Simulated Kilonova Spectra Interpolation with Comparison to AT2017gfo Observations

ORAL

Abstract

Neutron star mergers could be the primary channel for heavy-element nucleosynthesis in the Universe. Kilonovae provide, via observations of their spectra, a direct avenue to assess how much this channel contributes to r-process abundances. In this work, we present a simple kilonova spectral interpolation technique trained against our existing library of kilonova radiative transfer simulations which use state-of-the-art, physically-motivated atomic opacities and lines. Our model accurately reflects spectra for anisotropic (axisymmetric) time-dependent kilonova models over our presently four-dimensional kilonova model space. We compare our interpolated spectra to the AT2017gfo spectral data and find parameters consistent with our previous inferences deduced from long-term multiwavelength light curve observations. However, the spectral observations have significant systematic short-wavelength residuals relative to our models, which we cannot explain within our existing framework. Similar to previous studies, we argue an additional blue component is required. We find that a light, slow-moving lanthanide-free component could supplement early-time short-wavelength model deficits.

*ROS and MR acknowledge support from NSF AST1909534. CJF, CLF, OK, RW were supported by the US Department of Energy through the Los Alamos National Laboratory. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of U.S. Department of Energy (Contract No. 89233218CNA000001). Research presented in this article was supported by the Laboratory Directed Research and Development program of Los Alamos National Laboratory under project number 20190021DR. This research used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the U.S. Department of Energy National Nuclear Security Administration under Contract No. 89233218CNA000001.

Presenters

  • Marko Ristic

    • Rochester Institute of Technology

Authors

  • Marko Ristic

    • Rochester Institute of Technology
  • Richard O'Shaughnessy

    • Rochester Institute of Technology
  • V. Ashley Villar

    • Penn State Eberly College of Science
    • Penn State University
  • Ryan Wollaeger

    • Los Alamos National Laboratory
    • Los Alamos National Lab
  • Oleg Korobkin

    • Los Alamos National Laboratory
  • Chris L Fryer

    • Los Alamos National Laboratory
  • Christopher J Fontes

    • Los Alamos National Laboratory