Simulation of chirp mass distribution of neutron star and black hole merger events for gravitational-wave radiation

The gravitational waves (GWs) from the merger events of binary black hole (BH-BH) and binary neutron star (NS-NS) have been detected by LIGO-Virgo (O1 and O2). Besides, GWs from the NS-BH mergers have been recently reported and might be hopefully confirmed in the near future. The mass distributions of these merger events are poorly understood now; thus, LIGO-Virgo adopted a simple cut rule for chirp mass ($\mathcal{M}$) to distinguish the GW event candidates: $\mathcal{M}<2.1M_{\odot }$ for NS-NS, $2.1M_{\odot }<\mathcal{M}<4.35M_{\odot }$ for NS-BH, and $\mathcal{M}>4.35M_{\odot }$ for BH-BH. We tested its validity by simulating the chirp mass ($\mathcal{M}$) distributions in two synthetic models, i.e., Model Galaxy and Model LIGO, in which the masses of BHs and NSs are observed by the electromagnetic spectrum observations in our Galaxy and inferred by LIGO-Virgo detection (O1 and O2), respectively. The simulation shows that it is unsuitable for Model LIGO due to the BHs inferred by LIGO-Virgo are usually bigger than those in our Galaxy, and $\mathcal{M}$ of NS-BH events would distribute in the range of $2.1M_{\odot }<\mathcal{M}<7.3M_{\odot }$, which partially overlaps with those of BH-BH events. Therefore, we suggest that the new searching round of LIGO-Virgo (e.g., O3) should carefully seek out the underlying NS-BH candidates in the range of $2.1M_{\odot }<\mathcal{M}<7.3M_{\odot }$.

Figure 1

Mass likelihoods for the BHs ($\mathrm{N}=20$) inferred by LIGO-Virgo (O1 and O2) as shown in Table 1, where the primary BHs and secondary BHs are suffixed by “1” and “2,” respectively. All likelihoods are normalized to 1, so that the enclosed area of each likelihood is same.

Figure 2

The comparison for chirp mass distribution of Model Galaxy and LIGO after Monte Carlo random sampling, where cut line 1 and 2 represent the original cut rule used by [3], and cut line 3 is the newly added rule based on our simulation.