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Unequal mass binary neutron star simulations with neutrino transport: Ejecta and neutrino emission

Vincent, Trevor and Foucart, Francois and Duez, Matthew D. and Haas, Roland and Kidder, Lawrence E. and Pfeiffer, Harald P. and Scheel, Mark A. (2020) Unequal mass binary neutron star simulations with neutrino transport: Ejecta and neutrino emission. Physical Review D, 101 (4). Art. No. 044053. ISSN 2470-0010. doi:10.1103/physrevd.101.044053.

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We present 12 new simulations of unequal mass neutron star mergers. The simulations are performed with the SpEC code, and utilize nuclear-theory-based equations of state and a two-moment gray neutrino transport scheme with an improved energy estimate based on evolving the number density. We model the neutron stars with the SFHo, LS220, and DD2 equations of state (EOS) and we study the neutrino and matter emission of all 12 models to search for robust trends between binary parameters and emission characteristics. We find that the total mass of the dynamical ejecta exceeds 0.01  M⊙ only for SFHo with weak dependence on the mass ratio across all models. We find that the ejecta have a broad electron fraction (Y_e) distribution (≈0.06–0.48), with mean 0.2. Y_e increases with neutrino irradiation over time, but decreases with increasing binary asymmetry. We also find that the models have ejecta with a broad asymptotic velocity distribution (≈0.05–0.7c). The average velocity lies in the range 0.2c−0.3c and decreases with binary asymmetry. Furthermore, we find that disk mass increases with binary asymmetry and stiffness of the EOS. The Y_e of the disk increases with softness of the EOS. The strongest neutrino emission occurs for the models with soft EOS. For (anti) electron neutrinos we find no significant dependence of the magnitude or angular distribution or neutrino luminosity with mass ratio. The heavier neutrino species have a luminosity dependence on mass ratio but an angular distribution which does not change with mass ratio.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Foucart, Francois0000-0003-4617-4738
Duez, Matthew D.0000-0002-0050-1783
Haas, Roland0000-0003-1424-6178
Kidder, Lawrence E.0000-0001-5392-7342
Pfeiffer, Harald P.0000-0001-9288-519X
Additional Information:© 2020 American Physical Society. Received 5 August 2019; accepted 9 January 2020; published 28 February 2020. We would like to acknowledge helpful discussions with Tim Dietrich, Wyatt Brege, and Sergei Ossokine. F. F. gratefully acknowledges support from NASA through Grant No. 80NSSC18K0565, and from the NSF through Grant No. PHY-1806278. H. P. gratefully acknowledges support from the NSERC Canada. L. K. acknowledges support from NSF Grant No. PHY-1606654. M. S. acknowledges support from NSF Grants No. PHY-170212 and No. PHY-1708213. L. K. and M. S. also thank the Sherman Fairchild Foundation for their support. Computations were performed on the supercomputer Briaree from the Universite de Montreal, managed by Calcul Quebec and Compute Canada. The operation of these supercomputers is funded by the Canada Foundation for Innovation, NanoQuebec, Réseau de Médecine Génétique Appliquée (RMGA) and the Fonds de recherche du Quebec—Nature et Technologie (FRQ-NT). Computations were also performed on the Minerva cluster at the Max-Planck-Institute for Gravitational Physics, and the GPC and Niagara supercomputers at the SciNet HPC Consortium [96]. SciNet is funded by the Canada Foundation for Innovation, the Government of Ontario, Ontario Research Fund—Research Excellence, and the University of Toronto.
Group:TAPIR, Walter Burke Institute for Theoretical Physics
Funding AgencyGrant Number
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
Sherman Fairchild FoundationUNSPECIFIED
Canada Foundation for InnovationUNSPECIFIED
Réseau de Médecine Génétique Appliquée (RMGA)UNSPECIFIED
Fonds de recherche du Québec - Nature et technologies (FRQNT)UNSPECIFIED
Government of OntarioUNSPECIFIED
Ontario Research Fund-Research ExcellenceUNSPECIFIED
University of TorontoUNSPECIFIED
Issue or Number:4
Record Number:CaltechAUTHORS:20200302-134402101
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101655
Deposited By: Tony Diaz
Deposited On:02 Mar 2020 22:20
Last Modified:16 Nov 2021 18:04

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