论文标题
弱透镜中的密度分裂统计量的适应过滤器函数
An adapted filter function for density split statistics in weak lensing
论文作者
论文摘要
语境。弱重力透镜中的密度分裂统计分析可探测不同(前景)星系数密度及其弱透镜信号的区域之间的相关性,该统计是通过背景星系的形状变形来测量的。目标。在本文中,我们通过构建一个新的角滤波器函数来重新考虑密度分割统计数据,该函数适合于星系数密度和剪切模式之间的预期关系,以使加权星系数密度与用于量化剪切信号的过滤器相匹配。方法。我们使用数值射线追踪模拟的结果,特别是通过基于半分析模型的星系分布补充的千年模拟,构建了一对匹配的适应性滤波器功能,以用于星系密度和切向剪切信号。我们将新过滤器的性能与先前使用的顶级滤波器进行了比较,并将其应用于不同和独立的数值模拟集(SLIC,COSMO-SLICS)。结果。我们表明,适应过滤器在总物质和星系分布之间产生更好的相关性。此外,改编的过滤器提供了更大的信噪比,以限制总物质和星系分布之间的偏差,并且我们表明,除了具有非常大的$σ_8$值的宇宙学外,通常在不同宇宙学之间具有更敏感的歧视器。所有分析都得出结论,即我们的适应过滤器应在未来的密度分配统计工作中受到青睐。
Context. The density split statistics in weak gravitational lensing analyses probes the correlation between regions of different (foreground) galaxy number densities and their weak lensing signal, measured by the shape distortion of background galaxies. Aims. In this paper, we reconsider density split statistics, by constructing a new angular filter function that is adapted to the expected relation between galaxy number density and shear pattern, in a way that the filter weighting the galaxy number density is matched to the filter that is used to quantify the shear signal. Methods. We use the results of numerical ray-tracing simulations, specifically through Millennium Simulation supplemented by a galaxy distribution based on a semi-analytic model, to construct a matched pair of adapted filter functions for the galaxy density and the tangential shear signal. We compare the performance of our new filter to the previously used top-hat filter, applying both to a different and independent set of numerical simulations (SLICS, cosmo-SLICS). Results. We show that the adapted filter yields a better correlation between the total matter and the galaxy distribution. Furthermore, the adapted filter provides a larger signal-to-noise ratio to constrain the bias between the total matter and the galaxy distribution, and we show that it is, in general, a more sensitive discriminator between different cosmologies, with the exception of cosmologies with very large $σ_8$ values. All analyses lead to the conclusion that our adapted filter should be favored in future density split statistic works.