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arXiv · 2508.16399

Constraints on the extreme mass-ratio inspiral population from LISA data

Shashwat Singh·Christian E. A. Chapman-Bird·Christopher P L Berry·John Veitch
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Abstract

Gravitational waves from extreme mass-ratio inspirals (EMRIs), the inspirals of stellar-mass compact objects into massive black holes, are predicted to be observed by the Laser Interferometer Space Antenna (LISA). A sufficiently large number of EMRI observations will provide unique insights into the massive black hole population. We have developed a hierarchical Bayesian inference framework capable of constraining the parameters of the EMRI population, accounting for selection biases. We leverage the capacity of a feed-forward neural network as an emulator, enabling detectability calculations of $\sim10^5$ EMRIs in a fraction of a second, speeding up the likelihood evaluation by $\gtrsim6$ orders of magnitude. We validate our framework on a phenomenological EMRI population model. This framework enables studies of how well we can constrain EMRI population parameters, such as the slope of both the massive and stellar-mass black hole mass spectra and the branching fractions of different formation channels, allowing further investigation into the evolution of massive black holes.

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Shashwat Singh, Christian E. A. Chapman-Bird, Christopher P L Berry, John Veitch. 2025-08-22. Constraints on the extreme mass-ratio inspiral population from LISA data. https://doi.org/10.1088/1742-6596%2F3177%2F1%2F012113

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