Speaker
Description
The LIGO-Virgo-KAGRA (LVK) collaboration has detected over 300 gravitational-wave events, mostly from binary black hole (BBH) mergers. These detections enable precise inference of BBH population properties such as masses, redshift, and spins. However, the conventional spin prior—uniform in spin magnitude and isotropic in orientation—assigns near-zero probability density near effective spin |Xeff| = 1 and precession spin Xp = 0, potentially biasing hierarchical Bayesian population inference in these regions due to limited posterior samples. We propose a new spin prior that is uniform in both the Xeff and Xp parameters, conditioned on mass ratio. Using simulated BBH populations, we compare parameter estimation and hierarchical inference results between the conventional and new priors. Our results show that populations concentrated in low-probability-density regions(e.g |Xeff| = 1, Xp = 0) cannot be reliably inferred with the conventional prior, while the new prior mitigates this bias.
