利用k近邻分布对引力波源进行空间聚类分析
Spatial clustering of gravitational wave sources with $k$-nearest neighbour distributions
AI总结：
本文利用k近邻方法分析53个LIGO-Virgo-KAGRA双黑洞并合事件与WISE×SuperCOSMOS星表的空间聚类及互相关，未发现显著信号，指出未来探测数量与定位精度提升后将开启宇宙学新窗口。
摘要：
我们提出了一个框架，用于量化引力波（GW）瞬变源的聚类程度，并利用k近邻（kNN）形式体系测量它们与宇宙大尺度结构（LSS）的空间互相关。作为首次应用，我们测量了LIGO-Virgo-KAGRA前三轮观测运行中探测到的53个经适当选择的双黑洞（BBH）并合事件的最近邻分布，并将这些源与来自WISE×SuperCOSMOS全天巡天星表中的约1.7×10^7个星系和类星体进行互相关分析。为了在考虑GW数据中观测系统误差的同时确定聚类信号的显著性，我们创建了135个模拟BBH实现，这些实现在统计上与观测到的BBH相似，但在空间上不聚类。我们在数据中没有发现空间聚类或与LSS互相关的证据，并得出结论：目前的天空定位精度和探测数量不足以获得具有统计显著性的聚类信号。展望未来，未来LIGO（包括LIGO India）观测运行以及下一代GW探测器预期带来的统计上大量的探测数量和天空定位精度的显著提升，将使BBH-LSS互相关的测量成为可能，并为宇宙学打开一扇新的窗口。
英文摘要：
We present a framework to quantify the clustering of gravitational wave (GW) transient sources and measure their spatial cross-correlation with the large-scale structure (LSS) of the universe using the $k$-nearest neighbour ($k$NN) formalism. As a first application, we measure the nearest-neighbour distributions of 53 suitably selected Binary Black Hole (BBH) mergers detected in the first three observation runs of LIGO-Virgo-KAGRA and cross-correlate these sources with ~$1.7 \times 10^7$ galaxies and quasars from the WISE$\times$SuperCOSMOS all-sky catalogue. To determine the significance of the clustering signal while accounting for observational systematics in the GW data, we create 135 realisations of mock BBHs that are statistically similar to the observed BBHs but spatially unclustered. We find no evidence for spatial clustering or cross-correlation with LSS in the data and conclude that the present sky localisation and number of detections are insufficient to get a statistically significant clustering signal. Looking forward, the statistically large number of detections and the significant improvements in sky localisations expected from future observing runs of LIGO (including LIGO India) and the next generation of GW detectors will enable measurement of the BBH-LSS cross-correlation and open a new window into cosmology.
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