论文标题
通过嵌套采样分析的Ligo-Virgo GWTC-2事件的订单统计信息
An Order Statistics Post-Mortem on LIGO-Virgo GWTC-2 Events Analysed with Nested Sampling
论文作者
论文摘要
Ligo-Virgo合作进行的有关重力波事件的数据分析利用嵌套采样来计算贝叶斯证据和后验分布来推断紧凑型二进制文件的源特性。由于受约束的先验采样差，嵌套的采样算法可能会误射，并且无法忠实地对后验分布进行采样。 Fowlie等。 （2020）概述了一种使用似然插入顺序统计信息验证嵌套采样性能或识别参数空间中高原等病理的方法。在这里，该方法应用于Ligo-Virgo协作的第一和第二引力波瞬态目录（GWTC-1和GWTC-2）中所有事件的嵌套采样分析。插入顺序统计数据在目录中的45个事件中测试了均匀性，发现，除了少数例外对最终后代的影响可忽略不计，目录中事件分析的数据与无偏见的先前采样一致。但是，在目录级的元测试时反对均匀性的证据很弱，产生了1.44 * 10-3的kolmogorov-smirnov meta-p值。
The data analysis carried out by the LIGO-Virgo collaboration on gravitational-wave events utilizes nested sampling to compute Bayesian evidences and posterior distributions for inferring the source properties of compact binaries. With poor sampling from the constrained prior, nested sampling algorithms may misbehave and fail to sample the posterior distribution faithfully. Fowlie et al. (2020) outlines a method of validating the performance of nested sampling, or identifying pathologies such as plateaus in the parameter space, using likelihood insertion order statistics. Here, this method is applied to nested sampling analyses of all events in the first and second gravitational wave transient catalogs (GWTC-1 and GWTC-2) of the LIGO-Virgo collaboration. The insertion order statistics are tested for uniformity across 45 events in the catalog and it is found that, with a few exceptions that have negligible effect on the final posteriors, the data from the analysis of events in the catalog is consistent with unbiased prior sampling. There is, however, weak evidence against uniformity at the catalog-level meta-test, yielding a Kolmogorov-Smirnov meta-p-value of 1.44 * 10-3.
