非高斯质量函数的极尾
The Extreme Tail of the Non-Gaussian Mass Function
摘要：
大质量高红移星系团的计数为研究原初非高斯性提供了一个窗口。然而，目前的数据质量迫使统计分析探测参数空间的一个区域-质量函数的极端尾部-这在任何目前可用的计算质量函数的理论处方中都无法访问，也无法在N体模拟中校准。在这项工作中，我们提出了一个新的分析处方计算的“mummed”非高斯晕质量函数，它被构造为保持稳定的极端尾部。我们表明，处方工作良好的参数制度，目前已在模拟中探索。然后，我们使用Fisher矩阵技术来比较我们的处方与外推适合N体模拟，最近已被用来获得从南极望远镜收集的数据的约束。我们表明，对于目前的数据，这两个处方将导致统计上一致的约束。然而，随着数据的改善，由于处方的选择，有可能在约束中引入统计上显著的偏差，特别是如果非高斯性是尺度依赖的，并且在集群尺度上变得相对较大。然后，有必要在N体模拟中测试处方的准确性，该模拟可以在存在大的非高斯性的情况下探测具有高质量和红移的星系团。
英文摘要：
Number counts of massive high-redshift clusters provide a window to study primordial non-Gaussianity. The current quality of data, however, forces the statistical analysis to probe a region of parameter space -- the extreme tail of the mass function -- which is neither accessible in any of the currently available theoretical prescriptions for calculating the mass function, nor calibrated in N-body simulations. In this work we present a new analytical prescription for calculating a "resummed" non-Gaussian halo mass function, which is constructed to remain stable in the extreme tail. We show that the prescription works well in the parameter regime that has been currently explored in simulations. We then use Fisher matrix techniques to compare our prescription with an extrapolated fit to N-body simulations, which has recently been used to obtain constraints from data collected by the South Pole Telecope. We show that for the current data, both prescriptions would lead to statistically consistent constraints. As the data improve, however, there is a possibility of introducing a statistically significant bias in the constraints due to the choice of prescription, especially if non-Gaussianity is scale dependent and becomes relatively large on cluster scales. It would then be necessary to test the accuracy of the prescriptions in N-body simulations that can probe clusters with high masses and redshifts in the presence of large non-Gaussianity.
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