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arXiv 2604.03390astro-ph.IMastro-ph.GAgr-qc
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LISA全球拟合中的引力波人口推断基础

A Foundation for Gravitational-Wave Population Inference within the LISA Global Fit

Vanderbilt University（范德堡大学）；Fisk University（菲斯克大学）；Northwestern University（西北大学）；Monash University（蒙纳士大学）；University of Toronto（多伦多大学）；NASA Marshall Space Flight Center（美国国家航空航天局马歇尔太空飞行中心）；Universities Space Research Association（大学空间研究协会）；University of Alabama in Huntsville（亨茨维尔阿拉巴马大学）

Alexander W. Criswell, Sharan Banagiri, Vera Delfavero, Maria Jose Bustamante-Rosell, Stephen R. Taylor, Robert Rosati

备注：
26 pages, 7 figures; to be submitted to ApJ
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AI总结：

本文提出在LISA全球拟合中直接评估全层级人口似然的方法，开发了PELARGIR模块，并通过玩具模型验证，为引力波谱中的天体物理建模提供新路径。

摘要：

引力波天文中的群体推断使我们能够将单个探测结果与致密天体及其环境的天体物理联系起来。目前用于LIGO-Virgo-KAGRA数据的群体推断方法通过后处理单个事件后验来近似评估分层群体似然。然而，LISA的情况更为复杂，因为其数据处理采用的是跨维的“全球拟合”方法，同时存在可分辨信号和由银河系二体人口引起的未分辨随机“银河前景”，这导致了可分辨系统与未分辨系统之间以及我们检测前者能力的循环依赖。这些挑战并非没有机会；LISA的数据将包含银河系中每一个mHz致密双星，无论是单独存在还是在银河前景中，具有巨大的银河系和恒星天体物理学潜力。因此，我们提出了一种替代方法：在LISA全球拟合中直接评估完整的分层群体似然。我们开发了一种联合推断可分辨引力波源、未分辨随机前景以及共享基础天体物理群体的统计形式化方法，提出了PELARGIR，一个用于LISA全球拟合的原型GPU加速群体推断模块，并通过玩具模型分析展示了该形式化方法和PELARGIR，制定了向具有嵌入式群体推断的天体物理动机LISA全球拟合的路线图。尽管本文将该形式化方法应用于LISA银河系双星群体，但其适用于整个引力波谱，可用于脉冲星定时和下一代地面观测站。

英文摘要：

Population inference in gravitational-wave astronomy allows us to connect individual detections to the astrophysics of compact objects and their environments. Current approaches employed for population inference with LIGO-Virgo-KAGRA data approximate evaluation of the hierarchical population likelihood via post-processing of individual-event posteriors. However, the case of the Laser Interferometer Space Antenna (LISA) will be more complex for two main reasons: the transdimensional "global fit" approach to LISA data analysis which models all signals and noise simultaneously, and the presence of both individually-resolved signals and the unresolved stochastic ``Galactic foreground" arising from the Galactic binary population, which induces a circular dependence between the resolved and unresolved systems and our ability to detect the former. These challenges are not without opportunity; LISA's data will contain every mHz compact binary in the Milky Way -- either individually or within the Galactic foreground -- with great potential for Galactic and stellar astrophysics. We therefore propose an alternative approach: direct evaluation of the full hierarchical population likelihood within the LISA global fit. We develop a statistical formalism for joint inference of individually-resolved gravitational-wave sources, an unresolved stochastic foreground, and a shared, underlying astrophysical population, present PELARGIR, a prototype GPU-accelerated population inference module for the LISA global fit, demonstrate the formalism and PELARGIR via a toy model analysis, and lay out a roadmap towards an astrophysically-motivated LISA global fit with embedded population inference. While we apply the formalism here to the population of LISA Galactic binaries, it is applicable across the gravitational-wave spectrum with use cases in pulsar timing and next-generation terrestrial observatories.

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