Wysocki-Bayesian Population Models

We show how to simultaneously infer the compact binary rate versus mass and other parameters, for compact binaries observed via gravitational waves. For example, we infer the merger rate, mass distribution, spin distribution, and spin misalignment distribution for merging binary black holes, accounting for selection bias and measurement error.

This phenomenological framework lets us characterize the compact binary population, without adopting strong assumptions about the underlying physics. Such model-neutral inferences can be important to infer the underlying formation channel for binary black holes (see, e.g,, Mandel and O’Shaughnessy (2010)), as well as to identify how massive stars end their life (e.g., through BH natal masses and spins; see, e.g., Wysocki et al 2018).

For experts: Using synthetic data, we demonstrate how to reconstruct the merger rate versus parameters for binary neutron stars and black holes, and how these inferences improve our ability to constrain future observations like NS tides. Using both real observations (O1 and O2) and synthetic data, we emphasize that the merger rate and mass distribution are correlated: any conclusions about the merger rate must now propagate systematic uncertainty in the mass distribution into their results. Finally, reproducing previously discussed results, we show that current observations are consistent with small BH natal spins, strongly disfavoring a population with large spins; consistent with a deficit of very massive BHs, above the pair-instability cutoff; and do not yet appear to constrain the BH spin-orbit misalignment distribution.

For more information, see

• Wysocki et al Reconstructing phenomenological distributions of compact binaries via gravitational wave observations, available at arxiv.org (1805.06442)