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

TL;DR

This study extends previous work on eccentricity bias in gravitational-wave parameter estimation for binary neutron stars by including spin effects, revealing how eccentricity impacts parameter biases and neutron star property inference.

Contribution

It introduces a comprehensive analysis of eccentricity and spin effects on parameter biases using Fisher and Bayesian methods for realistic BNS populations.

Findings

Biases in mass and spin parameters increase quadratically with eccentricity.

Tidal deformability biases are widely distributed and depend on mass and spin.

Eccentricity can significantly affect neutron star property inference.

Abstract

In our previous work [Phys. Rev. D {\bf 105}. 124022 (2022)], we studied the impact of eccentricity on gravitational-wave parameter estimation for a nonspinning binary neutron star (BNS) system. We here extend the work to a more realistic case by including the spin parameter in the system. As in the previous work, we employ the analytic Fisher-Cutler-Vallisneri method to calculate the systematic bias that can be produced by using noneccentric waveforms in parameter estimation, and we verify the reliability of the method by comparing it with numerical Bayesian parameter estimation results. We generate $10^4$ BNS sources randomly distributed in the parameter space $m_1$-$m_2$-$\chi_{\rm eff}$-$e_0$, where the neutron star mass is in the range of $1 M_\odot \leq m_{1,2}\leq 2M_\odot (m_2 \leq m_1)$, the effective spin is $-0.2 \leq \chi_{\rm eff} \leq0 .2$, and the eccentricity (at the reference frequency 10 Hz) is $0 \leq e_0 \leq 0.024$. For the true value of the tidal deformability ($\lambda$) of neutron stars, we assume the equation of state model APR4. For all gravitational-wave signals emitted from the sources, we calculate the systematic biases ($\Delta \theta$) for the chirp mass ($M_c$), symmetric mass ratio ($\eta$), effective spin ($\chi_{\rm eff}$), and effective tidal deformability ($\tilde{\lambda}$), and obtain generalized distributions of the biases. The distribution of biases in $M_c, \eta$, and $\chi_{\rm eff}$ shows narrow bands that increase or decrease quadratically with increasing $e_0$, indicating a weak dependence of biases on the three parameters. On the other hand, the biases of $\tilde{\lambda}$ are widely distributed depending on the values of the mass and spin parameters at a given $e_0$. We investigate the implications of biased parameters for the inference of neutron star properties by performing Bayesian parameter estimation for specific cases.