The Cost of Circularity: Quantifying Eccentricity-Induced Biases in Binary Black Hole Inference

Abstract: Dynamically assembled binary black holes are expected to retain measurable orbital eccentricity in the LIGO-Virgo-KAGRA band, but most parameter estimation analyses still assume quasi-circular inspirals. This raises a critical question: how strongly does unmodeled eccentricity bias the inferred properties of BBH mergers? We address this by injecting eccentric signals generated with TEOBResumS-Dali and recovering them using the circular, precessing IMRPhenomXPHM waveform model. Across $20$-$80 \, M_\odot$ and eccentricities up to $e=0.5$, we find that circular waveform models remain reliable only for very small eccentricities. Above $e\sim0.2$ at 10 Hz, recovered masses, spins, inclination, and distances begin to show significant systematic offsets. Circular precessing templates mimic eccentric amplitude and phase modulations by introducing artificial precession, highlighting a major degeneracy between these effects. For high-mass, moderately eccentric mergers, circular models misestimate parameters at a level that would bias astrophysical interpretation and population studies. Our results establish the parameter-space boundaries where eccentric waveform models become essential for accurate inference in current and next-generation detectors.