Interpolating detailed simulations of kilonovae: Adaptive learning and parameter inference applications
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Ristić, M.; Champion, E.; O'Shaughnessy, R.; Wollaeger, R.;
Korobkin, O.; Chase, E. A.; Fryer, C. L.; Hungerford, A. L.; Fontes, C. J.
Detailed radiative transfer simulations of kilonovae are difficult to apply directly to observations; they only sparsely cover simulation parameters, such as the mass, velocity, morphology, and composition of the ejecta. On the other hand, semianalytic models for kilonovae can be evaluated continuously over model parameters, but neglect important physical details which are not incorporated in the simulations, thus introducing systematic bias. Starting with a grid of two-dimensional anisotropic simulations of kilonova light curves covering a wide range of ejecta properties, we apply adaptive learning techniques to iteratively choose new simulations and produce high-fidelity surrogate models for those simulations. These surrogate models allow for continuous evaluation across model parameters while retaining the microphysical details about the ejecta. Using a code for multimessenger inference developed by our group, we demonstrate how to use our interpolated models to infer kilonova parameters. Comparing to inferences using simplified analytic models, we recover different ejecta properties. We discuss the implications of this analysis which is qualitatively consistent with similar previous work using detailed ejecta opacity calculations and which illustrates systematic challenges for kilonova modeling. An associated data and code release provides our interpolated light-curve models, interpolation implementation which can be applied to reproduce our work or extend to new models, and our multimessenger parameter inference engine.
Constraining inputs to realistic kilonova simulations through comparison to observed r-process abundances
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Ristić, M.; Holmbeck, E.; Wollaeger, R.; Korobkin, O.; Champion, E.; O'Shaughnessy, R.; Fryer, C.; Fontes, C.; Mumpower, M.; Sprouse, T.
Kilonovae, one source of electromagnetic emission associated with neutron star mergers, are powered by the decay of radioactive isotopes in the neutron-rich merger ejecta. Models for kilonova
emission consistent with available modeling and the electromagnetic counterpart to GW170817 also
predict characteristic abundance patterns, determined by the relative balance of different types of
material in the outflow. Assuming the observed source is prototypical, this inferred abundance pattern in turn must match r -process abundances deduced by other means, such as what is observed in
the solar system. We report on analysis comparing the input mass-weighted elemental compositions
adopted in our radiative transfer simulations to the mass fractions of elements in the Sun. We characterise the extent to which our parameter inference results depend on our assumed composition
for the dynamical and wind ejecta and examine how the new results compare to previous work. We
find that a mass ratio of Mw/Md = 2.81 reproduces the observed AT2017gfo kilonova light curves
while also producing the abundance of neutron-capture elements in the solar system.
Surrogate light curve models for kilonovae with comprehensive wind ejecta outflows and parameter estimation for AT2017gfo
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Kedia, A.; Ristić, M.; O'Shaughnessy, R.; Yelikar, A. B.; Wollaeger, R. T.; Korobkin, O.; Chase, E. A.; Fryer, C. L.; Fontes, C. J.
The electromagnetic emission resulting from neutron star mergers have been shown to encode properties of the ejected material in their light curves. The ejecta properties inferred from the kilonova emission has been in tension with those calculated based on the gravitational wave signal and numerical relativity models. Motivated by this tension, we construct a broad set of surrogate light curve models derived for kilonova ejecta. The four-parameter family of two-dimensional anisotropic simulations and its associated surrogate explore different assumptions about the wind outflow morphology and outflow composition, keeping the dynamical ejecta component consistent. We present the capabilities of these surrogate models in interpolating kilonova light curves across various ejecta parameters and perform parameter estimation for AT2017gfo both without any assumptions on the outflow and under the assumption that the outflow must be representative of solar \emph{r}-process abundance patterns. Our parameter estimation for AT2017gfo shows these new surrogate models help alleviate the ejecta property discrepancy while also illustrating the impact of systematic modeling uncertainties on these properties, urging further investigation.