Systematic Biases in Gravitational-Wave Parameter Estimation from Neglecting Orbital Eccentricity in Space-Based Detectors
Abstract
Accurate modeling of gravitational-wave signals is essential for reliable inference of compact-binary source parameters, particularly for future space-based detectors operating in the milli- and deci-Hertz bands. In this work, we systematically investigate the parameter-estimation biases induced by neglecting orbital eccentricity when analyzing eccentric compact-binary coalescences with quasi-circular waveform templates. Focusing on the deci-Hertz detector B-DECIGO and the milli-Hertz detector LISA, we model eccentric inspiral signals using a frequency-domain waveform that incorporates eccentricity-induced higher harmonics and the time-dependent response of spaceborne detectors. We quantify systematic biases in the chirp mass, symmetric mass ratio, and luminosity distance using both Bayesian inference and the Fisher-Cutler-Vallisneri (FCV) formalism, and assess their significance relative to statistical uncertainties. By constructing mock gravitational-wave catalogs spanning stellar-mass and massive black-hole binaries, we identify critical initial eccentricities at which systematic errors become comparable to statistical errors. We find that for B-DECIGO, even very small eccentricities, at 0.1 Hz, can lead to significant biases, whereas for LISA such effects typically arise at larger eccentricities, at Hz, due to the smaller number of in-band cycles. Comparisons between FCV predictions and full Bayesian analyses demonstrate good agreement within the regime where waveform mismatches remain small, especially when extrinsic parameters are pre-aligned to minimize mismatches. Our results highlight the necessity of incorporating eccentricity in waveform models for future space-based gravitational-wave observations.
Keywords
Cite
@article{arxiv.2601.07739,
title = {Systematic Biases in Gravitational-Wave Parameter Estimation from Neglecting Orbital Eccentricity in Space-Based Detectors},
author = {Jin-Zhao Yang and Jia-Hao Zhong and Tao Yang},
journal= {arXiv preprint arXiv:2601.07739},
year = {2026}
}
Comments
17 pages, 9 figures