Space-based gravitational wave (GW) detectors are expected to detect the
stellar-mass binary black holes (SBBHs) inspiralling in the low-frequency band,
which exist in several years before the merger. Accurate GW waveforms in the
inspiral phase are crucial for the detection and analysis of those SBBHs. In
our study, based on post-Newtonian (PN) models, we investigate the differences
in the detection, accuracy requirement, and parameter estimation of SBBHs in
the cases of LISA, Taiji, and their joint detection. We find that low-order PN
models are sufficient for simulating low-mass ($le 50 mathrm{M}_odot$)
SBBHs population. Moreover, for detectable SBBHs in space-based GW detectors,
over 90% of the GW signals from low-order PN models meet accuracy requirement.
Additionally, different PN models do not exhibit significant differences in
Bayesian inference. Our research provides a comprehensive reference for
balancing computational resources and the desired accuracy of GW waveform
generation. It highlights the suitability of low-order PN models for simulating
SBBHs and emphasizes their potential in the detection and parameter estimation
of SBBHs.
Space-based gravitational wave detectors are expected to detect stellar-mass binary black holes inspiralling in the low-frequency band, which exist several years before the merger. Accurate gravitational wave (GW) waveforms in the inspiral phase are crucial for the detection and analysis of these binary black holes. In this study, we investigate the differences in the detection, accuracy requirement, and parameter estimation of stellar-mass binary black holes in the cases of LISA, Taiji, and their joint detection using post-Newtonian (PN) models.
Summary of Key Findings:
- Low-order PN models are sufficient for simulating low-mass SBBHs (≤ 50 M☉) population.
- Over 90% of the GW signals from low-order PN models meet accuracy requirements for detectable SBBHs in space-based GW detectors.
- Different PN models do not exhibit significant differences in Bayesian inference.
Roadmap for the Future:
1. Balancing Computational Resources and Accuracy
Our research provides a comprehensive reference for balancing computational resources and the desired accuracy of GW waveform generation. As low-order PN models are shown to be sufficient for simulating low-mass SBBHs, researchers can prioritize computational efficiency without sacrificing accuracy in these cases.
2. Potential of Low-Order PN Models
The study highlights the suitability of low-order PN models for simulating SBBHs and emphasizes their potential in the detection and parameter estimation of SBBHs. This opens up possibilities for further exploring the capabilities of low-order PN models in studying other astrophysical phenomena.
3. Improved Parameter Estimation
While the study finds that different PN models do not significantly differ in Bayesian inference, further research could focus on refining parameter estimation techniques to enhance the accuracy and reliability of analyzing SBBHs. This would contribute to a deeper understanding of the properties and behavior of these binary black holes.
4. Future Collaborative GW Detection
The joint detection of SBBHs by space-based GW detectors like LISA and Taiji holds promising prospects. Future collaborations between these detectors can enhance the overall detection capability and improve the accuracy of parameter estimation. The challenges associated with coordinating these efforts and combining data from multiple detectors will need to be addressed.
In conclusion, our study sheds light on the use of low-order PN models for simulating SBBHs and their significance in the detection and analysis of these astrophysical phenomena. By striking a balance between computational resources and accuracy, researchers can leverage the potential of low-order PN models to explore the properties of binary black holes further. Collaboration and improved parameter estimation techniques will contribute to greater insights into the nature of SBBHs.