4.7 Article

Imprints of primordial non-Gaussianities in X-ray and SZ signals from galaxy clusters

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 402, Issue 2, Pages 923-933

Publisher

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2009.15978.x

Keywords

methods: N-body simulations; methods: statistical; galaxies: clusters: general; cosmology: theory; large-scale structure of Universe-X-rays: galaxies: clusters

Funding

  1. ANR [ANR-06-JCJC-0141]
  2. DFG
  3. ASI [I/016/07/0, ASI-INAF I/023/05/0, ASI-INAF I/088/06/0]
  4. Agence Nationale de la Recherche (ANR) [ANR-06-JCJC-0141] Funding Source: Agence Nationale de la Recherche (ANR)

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Several inflationary models predict the possibility that the primordial perturbations of the density field may contain a degree of non-Gaussianity which would influence the subsequent evolution of cosmic structures at large scales. In order to study their impact, we use a set of three cosmological dark-matter-only simulations starting from initial conditions with different levels of non-Gaussianity: f(NL) = 0, +/- 100. More specifically, we focus on the distribution of galaxy clusters at different redshifts and, using suitable scaling relations, we determine their X-ray and Sunyaev-Zel'dovich signals. Our analysis allows us to estimate the differences in log N-log S and log N-log Y due to the different initial conditions and to predict the cluster counts at different redshifts expected for future surveys (eROSITA and SPT). We also use a second set of simulations assuming a different cosmological scenario to estimate how the dependence on f(NL) is degenerate with respect to other parameters. Our results indicate that the effects introduced by a realistic amount of primordial non-Gaussianity are small when compared to the ones connected with current uncertainties in cosmological parameters, particularly with sigma(8). However, if future surveys will be associated with optical follow-up campaigns to determine the cluster redshift, an analysis of the samples at z > 1 can provide significant constraints on f(NL). In particular, we predict that the SPT cluster survey will be able to detect similar to 1000 clusters at z > 1 for the Gaussian case, with a difference of 15-20 per cent associated with f(NL) = +/- 100.

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