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arXiv · 1801.05433

Progenitors of gravitational wave mergers: Binary evolution with the stellar grid-based code ComBinE

Matthias U. Kruckow·Thomas M. Tauris·Norbert Langer·Michael Kramer·Robert G. Izzard
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Abstract

The first gravitational wave detections of mergers between black holes and neutron stars represent a remarkable new regime of high-energy transient astrophysics. The signals observed with LIGO-Virgo detectors come from mergers of extreme physical objects which are the end products of stellar evolution in close binary systems. To better understand their origin and merger rates, we have performed binary population syntheses at different metallicities using the new grid-based binary population synthesis code ComBinE. Starting from newborn pairs of stars, we follow their evolution including mass loss, mass transfer and accretion, common envelopes and supernova explosions. We apply the binding energies of common envelopes based on dense grids of detailed stellar structure models, make use of improved investigations of the subsequent Case BB Roche-lobe overflow and scale supernova kicks according to the stripping of the exploding stars. We demonstrate that all the double black hole mergers, GW150914, LVT151012, GW151226, GW170104, GW170608 and GW170814, as well as the double neutron star merger GW170817, are accounted for in our models in the appropriate metallicity regime. Our binary interaction parameters are calibrated to match the accurately determined properties of Galactic double neutron star systems, and we discuss their masses and types of supernova origin. Using our default values for the input physics parameters, we find a double neutron star merger rate of about 3.0 Myr^-1 for Milky-Way equivalent galaxies. Our upper limit to the merger-rate density of double neutron stars is R=400 yr^-1 Gpc^-3 in the local Universe (z=0).

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Matthias U. Kruckow, Thomas M. Tauris, Norbert Langer, Michael Kramer, Robert G. Izzard. 2018-01-16. Progenitors of gravitational wave mergers: Binary evolution with the stellar grid-based code ComBinE. https://doi.org/10.1093/mnras%2Fsty2190

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