arXiv 0806.17422008-06-10astro-ph

点源成团对具有CMB各向异性的宇宙学参数的影响

Impact of Point Source Clustering on Cosmological Parameters with CMB Anisotropies

Paolo Serra, Asantha Cooray, Alexandre Amblard, Luca Pagano, Alessandro Melchiorri

备注：: 10 pages, 7 figures
发表信息：: Phys.Rev.D78:043004,2008
DOI：: 10.1103/PhysRevD.78.043004

摘要：

在宇宙微波背景（CMB）各向异性图中无法分辨的微弱射电点源很可能是大尺度结构暗物质分布的有偏示踪。虽然散粒噪声的贡献，未解决的无线电点源的角功率谱被包括在最佳构建的CMB角功率谱时，与WMAP数据，或当提取宇宙学参数，我们建议，聚类部分的点源功率谱也应该包括在内。这是特别必要的，在150 GHz以上的高频率，其中远红外源的集群预计占主导地位的散粒噪声水平的角功率谱在几十弧分角尺度的无线电和亚毫米源。我们在WMAP和ACBAR中对未分辨射电源的源聚类进行了估计，并在模型拟合宇宙学参数时对每个CMB数据集中的源聚类幅度进行了边缘化。对于WMAP 5年数据和ACBAR的组合，我们发现光谱指数从$0.963 \pm 0.014$的值变化到$0.959 \pm 0.014$（68%置信度）当点源的聚类功率谱包含在模型拟合中时。虽然我们发现，在当前数据中，有和没有源聚类的差异是微不足道的，但可能有必要用未来的数据集（如普朗克）来解释源聚类，特别是在角分角度尺度下正确地建模拟合各向异性。如果不考虑聚类并且用仅达到$l \sim 2000$的散粒噪声对点源进行建模，则谱指数将有大约1.5 $σ$的偏差。

英文摘要：

The faint radio point sources that are unresolved in cosmic microwave background (CMB) anisotropy maps are likely to be a biased tracer of the large-scale structure dark matter distribution. While the shot-noise contribution to the angular power spectrum of unresolved radio point sources is included either when optimally constructing the CMB angular power spectrum, as with WMAP data, or when extracting cosmological parameters, we suggest that clustering part of the point source power spectrum should also be included. This is especially necessary at high frequencies above 150 GHz, where the clustering of far-IR sources is expected to dominate the shot-noise level of the angular power spectrum at tens of arcminute angular scales of both radio and sub-mm sources. We make an estimate of source clustering of unresolved radio sources in both WMAP and ACBAR, and marginalize over the amplitude of source clustering in each CMB data set when model fitting for cosmological parameters. For the combination of WMAP 5-year data and ACBAR, we find that the spectral index changes from the value of $0.963 \pm 0.014$ to $0.959 \pm 0.014$ (at 68% c.l.) when the clustering power spectrum of point sources is included in model fits. While we find that the differences are marginal with and without source clustering in current data, it may be necessary to account for source clustering with future datasets such as Planck, especially to properly model fit anisotropies at arcminute angular scales. If clustering is not accounted and point sources are modeled with a shot-noise only out to $l \sim 2000$, the spectral index will be biased by about 1.5$σ$.

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