Simulation-based Inference for Gravitational-waves from Intermediate-Mass Binary Black Holes in Real Noise

2024/06/06 by V. Raymond, S. Al-Shammari, Raymond, Vivien +3 · 2 citations
Physics and Astronomy · #Cosmology and Gravitation Theories #FOS: Physical sciences #General Relativity and Quantum Cosmology (gr-qc) #Particle physics theoretical and experimental studies #Pulsars and Gravitational Waves Research

paper · pdf · doi:10.48550/arxiv.2406.03935

openalex publication_date 2024/06/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

We present an exploratory investigation into using Simulation-based Inference techniques, specifically Flow-Matching Posterior Estimation, to construct a posterior density estimator trained using real gravitational-wave detector noise. Our prototype estimator is trained on a 9-dimensional space, and for training efficiency outputs posterior probability distributions for the binary black holes chirp mass and mass ratio. We use this prototype estimator to investigate possible effects on parameter estimation for Intermediate-Mass Binary Black Holes, and show statistically significant reduction in measurement bias. Although the results show potential for improved measurements, they also highlight the need for further work.

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• Robust and scalable simulation-based inference for gravitational wave signals with gaps
• The impact of precession and higher-order multipoles on cosmological inference

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