Systematic bias due to eccentricity in parameter estimation for merging binary neutron stars
Hee-Suk Cho

TL;DR
This study investigates how small orbital eccentricities in binary neutron star mergers bias gravitational-wave parameter estimates, emphasizing the importance of accounting for eccentricity to accurately determine neutron star properties.
Contribution
The paper introduces a systematic analysis of eccentricity-induced biases in parameter estimation, comparing Bayesian and Fisher methods, and highlights the significance of including eccentricity in models.
Findings
Biases increase with eccentricity, especially beyond 0.01.
Biases are mainly dependent on eccentricity, weakly on masses.
Including eccentricity prevents incorrect neutron star equation of state predictions.
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 (), the symmetric mass ratio (), and the tidal deformability (). 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 -- space, where indicates the eccentricity at 10Hz, we calculate the measurement errors () and the…
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