Neutrinos are copiously emitted by neutron star mergers, due to the high temperatures reached by dense matter during the merger and its aftermath. Neutrinos influence the merger dynamics and shape the properties of the ejecta, including the resulting
We investigate rprocess nucleosynthesis and kilonova emission resulting from binary neutron star (BNS) mergers based on a threedimensional (3D) generalrelativistic magnetohydrodynamic (GRMHD) simulation of a hypermassive neutron star (HMNS) remnant. The simulation includes a microphysical finitetemperature equation of state (EOS) and neutrino emission and absorption effects via a leakage scheme. We track the thermodynamic properties of the ejecta using Lagrangian tracer particles and determine its composition using the nuclear reaction network SkyNet. We investigate the impact of neutrinos on the nucleosynthetic yields by varying the neutrino luminosities during postprocessing. The ejecta show a broad distribution with respect to their electron fraction Ye, peaking between ∼0.25–0.4 depending on the neutrino luminosity employed. We find that the resulting rprocess abundance patterns differ from solar, with no significant production of material beyond the second rprocess peak when using luminosities recorded by the tracer particles. We also map the HMNS outflows to the radiation hydrodynamics code SNEC and predict the evolution of the bolometric luminosity as well as broadband light curves of the kilonova. The bolometric light curve peaks on the timescale of a day and the brightest emission is seen in the infrared bands. This is the first direct calculation of the rprocess yields and kilonova signal expected from HMNS winds based on 3D GRMHD simulations. For longerlived remnants, these winds may be the dominant ejecta component producing the kilonova emission.
more » « less NSFPAR ID:
 10385189
 Publisher / Repository:
 Oxford University Press
 Date Published:
 Journal Name:
 Monthly Notices of the Royal Astronomical Society
 Volume:
 518
 Issue:
 4
 ISSN:
 00358711
 Page Range / eLocation ID:
 p. 53135322
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
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