Semi-Parametric Heirarchical Inference of LIGO-Virgos Binary Black Hole Mass Distribution

The LIGO and Virgo detectors have now detected nearly a hundred gravitational waves, originating from merging compact binaries, which contain information about the properties of each of the merging objects such as their masses and spins. With a catalog of observed merging compact binaries, one can infer their collective population properties through heirarchical inference, producing population probability distributions over the objects source parameters. In this talk I will motivate the need to move towards semi-parametric models, capable of fitting unexpected features, in our inferences of the distiribution of black hole masses. I will conclude by highlighting one such model based on cubic splines and present the results from applying this specific model to infer the binary black hole mass spectrum using both the second and third gravitational-wave transient catalogs (GWTC-2, GWTC-3).