A Broad Grid of 2D Kilonova Emission Models

Abstract Depending upon the properties of their compact remnants and the physics included in the models, simulations of neutron star mergers can produce a broad range of ejecta properties. The characteristics of this ejecta, in turn, define the kilonova emission. To explore the effect of ejecta prop...

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Bibliographic Details
Published in:The Astrophysical journal Vol. 918; no. 1; pp. 10 - 26
Main Authors: Wollaeger, R. T., Fryer, C. L., Chase, E. A., Fontes, C. J., Ristic, M., Hungerford, A. L., Korobkin, O., O’Shaughnessy, R., Herring, A. M.
Format: Journal Article
Language:English
Published: Philadelphia The American Astronomical Society 01-09-2021
IOP Publishing
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Summary:Abstract Depending upon the properties of their compact remnants and the physics included in the models, simulations of neutron star mergers can produce a broad range of ejecta properties. The characteristics of this ejecta, in turn, define the kilonova emission. To explore the effect of ejecta properties, we present a grid of two-component 2D axisymmetric kilonova simulations that vary mass, velocity, morphology, and composition. The masses and velocities of each component vary, respectively, from 0.001 to 0.1 M ⊙ and 0.05 to 0.3 c , covering much of the range of results from the neutron star merger literature. The set of 900 models is constrained to have a toroidal low electron fraction ( Y e ) ejecta with a robust r -process composition and either a spherical or lobed high- Y e ejecta with two possible compositions. We simulate these models with the Monte Carlo radiative transfer code SuperNu using a full suite of lanthanide and fourth-row element opacities. We examine the trends of these models with parameter variation, show how they can be used with statistical tools, and compare the model light curves and spectra to those of AT2017gfo, the electromagnetic counterpart of GW170817.
Bibliography:AAS29324
High-Energy Phenomena and Fundamental Physics
National Science Foundation (NSF)
LA-UR-20-30338
USDOE Laboratory Directed Research and Development (LDRD) Program
89233218CNA000001; 20190021DR; DGE-1450006; AST-1909534
ISSN:0004-637X
1538-4357
DOI:10.3847/1538-4357/ac0d03