Impact of an improved neutrino energy estimate on outflows in neutron star merger simulations

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Abstract
Binary neutron star mergers are promising sources of gravitational waves for ground-based detectors such as Advanced LIGO. Neutron-rich material ejected by these mergers may also be the main source of r-process elements in the Universe, while radioactive decays in the ejecta can power bright electromagnetic postmerger signals. Neutrino-matter interactions play a critical role in the evolution of the composition of the ejected material, which significantly impacts the outcome of nucleosynthesis and the properties of the associated electromagnetic signal. In this work, we present a simulation of a binary neutron star merger using an improved method for estimating the average neutrino energies in our energy-integrated neutrino transport scheme. These energy estimates are obtained by evolving the neutrino number density in addition to the neutrino energy and flux densities. We show that significant changes are observed in the composition of the polar ejecta when comparing our new results with earlier simulations in which the neutrino spectrum was assumed to be the same everywhere in optically thin regions. In particular, we find that material ejected in the polar regions is less neutron rich than previously estimated. Our new estimates of the composition of the polar ejecta make it more likely that the color and time scale of the electromagnetic signal depend on the orientation of the binary with respect to an observer’s line of sight. These results also indicate that important observable properties of neutron star mergers are sensitive to the neutrino energy spectrum, and may need to be studied through simulations including a more accurate, energy-dependent neutrino transport scheme.
Funding Information
  • National Aeronautics and Space Administration (NAS8-03060, NAS 5-26555)
  • Natural Sciences and Engineering Research Council of Canada
  • National Science Foundation (PHY-1306125, AST-1333129, PHY-1404569, AST-1333520, NSF-1440083, PHY-1151197, PHY-0960291, ACI-1053575)
  • Canada Foundation for Innovation
  • Fonds de Recherche du Québec - Nature et Technologies
  • Einstein Postdoctoral Fellowship (PF4-150122, PF3-140114)
  • Hubble Fellowship (51344.001)
  • Sherman Fairchild Foundation
  • NanoQuébec
  • Réseau de Médecine Génétique Appliquée

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