Statistics of the Sunyaev-Zel'dovich effect power spectrum

Peel, M.; Battye, Richard A.; Kay, Scott T.

doi:10.1111/j.1365-2966.2009.15121.x

Cited by 8 publications

(7 citation statements)

References 69 publications

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“…This can be quantified by the reduction in skewness between the unmasked and masked distributions from 2.2, 1.2, 0.7, and 0.4 (unmasked) to 0.5, 0.5, 0.4, and 0.2 (masked) at = 1000, 2500, 6000, and 10,000. We note that, as demonstrated by Zhang & Sheth (2007) and Peel et al 2009, the level of non-Gaussianity is also expected to decrease with increasing map area. For example, we find that the skewness in a sample of (unmasked) 169 deg 2 simulated maps measured at the same multipole numbers is 0.7, 0.7, 0.4, and 0.5.…”

Section: Masking Clustersmentioning

confidence: 52%

Sharpening the Precision of the Sunyaev-Zel'dovich Power Spectrum

Shaw

Zahn

Holder

et al. 2009

ApJ

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Using both halo model calculations and a large sample of simulated SZ maps, we demonstrate that high-mass clusters add significant non-Gaussian variance to measurements of the SZ power spectrum amplitude. The difficulty in correctly accounting theoretically for the contribution of these objects to the uncertainty in C leads to a reduced sensitivity to σ 8 . We show that a simple solution is to mask out the brightest clusters in the map before measuring the power spectrum. We demonstrate that fairly conservative masking can reduce the variance and Gaussianize the statistics significantly, thus increasing the sensitivity to cosmological parameters. Choosing which objects to mask is nontrivial; we found that using a fixed sky density produced a well-defined and well-behaved estimate that can easily be applied to real maps. For example, masking the 10 (90) brightest clusters in a 100 deg 2 SZ map will improve the sensitivity to C by a factor of two at = 1000 (2000) and 1.5 at = 2000 (4000). We show that even in the presence of astrophysical foregrounds (primary cosmic microwave background and point sources) and instrument noise, one can increase the precision on measurements of σ 8 by masking up to 0.9 clusters deg −2 .

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Section: Masking Clustersmentioning

confidence: 52%

Sharpening the Precision of the Sunyaev-Zel'dovich Power Spectrum

Shaw

Zahn

Holder

et al. 2009

ApJ

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“…Refregier et al 2000;Seljak et al 2001;Springel et al 2001;da Silva et al 2001;Bond et al 2002Bond et al , 2005Hallman et al 2007;Battaglia et al 2010) and semi-analytical/numerical calculations (e.g. Komatsu & Seljak 2002;Holder et al 2007;Moodley et al 2009;Peel et al 2009;Shaw et al 2010). However, there are still factor of ∼ 2 differences amongst the various predictions, even after correcting for different cosmologies using the approximate scaling Seljak et al 2001;Komatsu & Seljak 2002).…”

