English

Systematic bias due to eccentricity in parameter estimation for merging binary neutron stars

General Relativity and Quantum Cosmology 2022-06-13 v2

Abstract

We study the impact of eccentricity on gravitational-wave parameter estimation for binary neutron star systems. For signals with small eccentricity injected into the advanced LIGO sensitivity, we perform Bayesian parameter estimation using the circular waveform model and show how the recovered parameters can be biased from their true values, focusing on the intrinsic parameters the chirp mass (McM_c), the symmetric mass ratio (η\eta), and the tidal deformability (λ~\tilde{\lambda}). By comparing the results between the Bayesian and the analytic Fisher-Cutler-Vallisneri (FCV) methods, we obtain the valid criteria for the FCV approach. Employing the FCV method and using the realistic population of binary neutron star sources distributed in the m1m_1-m2m_2-e0e_0 space, where e0e_0 indicates the eccentricity at 10Hz, we calculate the measurement errors (σθ\sigma_{\theta}) and the systematic biases (Δθ/σθ\Delta \theta/\sigma_{\theta}) and obtain their generalized distributions in the range of 0e00.0250 \leq e_0 \leq 0.025. We find that for all of the three parameters, the biases increase with increasing e0e_0, and this increase is faster for larger e0e_0. The bias is mainly dependent on the value of e0e_0 and weakly dependent on the component masses, and thus the distribution shows a narrow band in the e0e_0-Δθ/σθ\Delta \theta/\sigma_{\theta} plane. We present various posterior examples to illustrate our new findings, such as the bimodality of posteriors. In particular, we give a specific injection-recovery example to demonstrate the importance of including eccentricity in parameter estimation to avoid incorrect predictions of the neutron star equation of state.

Keywords

Cite

@article{arxiv.2205.12531,
  title  = {Systematic bias due to eccentricity in parameter estimation for merging binary neutron stars},
  author = {Hee-Suk Cho},
  journal= {arXiv preprint arXiv:2205.12531},
  year   = {2022}
}

Comments

16 pages, 18 figures, version published in PRD

R2 v1 2026-06-24T11:27:57.315Z