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Does Matter Matter? Using the Mass Distribution to Distinguish Neutron Stars and Black Holes

  • Authors: Maya Fishbach, Reed Essick, and Daniel E. Holz

2020 The Astrophysical Journal Letters 899 L8.

  • Provider: AAS Journals

Caption: Figure 7.

Astrophysical merger rate within two different mass bins: for BNS, 1 M < m2 < m1 < 2.5 M, and for BBH, 5 M < m2 < m1 < 100 M, as inferred by each of the models. The dashed open probability density curves centered below ﹩{ \mathcal R }\sim {10}^{2}\,\ {\mathrm{Gpc}}^{-3}\ {\mathrm{yr}}^{-1}﹩ show the BBH rate inference and the solid filled curves show the BNS rate inference for the POWER LAW (blue), POWER LAW + DIP (orange), and POWER LAW + DIP + BREAK (green) models. For comparison, the gray shaded regions show the median and 90% credible intervals of the BBH (dashed) and BNS (solid) rates inferred by the LVC in Abbott et al. (2019a, 2019b). Allowing for a dip and break between NS and BH masses tends to decorrelate the merger rates, increasing the inferred BNS merger rate and decreasing the BBH merger rate.

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