Demonstrates direct comparison of observable compact-binary populations from GW data to astrophysical models, with unbiased inference shown possible and applied to O3 data.
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Joint strong-lensing and population inference on resolved gravitational-wave events finds no lensed events and tightens constraints on the black-hole merger rate peak redshift and high-redshift tail.
Maximum-likelihood-based posterior predictive checks detect model misspecification better than event-level versions for uncertain spin tilts, but current detector sensitivity limits their power; the Gaussian Component Spins model underpredicts high spin magnitudes and overpredicts anti-aligned tilts
B-spline agnostic reconstruction of binary black hole masses from GWTC-4.0 reveals multiple features and a logarithmic hierarchy that impacts Hubble constant measurements, with a low-mass subpopulation isolation method to mitigate systematics.
Spin sorting with the default spin model distinguishes spinning and nonspinning binary black hole populations in simulations and shows real data rule out a fully nonspinning population but allow mixed ones with up to 80% nonspinning sources.
GWKokab is a new modular JAX framework that uses normalizing flow samplers for efficient inference on subpopulations of compact binary mergers.
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