A Foundation for Gravitational-Wave Population Inference within the LISA Global Fit
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866913004346408960 |
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| author | Criswell, Alexander W. Banagiri, Sharan Delfavero, Vera Bustamante-Rosell, Maria Jose Taylor, Stephen R. Rosati, Robert |
| author_facet | Criswell, Alexander W. Banagiri, Sharan Delfavero, Vera Bustamante-Rosell, Maria Jose Taylor, Stephen R. Rosati, Robert |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_03390 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Foundation for Gravitational-Wave Population Inference within the LISA Global Fit Criswell, Alexander W. Banagiri, Sharan Delfavero, Vera Bustamante-Rosell, Maria Jose Taylor, Stephen R. Rosati, Robert Instrumentation and Methods for Astrophysics Astrophysics of Galaxies General Relativity and Quantum Cosmology 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. |
| title | A Foundation for Gravitational-Wave Population Inference within the LISA Global Fit |
| topic | Instrumentation and Methods for Astrophysics Astrophysics of Galaxies General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2604.03390 |