标题： 哪个是哪个？ 引力波双星中两个致密天体的识别 显示英文标题

标题： Which is which? Identification of the two compact objects in gravitational-wave binaries

摘要： 在引力波天文学中观察到的致密天体始终成对出现，而不会单独出现。 识别双星系统的两个组成部分是一项精细的操作，通常被视作理所当然。 标记过程（即哪个是物体“1”，哪个是物体“2”）在引力波数据推断中实际上起到了系统误差的作用，或者等效地，是一种未明确说明的先验。 常见的做法是根据质量单独对每个样本进行标记。 我们表明，可以使用后验分布整体来解决物体识别问题。 我们将这个问题表述为约束聚类——一种半监督机器学习的方法——并发现解开标记系统误差可以显著影响，或者说改善我们对数据的解释。 特别是，黑洞自旋测量的精度可以提高多达50%，多模态性和尾部趋势会消失，后验分布更接近高斯分布，并且更容易识别物体的性质（即黑洞与中子星）。 我们估计大约10%的LIGO/Virgo后验样本受到这种重新标记的影响，即它们可能被错误地归因于观测到的双星系统中的另一个致密天体。 显示英文摘要

摘要： Compact objects observed in gravitational-wave astronomy so far always come in pairs and never individually. Identifying the two components of a binary system is a delicate operation that is often taken for granted. The labeling procedure (i.e., which is object "1" and which is object "2") effectively acts as systematics, or, equivalently an unspecified prior, in gravitational-wave data inference. The common approach is to label the objects solely by their masses, on a sample-by-sample basis. We show that object identification can instead be tackled using the posterior distribution as a whole. We frame the problem in terms of constrained clustering -- a flavor of semi-supervised machine learning -- and find that unfolding the labeling systematics can significantly impact, and arguably improve, our interpretation of the data. In particular, the precision of black-hole spin measurements improves by up to 50%, multimodalities and tails tend to disappear, posteriors become closer to Gaussian distributions, and the identification of the nature of the object (i.e. black hole vs. neutron star) is facilitated. We estimate that about 10% of the LIGO/Virgo posterior samples are affected by this relabeling, i.e. they might have been attributed to the other compact object in the observed binaries.