic scale with the statistics of peaks of Gaussian random fields

THE CANDIDATE CLUSTER AND PROTOCLUSTER CATALOG (CCPC) OF SPECTROSCOPICALLY IDENTIFIED STRUCTURES SPANNING 2.74 < z < 3.71

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