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Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations I: Black Hole-Neutron Star Mergers (2103.02608v3)

Published 3 Mar 2021 in astro-ph.HE

Abstract: Mergers of black hole-neutron star (BHNS) binaries have now been observed by GW detectors with the recent announcement of GW200105 and GW200115. Such observations not only provide confirmation that these systems exist, but will also give unique insights into the death of massive stars, the evolution of binary systems and their possible association with gamma-ray bursts, $r$-process enrichment and kilonovae. Here we perform binary population synthesis of isolated BHNS systems in order to present their merger rate and characteristics for ground-based GW observatories. We present the results for 420 different model permutations that explore key uncertainties in our assumptions about massive binary star evolution (e.g. mass transfer, common-envelope evolution, supernovae), and the metallicity-specific star formation rate density, and characterize their relative impacts on our predictions. We find intrinsic local BHNS merger rates spanning $\mathcal{R}{\rm{m}}0 \approx 4$-$830\,\rm{Gpc}{-3}\,\rm{yr}{-1}$ for our full range of assumptions. This encompasses the rate inferred from recent BHNS GW detections, and would yield detection rates of $\mathcal{R}{\rm{det}} \approx 1$-$180\, \rm{yr}{-1}$ for a GW network consisting of LIGO, Virgo and KAGRA at design sensitivity. We find that the binary evolution and metallicity-specific star formation rate density each impact the predicted merger rates by order $\mathcal{O}(10)$. We also present predictions for the GW detected BHNS merger properties and find that all 420 model variations predict that $\lesssim 5\%$ of the BHNS mergers have BH masses $\gtrsim 18\,M_{\odot}$, total masses $ \gtrsim 20\,M_{\odot}$, chirp masses $\gtrsim 5.5\,M_{\odot}$, mass ratios $ \gtrsim 12$ or $\lesssim 2$. Moreover, we find that massive NSs $\gtrsim 2\,M_{\odot}$ are expected to be commonly detected in BHNS mergers in almost all our model variations.

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