Section: Resultsmentioning

confidence: 99%

Templates for the Sunyaev-Zel’dovich Angular Power Spectrum

Trac

Bode

Ostriker

2011

ApJ

108

182

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We present templates for the Sunyaev-Zel'dovich (SZ) angular power spectrum based on four models for the nonlinear gas distribution. The frequency-dependent SZ temperature fluctuations, with thermal (TSZ) and kinetic (KSZ) contributions, are calculated by tracing through a dark matter simulation, processed to include gas in dark matter halos and in the filamentary intergalactic medium. Different halo gas models are compared to study how star formation, energetic feedback, and nonthermal pressure support influence the angular power spectrum. The standard model has been calibrated to reproduce the stellar and gas fractions and X-ray scaling relations measured from low redshift clusters and groups. The other models illustrate the current theoretical and empirical uncertainties relating to properties of the intracluster medium. Relative to the standard model, their angular power spectra differ by approximately ±50% (TSZ), ±20% (KSZ), and ±40% (SZ at 148 GHz) for l = 3000, σ 8 = 0.8, and homogeneous reionization at z = 10. The angular power spectrum decreases in amplitude as gas mass and binding energy is removed through star formation, and as gas is pushed out to larger radii by energetic feedback. With nonthermal pressure support, less pressure is required to maintain hydrostatic equilibrium, thus reducing the thermal contribution to the SZ power. We also calculate the SZ templates as a function of σ 8 and quantify this dependence. Assuming C l ∝ (σ 8 /0.8) α , the effective scaling index ranges from 7 α TSZ 9, 4.5 α KSZ 5.5, and 6.5 α SZ (148 GHz) 8 at l = 3000 for 0.6 < σ 8 < 1. The template spectra are publicly available and can be used when fitting for the SZ contribution to the cosmic microwave background on arcminute scales. Subject headings: cosmology: theory -cosmic microwave background -large-scale-structure of universe -galaxies: clusters: general -intergalactic medium -methods: numerical 1

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“…The code was tested by other groups, who confirmed its accuracy in reproducing merger histories (Li et al 2007;Zhao et al 2009) and velocities of DM halos (Heisenberg et al 2011). It was also used by several groups to study, e.g., DM halo density profiles (Lu et al 2006) and concentrations (Zhao et al 2003), the Sunyaev-Zeldovich effect in clusters (Peel et al 2009) the properties of X-ray-selected clusters (Pierre et al 2011), galaxy clustering (Zheng et al 2007), the formation of the first stars (Schneider et al 2006) and of supermassive black holes (Jahnke & Macciò 2011).…”

Section: Introductionmentioning

confidence: 95%

An accurate tool for the fast generation of dark matter halo catalogues

Monaco

Sefusatti

Borgani

et al. 2013

Monthly Notices of the Royal Astronomical Society

136

139

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We present a new parallel implementation of the PINpointing Orbit Crossing-Collapsed HIerarchical Objects (PINOCCHIO) algorithm, a quick tool, based on Lagrangian Perturbation Theory, for the hierarchical build-up of Dark Matter (DM) halos in cosmological volumes. To assess its ability to predict halo correlations on large scales, we compare its results with those of an N-body simulation of a 3 h −1 Gpc box sampled with 2048 3 particles taken from the MICE suite, matching the same seeds for the initial conditions. Thanks to the FFTW libraries and to the relatively simple design, the code shows very good scaling properties. The CPU time required by PINOCCHIO is a tiny fraction (∼ 1/2000) of that required by the MICE simulation. Varying some of PINOCCHIO numerical parameters allows one to produce a universal mass function that lies in the range allowed by published fits, although it underestimates the MICE mass function of Friends-of-Friends (FoF) halos in the high mass tail. We compare the matter-halo and the halo-halo power spectra with those of the MICE simulation and find that these 2-point statistics are well recovered on large scales. In particular, when catalogs are matched in number density, agreement within ten per cent is achieved for the halo power spectrum. At scales k > 0.1 h Mpc −1 , the inaccuracy of the Zel'dovich approximation in locating halo positions causes an underestimate of the power spectrum that can be modeled as a Gaussian factor with a damping scale of d = 3 h −1 Mpc at z = 0, decreasing at higher redshift. Finally, a remarkable match is obtained for the reduced halo bispectrum, showing a good description of nonlinear halo bias. Our results demonstrate the potential of PINOCCHIO as an accurate and flexible tool for generating large ensembles of mock galaxy surveys, with interesting applications for the analysis of large galaxy redshift surveys.

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Statistics of the Sunyaev-Zel'dovich effect power spectrum

Cited by 8 publications

References 69 publications

Sharpening the Precision of the Sunyaev-Zel'dovich Power Spectrum

Sharpening the Precision of the Sunyaev-Zel'dovich Power Spectrum

Templates for the Sunyaev-Zel’dovich Angular Power Spectrum

An accurate tool for the fast generation of dark matter halo catalogues

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