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The population analysis of compact binaries involves the reconstruction ofsome of the gravitational wave (GW) signal parameters, such as, the mass andthe spin distribution, that gave rise to the observed data. This articleintroduces VAMANA, which reconstructs the binary black hole population using amixture model and facilitates excellent density measurement as informed by thedata. VAMANA uses a mixture of weighted Gaussians to reconstruct the chirp massdistribution. We expect Gaussian mixtures to provide flexibility in modelingcomplex distributions and enable us in capturing details in the astrophysicalchirp mass distribution. Each of the Gaussian in the mixture is combined withanother Gaussian and a power-law to simultaneously model the spin componentaligned with the orbital angular momentum and the mass ratio distribution, thusalso allowing us to capture their variation with the chirp mass. Additionally,we can also introduce broadband smoothing by restricting the Gaussian mixtureto lie within a threshold distance of a predefined reference chirp massdistribution. Using simulated data we show the robustness of our method inreconstructing complex populations for a large number of observations. We alsoapply our method to the publicly available catalog of GW observations madeduring LIGO's and Virgo's first and second observation runs and present thereconstructed mass, spin distribution, and the estimated merger rate of binaryblack holes.

VAMANA: Modeling Binary Black Hole Population with Minimal Assumptions