The impact of BNS outflow mass models on parameter estimation of kilonova observations

One can regard binary neutron star mergers as having maps between intrinsic properties, outflow properties, and observables. However, due to uncertainties in the equation of state, observational degeneracies, and uncertainties in radiative transfer processes, many ‘holes’ exist in these maps. To date, several groups have proposed fitting formulae based on collections of detailed merger simulations in order to relate BNS outflow properties (ejecta mass, composition, and velocity) and intrinsic properties (mass, radius). What is less well-studied is the uncertainties which arise due to differences between said formulae in light curve modeling and in parameter estimation.

Previously, we measured a suite of semi-analytical BNS dynamical and post-merger ejecta formulae and reported on their levels of combined agreement across a broad parameter space. Here, we apply these formulae to a one-dimensional kilonova model and perform nested sampling to extract the most likely intrinsic parameters from mock light curve data. Our science goals are twofold. First, we wish to establish, as a baseline, how well one can recover source (and outflow) parameters from fiducial observations; we then seek to measure what biases are introduced in this process when assuming one outflow model versus another.