Accurate and efficient simulation-based inference for massive black-hole binaries with LISA

This paper presents the very first application of DINGO to the LISA parameter-estimation problem! DINGO is an Australian animal that eats BILBY, and a powerful new gravitational-wave method for estimating source parameters. It is (at least in my view) the most modern and compelling application of AI to gravitational-wave parameter estimation, and it has already shown tremendous promise for the characterization of LIGO–Virgo sources. Even though it relies on some approximations, this paper demonstrates that the same AI-based approach can also be successfully applied to supermassive binary black holes in LISA.

A. Spadaro, J. Gair, D. Gerosa, S. R. Green, R. Buscicchio, N. Gupte, R. Tenorio, S. Clyne, M. Purrer, N. Korsakova.
arXiv:2603.20431 [astro-ph.HE].