论文标题
贝叶斯证据比较距离估计
Bayesian evidence comparison for distance scale estimates
论文作者
论文摘要
通过将模板拟合到由基金宇宙学模型激发的数据的汇总统计数据，通常会从天空调查中蒸馏出对宇宙参数的限制。但是，最近的工作表明了如何使用更通用的模板来估计距离尺度：所使用的基本函数并未明确绑定到任何一个宇宙学模型。我们描述了一个贝叶斯框架，用于（i）确定要使用多少个基础函数，以及（ii）将一个基集与另一个基集进行比较。我们的表述提供了（a）在不同基础集中的信念程度，（b）先验选择取决于基础集的事实，以及（c）数据集本身，共同确定派生的约束。在将其应用于真实数据之前，我们使用模拟数据集中的测量结果说明了我们的框架。
Constraints on cosmological parameters are often distilled from sky surveys by fitting templates to summary statistics of the data that are motivated by a fiducial cosmological model. However, recent work has shown how to estimate the distance scale using templates that are more generic: the basis functions used are not explicitly tied to any one cosmological model. We describe a Bayesian framework for (i) determining how many basis functions to use and (ii) comparing one basis set with another. Our formulation provides intuition into how (a) one's degree of belief in different basis sets, (b) the fact that the choice of priors depends on basis set, and (c) the data set itself, together determine the derived constraints. We illustrate our framework using measurements in simulated datasets before applying it to real data.
