Surrogate light curve models for kilonovae with comprehensive wind ejecta outflows and parameter estimation for AT2017gfo

TL;DR

This paper develops surrogate light curve models for kilonovae from neutron star mergers, addressing discrepancies in ejecta property estimates by exploring different outflow assumptions and aiding parameter inference for AT2017gfo.

Contribution

The authors introduce a set of surrogate models for kilonova light curves that incorporate wind ejecta outflows and demonstrate their use in parameter estimation, reducing previous discrepancies.

Findings

Surrogate models effectively interpolate kilonova light curves across parameters.

Parameter estimation with these models alleviates ejecta property discrepancies.

Systematic uncertainties significantly impact ejecta property inferences.

Abstract

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 r-process abundance patterns. Our parameter estimation for AT2017gfo shows these surrogate models help alleviate the ejecta property discrepancy while also illustrating the impact of systematic modeling uncertainties on these properties, urging further investigation.