利用归一化流进行双黑洞的层次化总体推断
Hierarchical Population Inference with Normalizing Flows for Binary Black Holes
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中文总结 AI 辅助
本文提出基于归一化流的层次化总体推断流程，用于双黑洞质量-红移分布重建，并引入互信息诊断检验内在演化，在模拟和GWTC-5.0数据上验证了有效性。
中文摘要 AI 辅助
低维参数化质量模型是引力波总体推断的标准方法，但其刚性可能使恢复的分布及由此得出的结论产生偏差。我们提出了一种流程，其中源坐标系下的双黑洞总体在$(z,m_1,m_2)$中由归一化流表示，该流直接通过层次似然训练，事件后验样本用于传播测量不确定性，检测到的注入用于考虑选择效应。我们将总体陈述限制在注入活动支持的区域内；对这一区域的限制本身可能引发质量与红移之间的表观关联。因此，我们引入了一种互信息诊断方法，在相同的支持限制下将重建结果与红移无关的参考进行比较，以检验超出支持几何所引发依赖性的关联。我们在两个模拟目录上验证了该方法，这两个目录仅在特征主质量尺度是否随红移演化方面有所不同。重建在两种情况下均恢复了注入的质量结构，基准测试确立了诊断在存在和不存在内在演化时的行为。应用于GWTC-5.0目录时，该方法恢复了约$10\\,M_\odot$和$35\\,M_\odot$附近的特征，与LVK对同一目录的总体分析一致，并且未发现主质量谱随红移内在演化的证据。更广泛地说，该流程解决了许多观测科学中常见的问题：从成员的噪声、间接和选择偏差测量中恢复总体分布。
英文摘要
Low-dimensional parametric mass models are standard in gravitational-wave population inference, but their rigidity can bias the recovered distribution and the conclusions drawn from it. We present a pipeline in which the source-frame binary-black-hole population in $(z,m_1,m_2)$ is represented by a normalizing flow trained directly through the hierarchical likelihood, with event posterior samples propagating measurement uncertainty and detected injections accounting for selection effects. We restrict population statements to the region supported by the injection campaign; conditioning on this region can itself induce an apparent association between mass and redshift. We therefore introduce a mutual-information diagnostic that compares the reconstruction with a redshift-independent reference under the same support restriction, testing for dependence beyond that induced by the support geometry. We validate the method on two simulated catalogues differing only in whether the characteristic primary-mass scale evolves with redshift. The reconstruction recovers the injected mass structure in both, and the benchmarks establish how the diagnostic behaves in the presence and absence of intrinsic evolution. Applied to the GWTC-5.0 catalogue, the method recovers features near $10\,M_\odot$ and $35\,M_\odot$, consistent with the LVK population analysis of the same catalogue, and finds no evidence for intrinsic evolution of the primary-mass spectrum with redshift. More broadly, the pipeline addresses a problem common to many observational sciences: recovering a population distribution from noisy, indirect, and selection-biased measurements of its members.
发表机构
- Sapienza Università di Roma（罗马第一大学）
- INFN, Sezione di Roma（意大利国家核物理研究所罗马分部）
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