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Gravitational-wave observations have the capability to strongly differentiatebetween different assumptions for how binary compact objects form. In thiswork, we show how to carefully interpolate a marginal likelihood betweenchoices of binary evolution model parameters. Using the StarTrack binaryevolution code, we compare one- and four-dimensional binary evolution models tothe compact binary mergers reported in recent gravitational-wave observingruns. We first consider a one-dimensional model, studying the effect ofsupernova kick velocity (drawn from a Maxwellian with dispersion {\sigma}_eff)on the simulated population of compact binary mergers, and find support forsubstantial SN recoil kicks. We follow this up with a four-dimensional study of{\sigma}_eff, mass transfer efficiency (fa) and the efficiency of angularmomentum depletion from ejected material (\b{eta}) during Roche-lobe accretion,and an observation-driven reduction in the mass-loss rate estimated fromstellar wind models (fwind1). We find that three of them ({\sigma}_eff, fa, andfwind1) can be efficiently limited by these observational comparisons. Afterinitially sampling from a uniform prior in the space of these parameters, werefined our sampling by iteratively estimating a Bayesian likelihood for eachsimulation and fitting that likelihood to a parametric model (a truncatedGaussian) in order to propose new. Our maximum likelihood simulation (K0559)has parameters: {\sigma}_eff = 108.3 km/s (indicating substantial SN recoilkicks), fa = 0.922 (indicating efficient mass transfer), and fwind1 = 0.328(indicating support for reduced wind-driven mass loss). Note that our estimatesare only valid within one particular model of compact binary formation throughisolated binary evolution and do not yet take into account the impact of otheruncertain pieces of stellar physics and binary evolution.

Iteratively Comparing Gravitational-Wave Observations to the Evolution of Massive Stellar Binaries