IN2P3/IRFU Machine Learning workshop 2026

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

17 nov. 2026, 15:10

20m

Amphitheatre (LPSC)

Standard talks AI for Physics Analysis, Inference and Discovery AI for Physics Analysis, Inference and Discovery

Orateur

Alice Spadaro (L2I Toulouse, CNRS/IN2P3, Université de Toulouse)

Description

The Laser Interferometer Space Antenna (LISA) is a future space-based gravitational-wave observatory designed to detect low-frequency gravitational waves, including those produced by massive black-hole binaries. I will present a machine-learning framework based on normalizing flows for rapid Bayesian parameter estimation of these sources. The method is trained on simulated LISA signals and can generate thousands of posterior samples in seconds, while maintaining good agreement with traditional inference methods over a broad range of signal-to-noise ratios. I will discuss the performance and current limitations of the approach, as well as future developments towards more realistic LISA data analysis.