The Combined Ultraviolet, Optical, and Near-Infrared Light Curves of the Kilonova Associated with the Binary Neutron Star Merger GW170817: Unified Data Set, Analytic Models, and Physical Implications

TL;DR

This paper compiles and models the ultraviolet, optical, and near-infrared light curves of GW170817's kilonova, providing a unified dataset and insights into ejecta components and neutron star physics.

Contribution

It creates the first homogenized, comprehensive dataset for GW170817's kilonova and applies semi-analytical models to elucidate ejecta properties and physical mechanisms.

Findings

Three-component kilonova model fits the data well

Ejecta masses and velocities are estimated for each component

Implications for neutron star properties and r-process enrichment

Abstract

We present the first effort to aggregate, homogenize, and uniformly model the combined ultraviolet, optical, and near-infrared dataset for the electromagnetic counterpart of the binary neutron star merger GW170817. By assembling all of the available data from 18 different papers and 46 different instruments, we are able to identify and mitigate systematic offsets between individual datasets, and to identify clear outlying measurements, with the resulting pruned and adjusted dataset offering an opportunity to expand the study of the kilonova. The unified dataset includes 647 individual flux measurements, spanning 0.45 to 29.4 days post-merger, and thus has greater constraining power for physical models than any single dataset. We test a number of semi-analytical models and find that the data are well modeled with a three-component kilonova model: a "blue" lanthanide-poor component with Mej~0.020 Msol and vej~0.27c; an intermediate opacity "purple" component with Mej~0.047 Msol and vej~0.15c; and a "red" lanthanide-rich component with Mej~0.011 Msol and vej~0.14c. We further explore the possibility of ejecta asymmetry and its impact on the estimated parameters. From the inferred parameters we draw conclusions about the physical mechanisms responsible for the various ejecta components, the properties of the neutron stars, and, combined with an up-to-date merger rate, the implications for r-process enrichment via this channel. To facilitate future studies of this keystone event we make the unified dataset and our modeling code public.