论文标题
宇宙均匀性量表估计是穿着的
Cosmological homogeneity scale estimates are dressed
论文作者
论文摘要
我们研究数量统计数据是宇宙中物质分布的均匀性过渡的度量,并分析了假定的调查选择函数如何“打扮”这种统计数据。由于估计的调查选择函数(理想情况下是观察到的分布中的选择偏差)部分退化,因此星系的估计潜在分布,识别正确的调查选择功能的能力对于获得群集统计的可靠估计值很重要。现有星系目录的选择功能是从数据模拟的,以类似于观察到的星系的红移分布和平均密度。提出的对即将进行调查的选择函数的估计值还使用星系的角度分布来生成角选择函数,而不是使用角度完整性估计值。我们认为,选择功能的这种建模可能可能低估现有目录探测的量表的均匀性的偏差。我们调查了传统应用方法对玩具模型设置中球体统计中数字计数估计估计调查选择功能的影响。该示例密度分布在渐近上是均匀的,而非线性密度波动在区域存在。我们发现,当调用调查选择函数的常规估计值时,具有与调查特征量表相当的周期范围的密度振荡将被抑制,从而导致数量计数统计量,这些统计量偏向同质性。对于我们的最大密度对比度为1的混凝土玩具模型,密度振荡的周期与调查半径相当,我们发现同质性量表被低估了约40%,但是该定量结果取决于模型设置。
We investigate number count statistics as measures for transition to homogeneity of the matter distribution in the Universe and analyse how such statistics might be `dressed' by the assumed survey selection function. Since the estimated survey selection function -- which ideally accounts for selection bias in the observed distribution -- is partially degenerate with the estimated underlying distribution of galaxies, the ability to identify the correct survey selection function is of importance for obtaining reliable estimates for clustering statistics. Selection functions of existing galaxy catalogues are modelled from data to resemble the redshift distribution and mean density of the observed galaxies. Proposed estimates of the selection function for upcoming surveys in addition use the angular distribution of galaxies to generate the angular selection function instead of using angular completeness estimates. We argue that such modelling of the selection function could potentially underestimate the deviance from homogeneity at scales probed by existing catalogues. We investigate the impact of conventionally applied methods for estimation of the survey selection function on number count in sphere statistics in a toy model setting. The example density distribution is asymptotically homogeneous, while non-linear density fluctuations are present regionally. We find that density oscillations with period comparable to characteristic scales of the survey are suppressed when conventional estimates of the survey selection function are invoked, resulting in number count statistics that are biased towards homogeneity. For our concrete toy model with maximum density contrasts of 1 and period of the density oscillation comparable in size to the survey radius, we find that the homogeneity scale is underestimated by ~40%, however this quantitative result is dependent on the model setup.