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arXiv 0909.4714astro-ph.CO
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来自星系团的X射线和SZ信号中的原始非高斯性印记

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

M. Roncarelli, L. Moscardini, E. Branchini, K. Dolag, M. Grossi, F. Iannuzzi, S. Matarrese

摘要:

几个暴胀模型预测,密度场的原始扰动可能包含一定程度的非高斯性,这将影响随后的大尺度宇宙结构的演化。为了研究它们的影响,我们使用了一组三个宇宙学的DM模拟,从不同水平的非高斯初始条件开始:f_NL = 0,+/-100。更具体地说,我们专注于星系团的分布在不同的红移,并使用适当的标度关系,我们确定其X射线和SZ信号。我们的分析使我们能够估计由于不同初始条件导致的logN-logS和logN-logY的差异,并预测未来调查(eROSITA和SPT)预期的不同红移下的簇计数。我们还使用了第二组模拟假设一个不同的宇宙学的情况下,以估计如何依赖于f_NL是退化相对于其他参数。我们的研究结果表明,由一个现实的量的原始非高斯性引入的影响是小的相比,与当前的宇宙学参数的不确定性,特别是与sigma_8。然而,如果未来的调查将与光学后续活动相关联,以确定集群红移,在z> 1的样本分析可以提供重要的限制f_NL。特别是,我们预测,SPT集群调查将能够检测到约1000个集群在z> 1的高斯情况下,与15 - 20%的差异与f_NL =+/-100。

英文摘要:

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 DM-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 SZ signals. Our analysis allows us to estimate the differences in the logN-logS and logN-logY 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 ~1000 clusters at z>1 for the Gaussian case, with a difference of 15-20 per cent associated to f_NL=+/-100.

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