A Comparative Study of Kilonova Models in Pure-EM and Multimessenger Parameter Estimation

Various kilonova models are employed in the literature to constrain both the intrinsic and emission properties of candidate events. This suite of commonly-used models vary in their dependencies, geometries, dimensionality, composition, and physical assumptions about the merger and post-merger environment.

We present a comparative study of several kilonova models and report on their relative behavior and similarities across a broad parameter space when employed in parameter estimation (PE) of the intrinsic properties (e.g. M_c or M_tot) and of the outflow properties (such as composition or mass). This work builds upon our previous studies of semi-analytical ejecta formulae and of their performance in PE. We ‘calibrate’ the set of models by having each of them fit a common set of fake data points and recording the parameters required to generate it. By using the models to produce light curves for the same mock binary system, we assess how differences in outflow assumptions correspond to different observables.